Willem J van Leeuwen

Interests

Teaching

Remote Sensing Science, Land use and land cover, Biogeography, Field Methods in Physical Geography, snow, decision support

Research

Remote Sensing Science, Climate variability and change, Snow, Drought and Disturbance, Land Surface phenology, Land use and land cover change , Biogeography,

Courses

Scholarly Contributions

Chapters

• Glenn, E. P., Leeuwen, W. J., Olsson, A. D., Sridhar, B. B., & Nagler, P. L. (2018). Hyperspectral Remote Sensing Tools for Quantifying Plant Litter and Invasive Species in Arid Ecosystems. In Hyperspectral remote sensing of vegetation. doi:10.1201/9780429431166-6
• Romo Leon, J. R., van Leeuwen, W. J., & Castellanos Villegas, A. E. (2013). Aplicaciones de percepcion remota y analisis espacial en la evaluacion del uso del territorio. In Percepcion Remota Para el Analisis de la Distribucion y Cambios de Uso de Suelo en Zonas Aridas y Semiaridas.. Ciudad Juárez, Mexico: Universidad Autónoma de Ciudad Juárez Press.
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  Romo Leon, J.R., Willem J.D. van Leeuwen, A.E. Castellanos Villegas, 2013. In Percepcion Remota Para el Analisis de la Distribucion y Cambios de Uso de Suelo en Zonas Aridas y Semiaridas .E. Sanchez Flores and R.E. Diaz Caravantes (Eds.), Dinamicas locales del cambio global. Aplicaciones de percepcion remota y analisis espacial en la evaluacion del uso del territorio. Ciudad Juárez, Mexico: Universidad Autónoma de Ciudad Juárez Press.
• van Leeuwen, W. J., Nagler, P. L., Sridhar, B. M., Olsson, A. D., J.D., W., & Glenn, E. P. (2012). Hyperspectral Remote Sensing Tools for Quantifying Plant Litter and Invasive Species in Arid Ecosystems. CRC.
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  ;Full Citation: Hyperspectral Remote Sensing Tools for Quantifying Plant Litter and Invasive Species in Arid EcosystemsPamela Lynn Nagler, B.B. Maruthi Sridhar, Aaryn Dyami Olsson, Willem J.D. van Leeuwen, and Edward P. Glenn, 2012. Hyperspectral Remote Sensing Tools for Quantifying Plant Litter and Invasive Species in Arid Ecosystems In: Hyperspectral remote sensing of vegetation Edts. Prasad Srinivasa Thenkabail; J G Lyon; Alfredo Huete; Boca Raton, FL, CRC Press.;Collaborative with graduate student: Yes;Collaborative with faculty member at UA: Yes;Other collaborative: Yes;Specify other collaborative: USGS collaoration;
• van Leeuwen, W. J., Nagler, P. L., Sridhar, B. M., Olsson, A. D., J.D., W., & Edward, a. (2011). Hyperspectral Remote Sensing Tools for Quantifying Plant Litter and Invasive Species in Arid Ecosystems. CRC press.
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  ;Your Role: Helped write a section and provided ASD data;Full Citation: Ch 16 Hyperspectral Remote Sensing Tools for Quantifying Plant Litter and Invasive Species in Arid Ecosystems, 2012 Pamela Lynn Nagler, B.B. Maruthi Sridhar, Aaryn Dyami Olsson, Willem J.D. van Leeuwen,and Edward P. Glenn pp 362-390. Editors: P.S. Thenkabail, J.G. Lyon and A. Huete. In: Hyperspectral Remote Sensing of VegetationCRC press. pp705;Collaborative with faculty member at UA: Yes;Other collaborative: Yes;Specify other collaborative: USGS;
• Glenn, E. P., Miura, T., Leeuwen, W. J., Didan, K., & Huete, A. (2010). MODIS Vegetation Indices. In Land Remote Sensing and Global Environmental Change(pp pp 579–602). doi:10.1007/978-1-4419-6749-7_26
• van Leeuwen, W. J., uete, A., Didan, K., Willem, J., T., G., & E., . (2010). MODIS Vegetation Indices.. Springer-Verlag.
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  Land Remote Sensing and Global Environmental ChangeRemote Sensing and Digital Image Processing, 2011, Volume 11, Part 5, 579-602, DOI: 10.1007/978-1-4419-6749-7_26http://www.springer.com/astronomy/extraterrestrial+physics,+space+sciences/book/978-1-4419-6748-0;Your Role: I contributed a section to the chapter that described the use of spectral vegetation indices in natural resource and agricultural decision support systems;Full Citation: Huete, A., Didan, K., #Willem J.D. van Leeuwen, Miura, T., Glenn, E., 2010. PART V: MODIS Vegetation Indices.pp579-602 In: Land Remote Sensing and Global Environmental Change: NASA's Earth Observing System and the Science of ASTER and MODIS. B. Ramachandran, C. Justice and M. Abrams (Editors). Springer-Verlag, New York. 750 pp. ;Collaborative with faculty member at UA: Yes;
• van Leeuwen, W. J. (2009). Visible, Near-IR & Shortwave IR Spectral Characteristics of Terrestrial Surfaces.. SAGE.
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  ;Your Role: Designed this original chapter and provided original data and analysis of component spectra that I collected and processed for this book chapter.;Full Citation: van Leeuwen, Willem J.D., 2009. Chapter 3: Visible, Near-IR & Shortwave IR Spectral Characteristics of Terrestrial Surfaces. In: The Sage Handbook of Remote Sensing. Editors: T. Warner, D. Nellis and G. Foody. SAGE. 33-50;
• Van Leeuwen, W. J. (2008). Visible, Near-IR, and Shortwave IR Spectral Characteristics of Terrestrial Surfaces. In The SAGE Handbook of Remote Sensing. SAGE Publications Inc. doi:10.4135/9780857021052.N3

Journals/Publications

• Biederman, J. A., Walter, J., Svoma, B., Van Leeuwen, W. J., & Broxton, P. D. (2023). Subseasonal to Seasonal Streamflow Forecasting in a Semiarid Watershed. Journal of the American Water Resources Association, 59(6), 1493–1510.
• Behrangi, A., Barron‐Gafford, G., Javadian, M., Smith, W. K., Lee, K., Knowles, J. F., Scott, R. L., Fisher, J. B., Moore, D. J., & Leeuwen, W. J. (2022). Canopy Temperature Is Regulated by Ecosystem Structural Traits and Captures the Ecohydrologic Dynamics of a Semiarid Mixed Conifer Forest Site. Journal of Geophysical Research: Biogeosciences, 127(2). doi:10.1029/2021jg006617
• Breshears, D. D., Gallery, R. E., Leeuwen, W. J., Mitchell, J. J., Barnes, M., & Gebhardt, M. (2022). Evaluation of vegetation indices and imaging spectroscopy to estimate foliar nitrogen across disparate biomes. Ecosphere, 13(3). doi:10.1002/ecs2.3992
• Broxton, P. D., Dwivedi, R., Biederman, J. A., Lee, K., & van Leeuwen, W. J. (2022). Snowtography quantifies effects of forest cover on net water input to soil at sites with ephemeral or stable seasonal snowpack in Arizona, USA. Ecohydrology. doi:10.1002/eco.2494
• Leeuwen, W. J., Conley, C., Norton, C. L., Gillan, J. K., & Hartfield, K. (2022). A Novel Spectral Index to Identify Cacti in the Sonoran Desert at Multiple Scales Using Multi-Sensor Hyperspectral Data Acquisitions. Land. doi:10.3390/land11060786
• Leeuwen, W. J., Hartfield, K. A., Crimmins, M. A., Leeuwen, W. J., Khatri-chhetri, P., Kane, V. R., Hendryx, S. M., Hartfield, K. A., & Crimmins, M. A. (2021). Assessing vegetation response to multi-scalar drought across the mojave, sonoran, chihuahuan deserts and apache highlands in the Southwest United States. Remote Sensing, 13(6). doi:10.3390/rs13061103
• Broxton, P. D., & van Leeuwen, W. (2020). Structure from Motion of Multi-Angle RPAS Imagery Complements Larger-Scale Airborne Lidar Data for Cost-Effective Snow Monitoring in Mountain Forests. Remote Sensing, 12(14).
• Broxton, P. D., Biederman, J. A., & Leeuwen, W. J. (2020). Forest cover and topography regulate the thin, ephemeral snowpacks of the semiarid Southwest United States. Ecohydrology, 13(4). doi:10.1002/eco.2202
• Broxton, P. D., van, L., & Biederman, J. A. (2020). Forest cover and topography regulate the thin, ephemeral snowpacks of the semiarid Southwest United States. Ecohydrology, 13(4), e2202.
• Cornejo-Denman, L., Romo-Leon, J. R., Hartfield, K., van Leeuwen, W. J., Ponce-Campos, G. E., & Castellanos-Villegas, A. (2020). Landscape Dynamics in an Iconic Watershed of Northwestern Mexico: Vegetation Condition Insights Using Landsat and PlanetScope Data. Remote Sensing, 12(16).
• Gillan, J. K., Karl, J. W., & van Leeuwen, W. J. (2020). Integrating drone imagery with existing rangeland monitoring programs. Environmental monitoring and assessment, 192(5), 269.
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  The recent availability of small and low-cost sensor carrying unmanned aerial systems (UAS, commonly known as drones) coupled with advances in image processing software (i.e., structure from motion photogrammetry) has made drone-collected imagery a potentially valuable tool for rangeland inventory and monitoring. Drone-imagery methods can observe larger extents to estimate indicators at landscape scales with higher confidence than traditional field sampling. They also have the potential to replace field methods in some instances and enable the development of indicators not measurable from the ground. Much research has already demonstrated that several quantitative rangeland indicators can be estimated from high-resolution imagery. Developing a suite of monitoring methods that are useful for supporting management decisions (e.g., repeatable, cost-effective, and validated against field methods) will require additional exploration to develop best practices for image acquisition and analytical workflows that can efficiently estimate multiple indicators. We embedded with a Bureau of Land Management (BLM) field monitoring crew in Northern California, USA to compare field-measured and imagery-derived indicator values and to evaluate the logistics of using small UAS within the framework of an existing monitoring program. The unified workflow we developed to measure fractional cover, canopy gaps, and vegetation height was specific for the sagebrush steppe, an ecosystem that is common in other BLM managed lands. The correspondence between imagery and field methods yielded encouraging agreement while revealing systematic differences between the methods. Workflow best practices for producing repeatable rangeland indicators is likely to vary by vegetation composition and phenology. An online space dedicated to sharing imagery-based workflows could spur collaboration among researchers and quicken the pace of integrating drone-imagery data within adaptive management of rangelands. Though drone-imagery methods are not likely to replace most field methods in large monitoring programs, they could be a valuable enhancement for pressing local management needs.
• Hartfield, K. A., Van Leeuwen, W. J., & Gillan, J. K. (2020). Remotely Sensed Changes in Vegetation Cover Distribution and Groundwater along the Lower Gila River. Land, 9(9), 18. doi:https://doi.org/10.3390/land9090326
• Hartfield, K., Castellanos, A. E., Ponce-Campos, G. E., Leeuwen, W. J., Romo-Leon, J. R., & Cornejo-Denman, L. (2020). Landscape Dynamics in an Iconic Watershed of Northwestern Mexico: Vegetation Condition Insights Using Landsat and PlanetScope Data. Remote Sensing. doi:10.3390/rs12162519
• Hartfield, K., Gillan, J. K., & Leeuwen, W. J. (2020). Remotely Sensed Changes in Vegetation Cover Distribution and Groundwater along the Lower Gila River. Land. doi:10.3390/land9090326
• Hartfield, K., van Leeuwen, W., & Gillan, J. K. (2020). Remotely Sensed Changes in Vegetation Cover Distribution and Groundwater along the Lower Gila River. Land, 9(9).
• Leeuwen, W. J., Karl, J. W., & Gillan, J. K. (2020). Integrating drone imagery with existing rangeland monitoring programs. Environmental Monitoring and Assessment. doi:10.1007/s10661-020-8216-3
• Smith, W. K., Wang, X., Dannenberg, M. P., Yan, D., Jones, M. O., Kimball, J. S., Moore, D. J., Leeuwen, W. J., & Didan, K. (2020). Globally Consistent Patterns of Asynchrony in Vegetation Phenology Derived From Optical, Microwave, and Fluorescence Satellite Data. Journal of Geophysical Research: Biogeosciences, 125(7). doi:10.1029/2020jg005732
• Wang, X., Dannenberg, M. P., Yan, D., Jones, M. O., Kimball, J. S., Moore, D., van Leeuwen, W., Didan, K., & Smith, W. K. (2020). Globally Consistent Patterns of Asynchrony in Vegetation Phenology Derived From Optical, Microwave, and Fluorescence Satellite Data. Journal of Geophysical Research: Biogeosciences, 125(7), e2020JG005732.
• Broxton, P. D., Leeuwen, W. J., & Biederman, J. A. (2019). Improving Snow Water Equivalent Maps With Machine Learning of Snow Survey and Lidar Measurements. Water Resources Research, 55(5), 3739-3757. doi:10.1029/2018wr024146
• Broxton, P. D., van Leeuwen, W. J., & Biederman, J. A. (2019). Improving Snow Water Equivalent Maps With Machine Learning of Snow Survey and Lidar Measurements. WATER RESOURCES RESEARCH, 55(5), 3739-3757.
• Kautz, M. A., Collins, C., Guertin, D. P., Goodrich, D. C., van Leeuwen, W. J., & Williams, J. (2019). Hydrologic model parameterization using dynamic Landsat-based vegetative estimates within a semiarid grassland. JOURNAL OF HYDROLOGY, 575, 1073-1086.
• Williams, C. J., Leeuwen, W. J., Goodrich, D. C., Guertin, D. P., Collins, C. H., & Kautz, M. A. (2019). Hydrologic model parameterization using dynamic Landsat-based vegetative estimates within a semiarid grassland. Journal of Hydrology. doi:10.1016/j.jhydrol.2019.05.044
• Archer, S. R., Wilcox, B. P., Birt, A., Fuhlendorf, S. D., Kreuter, U. P., Sorice, M. G., van Leeuwen, W. J., & Zou, C. B. (2018). Viewing Woody-Plant Encroachment through a Social–Ecological Lens. BioScience, 68(9), 691-705. doi:10.1093/biosci/biy051
• Carter, F., & van Leeuwen, W. J. (2018). Mapping saguaro cacti using digital aerial imagery in Saguaro National Park. Journal of Applied Remote Sensing, 12(03), 1. doi:10.1117/1.jrs.12.036016
• Forest, C. (2018). Mapping saguaro cacti using digital aerial imagery in Saguaro National Park. Journal of Applied Remote Sensing, 12, 12 - 12 - 14.
• Hartfield, K. A., & Van Leeuwen, W. J. (2018). Woody Cover Estimates in Oklahoma and Texas Using a Multi-Sensor Calibration and Validation Approach. Remote Sensing, 10(4), 19. doi:10.3390/rs10040632
• Leeuwen, W. J., Crimmins, M. A., Munoz, A. B., Marsh, S. E., Leeuwen, W. J., El-vilaly, M. A., Didan, K., & Crimmins, M. A. (2018). Vegetation productivity responses to drought on tribal lands in the four corners region of the Southwest USA. Frontiers in Earth Science, 12(1), 37-51. doi:10.1007/s11707-017-0646-z
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  For more than a decade, the Four Corners Region has faced extensive and persistent drought conditions that have impacted vegetation communities and local water resources while exacerbating soil erosion. These persistent droughts threaten ecosystem services, agriculture, and livestock activities, and expose the hypersensitivity of this region to inter-annual climate variability and change. Much of the intermountainWestern United States has sparse climate and vegetation monitoring stations, making fine-scale drought assessments difficult. Remote sensing data offers the opportunity to assess the impacts of the recent droughts on vegetation productivity across these areas. Here, we propose a drought assessment approach that integrates climate and topographical data with remote sensing vegetation index time series. Multisensor Normalized Difference Vegetation Index (NDVI) time series data from 1989 to 2010 at 5.6 km were analyzed to characterize the vegetation productivity changes and responses to the ongoing drought. A multi-linear regression was applied to metrics of vegetation productivity derived from the NDVI time series to detect vegetation productivity, an ecosystem service proxy, and changes. The results show that around 60.13% of the study area is observing a general decline of greenness (p
• Barnes, M. L., Breshears, D. D., Law, D. J., van Leeuwen, W. J., Monson, R. K., Fojtik, A. C., Barron-Gafford, G. A., & Moore, D. J. (2017). Beyond greenness: Detecting temporal changes in photosynthetic capacity with hyperspectral reflectance data. PloS one, 12(12), e0189539.
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  Earth's future carbon balance and regional carbon exchange dynamics are inextricably linked to plant photosynthesis. Spectral vegetation indices are widely used as proxies for vegetation greenness and to estimate state variables such as vegetation cover and leaf area index. However, the capacity of green leaves to take up carbon can change throughout the season. We quantify photosynthetic capacity as the maximum rate of RuBP carboxylation (Vcmax) and regeneration (Jmax). Vcmax and Jmax vary within-season due to interactions between ontogenetic processes and meteorological variables. Remote sensing-based estimation of Vcmax and Jmax using leaf reflectance spectra is promising, but temporal variation in relationships between these key determinants of photosynthetic capacity, leaf reflectance spectra, and the models that link these variables has not been evaluated. To address this issue, we studied hybrid poplar (Populus spp.) during a 7-week mid-summer period to quantify seasonally-dynamic relationships between Vcmax, Jmax, and leaf spectra. We compared in situ estimates of Vcmax and Jmax from gas exchange measurements to estimates of Vcmax and Jmax derived from partial least squares regression (PLSR) and fresh-leaf reflectance spectroscopy. PLSR models were robust despite dynamic temporal variation in Vcmax and Jmax throughout the study period. Within-population variation in plant stress modestly reduced PLSR model predictive capacity. Hyperspectral vegetation indices were well-correlated to Vcmax and Jmax, including the widely-used Normalized Difference Vegetation Index. Our results show that hyperspectral estimation of plant physiological traits using PLSR may be robust to temporal variation. Additionally, hyperspectral vegetation indices may be sufficient to detect temporal changes in photosynthetic capacity in contexts similar to those studied here. Overall, our results highlight the potential for hyperspectral remote sensing to estimate determinants of photosynthetic capacity during periods with dynamic temporal variations related to seasonality and plant stress, thereby improving estimates of plant productivity and characterization of the associated carbon budget.
• Barreto, A., Barreto, A., Crimmins, M. A., Crimmins, M. A., Van Leeuwen, W. J., Van Leeuwen, W. J., Marsh, S. E., Marsh, S. E., Didan, K., Didan, K., El Vilaly, M. A., & El Vilaly, M. A. (2017). Vegetation Productivity Responses to Drought on Tribal Lands in the Four Corners Region of the Southwest U.S.. Frontiers of Earth Science. doi:https://doi.org/10.1007/s11707-017-0646-z
• Law, D. J., Barron-Gafford, G. A., Moore, D. J., Fojtik, A. C., Monson, R. K., Leeuwen, W. J., Breshears, D. D., & Barnes, M. (2017). Beyond greenness: Detecting temporal changes in photosynthetic capacity with hyperspectral reflectance data. PLOS ONE. doi:10.1371/journal.pone.0189539
• Petrakis, R., Van, L. W., Villarreal, M., Tashjian, P., Dello, R. R., & A., S. C. (2017). Historical Analysis of Riparian Vegetation Change in Response to Shifting Management Objectives on the Middle Rio Grande. Land, 6(2). doi:DOI: 10.3390/land6020029
• Prohaska, N., Albert, L. P., Saleska, S. R., Oliviera, R. C., Malhi, Y., Martins, G., Garnello, A., Leeuwen, W. J., Yang, X., Guan, K., Serbin, S. P., Chavana-Bryant, C., & Wu, J. (2017). Convergence in relationships between leaf traits, spectra and age across diverse canopy environments and two contrasting tropical forests. New Phytologist, 214(3), 1033-1048. doi:10.1111/nph.14051
• Wu, J., Chavana-Bryant, C., Prohaska, N., Serbin, S. P., Guan, K., Albert, L. P., Yang, X., van Leeuwen, W. J., Garnello, A. J., Martins, G., Malhi, Y., Gerard, F., Oliviera, R. C., & Saleska, S. R. (2017). Convergence in relationships between leaf traits, spectra and age across diverse canopy environments and two contrasting tropical forests. The New phytologist, 214(3), 1033-1048.
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  Leaf age structures the phenology and development of plants, as well as the evolution of leaf traits over life histories. However, a general method for efficiently estimating leaf age across forests and canopy environments is lacking. Here, we explored the potential for a statistical model, previously developed for Peruvian sunlit leaves, to consistently predict leaf ages from leaf reflectance spectra across two contrasting forests in Peru and Brazil and across diverse canopy environments. The model performed well for independent Brazilian sunlit and shade canopy leaves (R2  = 0.75-0.78), suggesting that canopy leaves (and their associated spectra) follow constrained developmental trajectories even in contrasting forests. The model did not perform as well for mid-canopy and understory leaves (R2  = 0.27-0.29), because leaves in different environments have distinct traits and trait developmental trajectories. When we accounted for distinct environment-trait linkages - either by explicitly including traits and environments in the model, or, even better, by re-parameterizing the spectra-only model to implicitly capture distinct trait-trajectories in different environments - we achieved a more general model that well-predicted leaf age across forests and environments (R2  = 0.79). Fundamental rules, linked to leaf environments, constrain the development of leaf traits and allow for general prediction of leaf age from spectra across species, sites and canopy environments.
• Falk, D. A., McEwen, A. S., Van Leeuwen, W. J., Van Leeuwen, W. J., McEwen, A. S., & Falk, D. A. (2016). Low-cost high-resolution global pyrogenic thermal sensing: Critical information for biosphere-atmosphere interactions. Decadal Survey for Earth Science and Applications from Space, National Academy of Science, ESAS 2017.
• Glade, F. E., Miranda, M. D., Meza, F. J., & van Leeuwen, W. J. (2016). Productivity and phenological responses of natural vegetation to present and future inter-annual climate variability across semi-arid river basins in Chile. Environmental monitoring and assessment, 188(12), 676.
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  Time series of vegetation indices and remotely sensed phenological data offer insights about the patterns in vegetation dynamics. Both are useful sources of information for analyzing and monitoring ecosystem responses to environmental variations caused by natural and anthropogenic drivers. In the semi-arid region of Chile, climate variability and recent severe droughts in addition to land-use changes pose threats to the stability of local ecosystems. Normalized difference vegetation index time series (2000-2013) data from the moderate resolution imaging spectroradiometer (MODIS) was processed to monitor the trends and patterns of vegetation productivity and phenology observed over the last decade. An analysis of the relationship between (i) vegetation productivity and (ii) precipitation and temperature data for representative natural land-use cover classes was made. Using these data and ground measurements, productivity estimates were projected for two climate change scenarios (RCP2.6 and RCP8.5) at two altitudinal levels. Results showed negative trends of vegetation productivity below 2000 m a.s.l. and positive trends for higher elevations. Phenology analysis suggested that mountainous ecosystems were starting their growing period earlier in the season, coinciding with a decreased productivity peak during the growing season. The coastal shrubland/grassland land cover class had a significant positive relation with rainfall and a significant negative relation with temperature, suggesting that these ecosystems are vulnerable to climate change. Future productivity projections indicate that under an RCP8.5 climate change scenario, productivity could decline by 12% in the period of 2060-2100, leading to a severe vegetation degradation at lower altitudes and in drier areas.
• Leeuwen, W. J., Meza, F., Miranda, M., & Glade, F. E. (2016). Productivity and phenological responses of natural vegetation to present and future inter-annual climate variability across semi-arid river basins in Chile. Environmental Monitoring and Assessment. doi:10.1007/s10661-016-5675-7
• Romo-Leon, J. R., van Leeuwen, W. J., & Castellanos-Villegas, A. (2016). Land Use and Environmental Variability Impacts on the Phenology of Arid Agro-Ecosystems. Environmental management, 57(2), 283-97.
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  The overexploitation of water resources in arid environments often results in abandonment of large extensions of agricultural lands, which may (1) modify phenological trends, and (2) alter the sensitivity of specific phenophases to environmental triggers. In Mexico, current governmental policies subsidize restoration efforts, to address ecological degradation caused by abandonments; however, there is a need for new approaches to assess their effectiveness. Addressing this, we explore a method to monitor and assess (1) land surface phenology trends in arid agro-ecosystems, and (2) the effect of climatic factors and restoration treatments on the phenology of abandoned agricultural fields. We used 16-day normalized difference vegetation index composites from the moderate resolution imaging spectroradiometer from 2000 to 2009 to derive seasonal phenometrics. We then derived phenoclimatic variables and land cover thematic maps, to serve as a set of independent factors that influence vegetation phenology. We conducted a multivariate analysis of variance to analyze phenological trends among land cover types, and developed multiple linear regression models to assess influential climatic factors driving phenology per land cover analyzed. Our results suggest that the start and length of the growing season had different responses to environmental factors depending on land cover type. Our analysis also suggests possible establishment of arid adapted species (from surrounding ecosystems) in abandoned fields with longer times since abandonment. Using this approach, we were able increase our understanding on how climatic factors influence phenology on degraded arid agro-ecosystems, and how this systems evolve after disturbance.
• Wu, J., Chavana-Bryant, C., Prohaska, N., Serbin, S. P., Guan, K., Albert, L. P., Yang, X., Van Leeuwen, W. J., Garnello, A. J., Martins, G., Malhi, Y., Gerard, F., Oliviera, R. c., & Saleska, S. R. (2016). Convergence in relations among leaf traits, spectra and age across diverse canopy environments and two contrasting tropical forests. New Phytologist. doi:10.1111/nph.14051
• Xu, C., W, Z., J, H., & Van Leeuwen, W. J. (2016). Prediction of Soil Moisture Content and Soil Salt Concentration from Hyperspectral Laboratory and Field Data. Remote Sensing, 8(42).
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  Xu, C., Zeng, W., Huang, J., Wu, J. and Willem J.D.van Leeuwen, 2016. Prediction of Soil Moisture Content and Soil Salt Concentration from Hyperspectral Laboratory and Field Data. Remote Sensing 8: 42.
• Crimmins, M. A., Rasmussen, C., Leeuwen, W. J., Schaap, M. G., & Shepard, C. (2015). Subsurface soil textural control of aboveground productivity in the US Desert Southwest. Geoderma Regional. doi:10.1016/j.geodrs.2014.12.003
• Flesch, A. D., Hutto, R. L., van Leeuwen, W. J., Hartfield, K., & Jacobs, S. (2015). Correction: Spatial, Temporal, and Density-Dependent Components of Habitat Quality for a Desert Owl. PloS one, 10(10), e0141178.
• Flesch, A. D., Hutto, R. L., van Leeuwen, W. J., Hartfield, K., & Jacobs, S. (2015). Spatial, Temporal, and Density-dependent Components of Ferruginous Pygmy-Owls Habitat Quality. PLOS, 10(e0119986).
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  Spatial, Temporal, and Density-Dependent Components of Habitat Quality for a Desert OwlAARON D. FLESCH RICHARD L. HUTTO WILLEM VAN LEEUWEN AND KYLE HARTFIELD, SKY L. JACOBS
• Flesch, A. D., Hutto, R. L., van Leeuwen, W. J., Hartfield, K., & Jacobs, S. (2015). Spatial, temporal, and density-dependent components of habitat quality for a desert owl. PloS one, 10(3), e0119986.
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  Spatial variation in resources is a fundamental driver of habitat quality but the realized value of resources at any point in space may depend on the effects of conspecifics and stochastic factors, such as weather, which vary through time. We evaluated the relative and combined effects of habitat resources, weather, and conspecifics on habitat quality for ferruginous pygmy-owls (Glaucidium brasilianum) in the Sonoran Desert of northwest Mexico by monitoring reproductive output and conspecific abundance over 10 years in and around 107 territory patches. Variation in reproductive output was much greater across space than time, and although habitat resources explained a much greater proportion of that variation (0.70) than weather (0.17) or conspecifics (0.13), evidence for interactions among each of these components of the environment was strong. Relative to habitat that was persistently low in quality, high-quality habitat buffered the negative effects of conspecifics and amplified the benefits of favorable weather, but did not buffer the disadvantages of harsh weather. Moreover, the positive effects of favorable weather at low conspecific densities were offset by intraspecific competition at high densities. Although realized habitat quality declined with increasing conspecific density suggesting interference mechanisms associated with an Ideal Free Distribution, broad spatial heterogeneity in habitat quality persisted. Factors linked to food resources had positive effects on reproductive output but only where nest cavities were sufficiently abundant to mitigate the negative effects of heterospecific enemies. Annual precipitation and brooding-season temperature had strong multiplicative effects on reproductive output, which declined at increasing rates as drought and temperature increased, reflecting conditions predicted to become more frequent with climate change. Because the collective environment influences habitat quality in complex ways, integrated approaches that consider habitat resources, stochastic factors, and conspecifics are necessary to accurately assess habitat quality.
• Hartfield, K., Jacobs, S., Leeuwen, W. J., Hutto, R. L., & Flesch, A. D. (2015). Correction: Spatial, Temporal, and Density-Dependent Components of Habitat Quality for a Desert Owl. PLOS ONE. doi:10.1371/journal.pone.0141178
• Romo-Leon, R. J., Van Leeuwen, W. J., & Castellanos-Villegas, A. (2015). Land Use and Environmental Variability Impacts on the Phenology of Arid Agro-Ecosystems. Environmental management, 1-15.
• Shepard, C., Schaap, M. G., Crimmins, M. A., van Leeuwen, W. J., & Rasmussen, C. (2015). Subsurface soil textural control of aboveground productivity in the US Desert Southwest. Geoderma Regional, 4(0), 44-54.
• Wisniewski, W. T., Marsh, S. E., Hirschboeck, K. K., Leeuwen, W. J., & Czyzowska-Wisniewski, E. H. (2015). Fractional snow cover estimation in complex alpine-forested environments using an artificial neural network. Remote Sensing of Environment. doi:10.1016/j.rse.2014.09.026
• Czyzowska-Wisniewski, E. H., van Leeuwen, W. J., Hirschboeck, K. K., Marsh, S. E., & Wisniewski, W. T. (2015). Fractional snow cover estimation in complex alpine-forested environments using an artificial neural network. Remote Sensing of Environment, 156(0), 403-417.
• Hartfield, K., Szutu, D., Leeuwen, W. J., Swetish, J. B., Papuga, S. A., & Sanchez-Mejia, Z. M. (2014). Quantifying the influence of deep soil moisture on ecosystem albedo: The role of vegetation. Water Resources Research, 50(5), 4038-4053. doi:10.1002/2013wr014150
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  As changes in precipitation dynamics continue to alter the water availability in dryland ecosystems, understanding the feedbacks between the vegetation and the hydrologic cycle and their influence on the climate system is critically important. We designed a field campaign to examine the influence of two-layer soil moisture control on bare and canopy albedo dynamics in a semiarid shrubland ecosystem. We conducted this campaign during 2011 and 2012 within the tower footprint of the Santa Rita Creosote Ameriflux site. Albedo field measurements fell into one of four Cases within a two-layer soil moisture framework based on permutations of whether the shallow and deep soil layers were wet or dry. Using these Cases, we identified differences in how shallow and deep soil moisture influence canopy and bare albedo. Then, by varying the number of canopy and bare patches within a gridded framework, we explore the influence of vegetation and soil moisture on ecosystem albedo. Our results highlight the importance of deep soil moisture in land surface-atmosphere interactions through its influence on aboveground vegetation characteristics. For instance, we show how green-up of the vegetation is triggered by deep soil moisture, and link deep soil moisture to a decrease in canopy albedo. Understanding relationships between vegetation and deep soil moisture will provide important insights into feedbacks between the hydrologic cycle and the climate system.
• Romo-Leon, J. R., van Leeuwen, W. J., & Castellanos-Villegas, A. (2014). Using remote sensing tools to assess land use transitions in unsustainable arid agro-ecosystems. Journal of Arid Environments, 106, 27-35.
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  Abstract: This research investigates the human impact on land-cover dynamics in arid agro-ecosystems. Our study area was La Costa de Hermosillo (northwestern Mexico), where the unregulated use of water resources has resulted in the abandonment of irrigated agricultural fields and a shift to new economic activities. Using remote sensing and ancillary datasets combined with classification and regression tree (CART) models, we mapped land-cover class distributions over 22 years (1988-2009) to characterize agricultural changes following management decisions. Our land-cover classification maps had an overall accuracy of over 80%. Using these maps, we were able to show the decrease in agriculture from approximately 115,066 to 66,044ha between 1988 and 2009 and the conversion to alternative economic activities, with aquaculture increasing from 0 to 10,083ha during the same period. Our analyses also show the temporal-spatial dynamics of land-use management practices, which suggest that implementation of the remote sensing methods developed in this manuscript may contribute to bridging the gap of knowledge between ecological effects and unsustainable management practices and decrease the time required to inform and make policy decisions in arid agro-ecosystems. © 2014 Elsevier Ltd.
• Sanchez-Mejia, Z. M., Papuga, S. A., Swetish, J. B., Leeuwen, W. J., Szutu, D., & Hartfield, K. (2014). Quantifying the influence of deep soil moisture on ecosystem albedo: The role of vegetation. Water Resources Research, 50(5), 4038--4053.
• Sanchez-Mejia, Z. M., Papuga, S. A., Swetish, J., van Leeuwen, W. J., Szutu, D., & Hartfield, K. (2014). Quantifying the influence of deep soil moisture on ecosystem albedo: the role of vegetation. Water Resources Research.
• Casady, G. M., J.D., W., & Reed, B. C. (2013). Estimating winter annual biomass in the sonoran and mojave deserts with satellite- and ground-based observations. Remote Sensing, 5(2), 909-926.
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  Abstract: Winter annual plants in southwestern North America influence fire regimes, provide forage, and help prevent erosion. Exotic annuals may also threaten native species. Monitoring winter annuals is difficult because of their ephemeral nature, making the development of a satellite monitoring tool valuable. We mapped winter annual aboveground biomass in the Desert Southwest from satellite observations, evaluating 18 algorithms using time-series vegetation indices (VI). Field-based biomass estimates were used to calibrate and evaluate each algorithm. Winter annual biomass was best estimated by calculating a base VI across the period of record and subtracting it from the peak VI for each winter season (R2 = 0.92). The normalized difference vegetation index (NDVI) derived from 8-day reflectance data provided the best estimate of winter annual biomass. It is important to account for the timing of peak vegetation when relating field-based estimates to satellite VI data, since post-peak field estimates may indicate senescent biomass which is inaccurately represented by VI-based estimates. Images generated from the best-performing algorithm show both spatial and temporal variation in winter annual biomass. Efforts to manage this variable resource would be enhanced by a tool that allows the monitoring of changes in winter annual resources over time. © 2013 by the authors.
• Casady, G. M., van Leeuwen, W. J., & Reed, B. C. (2013). Winter Annual Biomass in the Sonoran and Mojave Deserts with Satellite- and Ground-Based Observations. Remote Sensing, 5(2), 909-926.
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  Casady, Grant M., van Leeuwen, Willem J.D., Reed, Bradley C. 2013. Winter Annual Biomass in the Sonoran and Mojave Deserts with Satellite- and Ground-Based Observations. Remote Sens. 5, no. 2: 909-926
• Reed, B. C., Leeuwen, W. J., & Casady, G. M. (2013). Estimating Winter Annual Biomass in the Sonoran and Mojave Deserts with Satellite- and Ground-Based Observations. Remote Sensing. doi:10.3390/rs5020909
• van, L., Hartfield, K., Miranda, M., & Meza, F. J. (2013). Trends and ENSO/AAO Driven Variability in NDVI Derived Productivity and Phenology alongside the Andes Mountains. REMOTE SENSING, 5(3), 1177-1203.
• Kariyeva, J., & J.D., W. (2012). Phenological dynamics of irrigated and natural drylands in Central Asia before and after the USSR collapse. Agriculture, Ecosystems and Environment, 162, 77-89.
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  Abstract: Central Asia has experienced drastic socio-economic, geopolitical, and ecological transitions within the last few decades. The USSR collapse in 1991 has led to widespread changes in land cover and land use due to economic and political transformations within the region. Management practices during and after the Soviet era have intensified ecological problems and demands on resources. Satellite derived vegetation greenness data offer insights into these dynamics by providing measurements linked to vegetation productivity and the timing of vegetation growth cycles, including the timing of greenness onset, peak, and senescence. The main research goals are to examine the impact of socio-economic and bioclimatic factors by characterizing interannual dynamics of regional land surface phenology. One of the longest available records (1981-2006) of geospatial time-series data of the biweekly Normalized Difference Vegetation Index (NDVI) were used to derive annual pheno-metrics for sites in Uzbekistan and Turkmenistan. Land cover types include irrigated agriculture, riparian zones, and arid desert regions. Statistical analysis showed significant differences between pre- and post-Soviet collapse seasonal NDVI trajectories and interannual variation in greenness onset and vegetation response. Changes in satellite-based land surface phenological information are attributed to differences in prevailing land management, climate, and socio-economic factors before and after the USSR collapse. © 2012.
• Kariyeva, J., J., W., & Woodhouse, C. A. (2012). Impacts of climate gradients on the vegetation phenology of major land use types in Central Asia (1981-2008). Frontiers of Earth Science, 6(2), 206-225.
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  Abstract: Time-series of land surface phenology (LSP) data offer insights about vegetation growth patterns. They can be generated by exploiting the temporal and spectral reflectance properties of land surface components. Interannual and seasonal LSP data are important for understanding and predicting an ecosystem's response to variations caused by natural and anthropogenic drivers. This research examines spatio-temporal change patterns and interactions between terrestrial phenology and 28 years of climate dynamics in Central Asia. Long-term (1981-2008) LSP records such as timing of the start, peak and length of the growing season and vegetation productivity were derived from remotely sensed vegetation greenness data. The patterns were analyzed to identify and characterize the impact of climate drivers at regional scales. We explored the relationships between phenological and precipitation and temperature variables for three generalized land use types that were exposed to decadelong regional drought events and intensified land and water resource use: rainfed agriculture, irrigated agriculture, and non-agriculture. To determine whether and how LSP dynamics are associated with climate patterns, a series of simple linear regression analyses between these two variables was executed. The three land use classes showed unique phenological responses to climate variation across Central Asia. Most of the phenological response variables were shown to be positively correlated to precipitation and negatively correlated to temperature. The most substantial climate variable affecting phenological responses of all three land use classes was a spring temperature regime. These results indicate that future higher temperatures would cause earlier and longer growing seasons. © 2012 Higher Education Press and Springer-Verlag Berlin Heidelberg.
• Kariyeva, J., van, L., & Woodhouse, C. A. (2012). Impacts of climate gradients on the vegetation phenology of major land use types in Central Asia (1981-2008). FRONTIERS OF EARTH SCIENCE, 6(2), 206-225.
• Landau, K. I., & van Leeuwen, W. J. (2012). Fine scale spatial urban land cover factors associated with adult mosquito abundance and risk in Tucson, Arizona. Journal of vector ecology : journal of the Society for Vector Ecology, 37(2), 407-18.
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  It is currently unclear what role microhabitat land cover plays in determining the seasonal spatial distribution of Aedes aegypti and Culex quinquefasciatus, disease vectors of dengue and West Nile Virus, respectively, in Tucson, AZ. We compared mosquito abundance to sixteen land cover variables derived from 2010 NAIP multispectral data and 2008 LiDAR height data. Mosquitoes were trapped with 30-9 traps from May to October of 2010 and 2011. Variables were extracted for five buffer zones (10-50 m radii at 10 m intervals) around trapping sites. Stepwise regression was performed to determine the best scale for observation and the influential land cover variables. The 30 m radius buffer was determined to be the best for observing the land cover-mosquito abundance relationship. Ae. aegypti presence was positively associated with structure and medium height trees and negatively associated with bare earth; Cx. quinquefasciatus presence was positively associated with pavement and medium height trees and negatively associated with shrubs. These findings emphasize vegetation, impervious surfaces, and soil influences on mosquito presence in an urban setting. Lastly, the land cover-mosquito abundance relationships were used to produce risk maps of seasonal presence that highlight high risk areas in Tucson, which may be useful for focusing mosquito control program actions.
• Leeuwen, W. J., & Kariyeva, J. (2012). Phenological dynamics of irrigated and natural drylands in Central Asia before and after the USSR collapse. Agriculture, Ecosystems & Environment. doi:10.1016/j.agee.2012.08.006
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  ► Institutional and land use changes can be detected with satellite time series data. ► Variation in vegetation phenology was significant with institutional regime change. ► Change in land surface phenology revealed differences in crop cultivation practices. ► ENSO phases and annual vegetation productivity show correspondence in case studies. ► Vegetation index values increases/decreases with warm/cold ENSO phases respectively. Central Asia has experienced drastic socio-economic, geopolitical, and ecological transitions within the last few decades. The USSR collapse in 1991 has led to widespread changes in land cover and land use due to economic and political transformations within the region. Management practices during and after the Soviet era have intensified ecological problems and demands on resources. Satellite derived vegetation greenness data offer insights into these dynamics by providing measurements linked to vegetation productivity and the timing of vegetation growth cycles, including the timing of greenness onset, peak, and senescence. The main research goals are to examine the impact of socio-economic and bioclimatic factors by characterizing interannual dynamics of regional land surface phenology. One of the longest available records (1981–2006) of geospatial time-series data of the biweekly Normalized Difference Vegetation Index (NDVI) were used to derive annual pheno-metrics for sites in Uzbekistan and Turkmenistan. Land cover types include irrigated agriculture, riparian zones, and arid desert regions. Statistical analysis showed significant differences between pre- and post-Soviet collapse seasonal NDVI trajectories and interannual variation in greenness onset and vegetation response. Changes in satellite-based land surface phenological information are attributed to differences in prevailing land management, climate, and socio-economic factors before and after the USSR collapse.
• Leeuwen, W. J., & Landau, K. I. (2012). Fine scale spatial urban land cover factors associated with adult mosquito abundance and risk in Tucson, Arizona. Journal of Vector Ecology. doi:10.1111/j.1948-7134.2012.00245.x
• Raul, J., J.D., W., & Casady, G. M. (2012). Using MODIS-NDVI for the modeling of post-wildfire vegetation response as a function of environmental conditions and pre-fire restoration treatments. Remote Sensing, 4(3), 598-621.
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  Abstract: Post-fire vegetation response is influenced by the interaction of natural and anthropogenic factors such as topography, climate, vegetation type and restoration practices. Previous research has analyzed the relationship of some of these factors to vegetation response, but few have taken into account the effects of pre-fire restoration practices. We selected three wildfires that occurred in Bandelier National Monument (New Mexico, USA) between 1999 and 2007 and three adjacent unburned control areas. We used interannual trends in the Normalized Difference Vegetation Index (NDVI) time series data derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) to assess vegetation response, which we define as the average potential photosynthetic activity through the summer monsoon. Topography, fire severity and restoration treatment were obtained and used to explain post-fire vegetation response. We applied parametric (Multiple Linear Regressions-MLR) and non-parametric tests (Classification and Regression Trees-CART) to analyze effects of fire severity, terrain and pre-fire restoration treatments (variable used in CART) on post-fire vegetation response. MLR results showed strong relationships between vegetation response and environmental factors (p < 0.1), however the explanatory factors changed among treatments. CART results showed that beside fire severity and topography, pre-fire treatments strongly impact post-fire vegetation response. Results for these three fires show that pre-fire restoration conditions along with local environmental factors constitute key processes that modify post-fire vegetation response. © 2012 by the authors.
• Romo-Leon, J. R., Leeuwen, W. J., & Villarreal, M. L. (2012). Mapping and monitoring riparian vegetation distribution, structure and composition with regression tree models and post-classification change metrics. International Journal of Remote Sensing, 33(13), 4266-4290. doi:10.1080/01431161.2011.644594
• Villarreal, M. L., J., W., & Romo-Leon, J. R. (2012). Mapping and monitoring riparian vegetation distribution, structure and composition with regression tree models and post-classification change metrics. International Journal of Remote Sensing, 33(13), 4266-4290.
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  Abstract: Riparian systems have become increasingly susceptible to both natural and human disturbances as cumulative pressures from changing land use and climate alter the hydrological regimes. This article introduces a landscape dynamics monitoring protocol that incorporates riparian structural classes into the land-cover classification scheme and examines riparian change within the context of surrounding land-cover change. We tested whether Landsat Thematic Mapper (TM) imagery could be used to document a riparian tree die-off through the classification of multi-date Landsat images using classification and regression tree (CART) models trained with physiognomic vegetation data. We developed a post-classification change map and used patch metrics to examine the magnitude and trajectories of riparian class change relative to mapped disturbance parameters. Results show that catchments where riparian change occurred can be identified from land-cover change maps; however, the main change resulting from the die-off disturbance was compositional rather than structural, making accurate post-classification change detection difficult. © 2012 Copyright Taylor and Francis Group, LLC.
• Villarreal, M. L., van Leeuwen, W. J., & Romo Leon, R. J. (2012). Mapping and monitoring riparian vegetation distribution, structure and composition with regression tree models and post-classification change metrics. International Journal of Remote Sensing.
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  ;Your Role: Led the implementation of Classification and Regression Tree (CART) Vegetation type classification protocol;Full Citation: Villarreal, M.L., Willem J.D. van Leeuwen, Jose Raul Romo-Leon. 2012. Mapping and monitoring riparian vegetation distribution, structure and composition with regression tree models and post-classification change metrics, International Journal of Remote Sensing, 33:13, 4266-4290. NA. (20%).;Collaborative with graduate student: Yes;
• Woodhouse, C. A., Leeuwen, W. J., & Kariyeva, J. (2012). Impacts of climate gradients on the vegetation phenology of major land use types in Central Asia (1981–2008). Frontiers of Earth Science. doi:10.1007/s11707-012-0315-1
• van Leeuwen, W. J., Davison, J. E., Casady, G. M., & Marsh, S. E. (2012). Phenological Characterization of Desert Sky Island Vegetation Communities with Remotely Sensed and Climate Time Series Data. REMOTE SENSING, 2(2), 388-415.
• van Leeuwen, W. J., Kariyeva, J., & Willem, J. (2012). Impacts of climate gradients on the vegetation phenology of major land use types in Central Asia (1981-2008). Frontiers of Earth Science.
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  ;Your Role: Data interpretation and Research design;Full Citation: Kariyeva, J., Willem J. D. van Leeuwen, C. A. Woodhouse, 2012. Impacts of climate gradients on the vegetation phenology of major land use types in Central Asia (1981-2008) Frontiers of Earth Science, 6(2):206-225.;Collaborative with graduate student: Yes;Collaborative with faculty member in unit: Yes;
• van Leeuwen, W. J., Kariyeva, J., & Willem, J. (2012). Phenological dynamics of irrigated and natural drylands in Central Asia before and after the USSR collapse. Agriculture, Ecosystems & Environment.
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  ;Your Role: Research design, co-author;Full Citation: Kariyeva, J., Willem J.D. van Leeuwen, 2012. Phenological dynamics of irrigated and natural drylands in Central Asia before and after the USSR collapse. Agriculture, Ecosystems & Environment, 162, 77-89.;Collaborative with graduate student: Yes;
• van Leeuwen, W. J., Kariyeva, J., Willem, J., & Leeuwen, V. (2012). Phenological dynamics of irrigated and natural drylands in Central Asia before and after the USSR collapse. Agriculture, Ecosystems & Environment, 162, 77-89.
• van Leeuwen, W. J., Kariyeva, J., Willem, J., Leeuwen, V., & Woodhouse, C. (2012). Impacts of climate gradients on the vegetation phenology of major land use types in Central Asia (1981-2008). Frontiers of Earth Science, 6(2), 206-225.
• van Leeuwen, W. J., Landau, K. I., & Willem, J. (2012). Fine scale spatial urban land cover factors associated with adult mosquito abundance and risk in Tucson. Journal of Vector Ecology.
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  ;Your Role: Research design;Full Citation: Landau, K.I., Willem J.D. van Leeuwen, 2012. Fine scale spatial urban land cover factors associated with adult mosquito abundance and risk in Tucson, Arizona. Journal of Vector Ecology, 37(2):407-418.;Collaborative with graduate student: Yes;
• van Leeuwen, W. J., Leon, R., R., J., J.D., W., & Casady, G. M. (2012). Using MODIS-NDVI for the Modeling of Post-Wildfire Vegetation Response as a Function of Environmental Conditions and Pre-Fire Restoration Treatments.. Remote Sensing.
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  ;Your Role: Research design co-author;Full Citation: Romo Leon, J. R., Willem J.D. van Leeuwen, G. M. Casady, 2012. Using MODIS-NDVI for the Modeling of Post-Wildfire Vegetation Response as a Function of Environmental Conditions and Pre-Fire Restoration Treatments. Remote Sensing. 4(3): 598-621.;Collaborative with graduate student: Yes;Collaborative with faculty member at UA: Yes;
• van Leeuwen, W. J., Nagler, P., Maruthi, S. B., Olsson, A., Willem, J., Leeuwen, V., & Glenn, E. (2012). Hyperspectral Remote Sensing Tools for Quantifying Plant Litter and Invasive Species in Arid Ecosystems. Hyperspectral remote sensing of vegetation.
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  Hyperspectral remote sensing of vegetation Edts. Prasad Srinivasa Thenkabail; J G Lyon; Alfredo Huete; Boca Raton, FL, CRC Press.
• van Leeuwen, W. J., Villarreal, M., Willem, J., Leeuwen, V., & Romo-Leon, J. (2012). Mapping and monitoring riparian vegetation distribution, structure and composition with regression tree models and post-classification change metrics. International Journal of Remote Sensing, 33(13), 4266-4290.
• Breshears, D. D., Casady, G. M., Leeuwen, W. J., & Davison, J. E. (2011). Remotely sensed vegetation phenology and productivity along a climatic gradient: on the value of incorporating the dimension of woody plant cover. Global Ecology and Biogeography. doi:10.1111/j.1466-8238.2010.00571.x
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  Aim Woody plants affect vegetation–environment interactions by modifying microclimate, soil moisture dynamics and carbon cycling. In examining broadscale patterns in terrestrial vegetation dynamics, explicit consideration of variation in the amount of woody plant cover could provide additional explanatory power that might not be available when only considering landscape-scale climate patterns or specific vegetation assemblages. Here we evaluate the interactive influence of woody plant cover on remotely sensed vegetation dynamics across a climatic gradient along a sky island. Location The Santa Rita Mountains, Arizona, USA. Methods Using a satellite-measured normalized difference vegetation index (NDVI) from 2000 to 2008, we conducted time-series and regression analyses to explain the variation in functional attributes of vegetation (productivity, seasonality and phenology) related to: (1) vegetation community, (2) elevation as a proxy for climate, and (3) woody plant cover, given the effects of the other environmental variables, as an additional ecological dimension that reflects potential vegetation– environment feedbacks at the local scale. Results NDVI metrics were well explained by interactions among elevation, vegetation community and woody plant cover. After accounting for elevation and vegetation community, woody plant cover explained up to 67% of variation in NDVI metrics and, notably, clarified elevation- and community-specific patterns of vegetation dynamics across the gradient.
• Davison, J. E., Breshears, D. D., J., W., & Casady, G. M. (2011). Remotely sensed vegetation phenology and productivity along a climatic gradient: On the value of incorporating the dimension of woody plant cover. Global Ecology and Biogeography, 20(1), 101-113.
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  Abstract: Aim Woody plants affect vegetation-environment interactions by modifying microclimate, soil moisture dynamics and carbon cycling. In examining broad-scale patterns in terrestrial vegetation dynamics, explicit consideration of variation in the amount of woody plant cover could provide additional explanatory power that might not be available when only considering landscape-scale climate patterns or specific vegetation assemblages. Here we evaluate the interactive influence of woody plant cover on remotely sensed vegetation dynamics across a climatic gradient along a sky island.Location The Santa Rita Mountains, Arizona, USA.Methods Using a satellite-measured normalized difference vegetation index (NDVI) from 2000 to 2008, we conducted time-series and regression analyses to explain the variation in functional attributes of vegetation (productivity, seasonality and phenology) related to: (1) vegetation community, (2) elevation as a proxy for climate, and (3) woody plant cover, given the effects of the other environmental variables, as an additional ecological dimension that reflects potential vegetation-environment feedbacks at the local scale.Results NDVI metrics were well explained by interactions among elevation, vegetation community and woody plant cover. After accounting for elevation and vegetation community, woody plant cover explained up to 67% of variation in NDVI metrics and, notably, clarified elevation- and community-specific patterns of vegetation dynamics across the gradient.Main conclusions In addition to the environmental factors usually considered - climate, reflecting resources and constraints, and vegetation community, reflecting species composition and relative dominance - woody plant cover, a broad-scale proxy of many vegetation-environment interactions, represents an ecological dimension that provides additional process-related understanding of landscape-scale patterns of vegetation function. © 2010 Blackwell Publishing Ltd.
• Davison, J. E., Breshears, D. D., van, L., & Casady, G. M. (2011). Remotely sensed vegetation phenology and productivity along a climatic gradient: on the value of incorporating the dimension of woody plant cover. GLOBAL ECOLOGY AND BIOGEOGRAPHY, 20(1), 101-113.
• Gu, Y., Brown, J. F., Miura, T., van Leeuwen, W. J., & Reed, B. C. (2011). Phenological Classification of the United States: A Geographic Framework for Extending Multi-Sensor Time-Series Data. REMOTE SENSING, 2(2), 526-544.
• Hartfield, K. A., Landau, K. I., & J.D., W. (2011). Fusion of high resolution aerial multispectral and lidar data: Land cover in the context of urban mosquito habitat. Remote Sensing, 3(11), 2364-2383.
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  Abstract: Remotely sensed multi-spectral and -spatial data facilitates the study of mosquito-borne disease vectors and their response to land use and cover composition in the urban environment. In this study we assess the feasibility of integrating remotely sensed multispectral reflectance data and LiDAR (Light Detection and Ranging)-derived height information to improve land use and land cover classification. Classification and Regression Tree (CART) analyses were used to compare and contrast the enhancements and accuracy of the multi-sensor urban land cover classifications. Eight urban land-cover classes were developed for the city of Tucson, Arizona, USA. These land cover classes focus on pervious and impervious surfaces and microclimate landscape attributes that impact mosquito habitat such as water ponds, residential structures, irrigated lawns, shrubs and trees, shade, and humidity. Results show that synergistic use of LiDAR, multispectral and the Normalized Difference Vegetation Index data produced the most accurate urban land cover classification with a Kappa value of 0.88. Fusion of multi-sensor data leads to a better land cover product that is suitable for a variety of urban applications such as exploring the relationship between neighborhood composition and adult mosquito abundance data to inform public health issues. © 2011 by the authors.
• Kariyeva, J., & J.D., W. (2011). Environmental drivers of NDVI-based vegetation phenology in Central Asia. Remote Sensing, 3(2), 203-246.
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  Abstract: Through the application and use of geospatial data, this study aimed to detect and characterize some of the key environmental drivers contributing to landscape-scale vegetation response patterns in Central Asia. The objectives of the study were to identify the variables driving the year-to-year vegetation dynamics in three regional landscapes (desert, steppe, and mountainous); and to determine if the identified environmental drivers can be used to explain the spatial-temporal variability of these spatio-temporal dynamics over time. It was posed that patterns of change in terrestrial phenology, derived from the 8 km bi-weekly time series of Normalized Difference Vegetation Index (NDVI) data acquired by the Advanced Very High Resolution Radiometer (AVHRR) satellites (1981-2008), can be explained through a multi-scale analysis of a suite of environmental drivers. Multiple linear stepwise regression analyses were used to test the hypotheses and address the objectives of the study. The annually computed phenological response variables or pheno-metricstime (season start, season length, and an NDVI-based productivity metric) were modeled as a function of ten environmental factors relating to soil, topography, and climate. Each of the three studied regional landscapes was shown to be governed by a distinctive suite of environmental drivers. The phenological responses of the steppe landscapes were affected by the year-to-year variation in temperature regimes. The phenology of the mountainous landscapes was influenced primarily by the elevation gradient. The phenological responses of desert landscapes were demonstrated to have the greatest variability over time and seemed to be affected by soil carbon content and year-to-year variation of both temperature regimes and winter precipitation patterns. Amounts and scales of observed phenological variability over time (measured through coefficient of variation for each pheno-metrictime) in each of the regional landscapes were interpreted in terms of their resistance and resilience capacities under existing and projected environmental settings. © 2011 by the authors.
• Kariyeva, J., & van Leeuwen, W. J. (2011). Environmental Drivers of NDVI-Based Vegetation Phenology in Central Asia. REMOTE SENSING, 3(2), 203-246.
• Leeuwen, W. V., & Vilaly, M. E. (2011). Remotely sensed vegetation phenology of sky islands in the madrean archipelago. 34th International Symposium on Remote Sensing of Environment - The GEOSS Era: Towards Operational Environmental Monitoring.
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  Abstract: The goal of this work is to develop an assessment of changes in landscape scale phenology (Timing of biological events such as green-up and flowering) for vegetation along elevation gradients for mountain sky islands in the drylands of the Southwest US and Northern Mexico. The main goal is to better understand the variability in climate and vegetation green-up relationships as they vary seasonally and interannually and along the elevation and latitudinal gradients. Land surface phenological time series derived from the MODIS Normalized Difference Vegetation Index data from 2000 to 2010 were processed to characterize the interannual and seasonal variability among different sky islands in the Madrean Archipelago. Representative mountains among the sky islands and elevation clines showed unique recurring and interannual phenological trajectories and spatial patterns related to seasonality, drought, and some wildfire events. The start of the season was generally earlier for the higher elevations, while seasonal productivity generally increased with elevation.
• Leeuwen, W. V., Hutchinson, C., Drake, S., Doorn, B., Kaupp, V., Haithcoat, T., Likholetov, V., Sheffner, E., & Tralli, D. (2011). Benchmarking enhancements to a decision support system for global crop production assessments. Expert Systems with Applications, 38(7), 8054-8065.
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  Abstract: The Office of Global Analysis/International Production Assessment Division (OGA/IPAD) of the United States Department of Agriculture - Foreign Agricultural Service (USDA-FAS) has been assimilating new data and information products from agencies such as the National Aeronautics and Space Administration (NASA) into its operational decision support system (DSS). The FAS mission is to improve monthly estimates of global production of major agricultural commodities and provide US Government senior decision makers and the public the most accurate, timely, and objective assessment of the global food supply situation possible. These estimates are ultimately captured as the US governments' official assessments of world food supply for the commodity markets and policy makers. The goal of this research was to measure changes in the quality and accuracy of decision support information resulting from the assimilation of new NASA products in the DSS. We gathered both qualitative and quantitative information through questionnaires and interviews to benchmark these changes. We used an interactive project lifecycle risk management tool developed for NASA mission spaceflight design and quality assurance (DDP - Defect Detection and Prevention) to do this. In this case, we used it to (1) quantify the change in DSS Objectives attained after assimilation of new products, and (2) evaluate the effectiveness of various Mitigation options against potential Risks. The change in Objectives attainment was considered the most important benchmarking indicator for examining the effectiveness of the assimilation of NASA products into OGA/IPAD's DSS. From this research emerged a novel model for benchmarking DSSs that (1) promotes continuity and synergy within and between government agencies, (2) accommodates scientific, operational and architectural dynamics, and (3) facilitates transfer of knowledge among research, management, and decision-making agencies. © 2011 Elsevier Ltd. All rights reserved.
• Leeuwen, v., J.D, W., Hutchinson, C., Drake, S., Doorn, B., Kaupp, V., Haithcoat, T., Likholetov, V., Sheffner, E., & Tralli, D. (2011). Benchmarking enhancements to a decision support system for global crop production. Expert Systems with Applications.
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  ;Your Role: Lead author, NASA sponsored research;Full Citation: van Leeuwen, Willem J.D, Chuck Hutchinson, Sam Drake, Brad Doorn, Verne Kaupp, Tim Haithcoat, Vladislav Likholetov, Ed Sheffner, and Dave Tralli, 2011. Benchmarking enhancements to a decision support system for global crop production, Expert Systems with Applications 38(7): 8054-806.;Collaborative with faculty member in unit: Yes;Other collaborative: Yes;Specify other collaborative: JPL, NASA, USDA, Univ of Missouri collaborators;
• Leon, J. R., van Leeuwen, W. J., & Casady, G. M. (2011). Using MODIS-NDVI for the Modeling of Post-Wildfire Vegetation Response as a Function of Environmental Conditions and Pre-Fire Restoration Treatments. REMOTE SENSING, 4(3), 598-621.
• van Leeuwen, W. J. (2011). Monitoring the effects of forest restoration treatments on post-fire vegetation recovery with MODIS multitemporal data. SENSORS, 8(3), 2017-2042.
• van Leeuwen, W. J., Davison, J., Breshears, D., Leeuwen, V., WJD, ., & Casady, G. (2011). Remotely sensed vegetation phenology and productivity along a climatic gradient: on the value of incorporating the dimension of woody plant cover. Global Ecology and Biogeography, 20, 101-113.
• van Leeuwen, W. J., Hartfield, K. A., Landau, K. I., & Willem, J. (2011). Fusion of High Resolution Aerial Multispectral and LiDAR Data: Land Cover in the Context of Urban Mosquito Habitat. Remote Sensing.
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  ;Your Role: Senior author; research lead; NSF sponsored research;Full Citation: Hartfield, Kyle A., Landau, Katheryn I., Willem J.D. van Leeuwen, 2011. Fusion of High Resolution Aerial Multispectral and LiDAR Data: Land Cover in the Context of Urban Mosquito Habitat. Remote Sensing, 3(11): 2364-2383.;Electronic: Yes;Collaborative with graduate student: Yes;Other collaborative: Yes;Specify other collaborative: Kyle Hartfield is a senior research specialist at the Arizona Remote Sensing Center;
• van Leeuwen, W. J., Hartfield, K., Landau, K., Willem, J., & Leeuwen, V. (2011). Fusion of High Resolution Aerial Multispectral and LiDAR Data: Land Cover in the Context of Urban Mosquito Habitat. Remote Sensing, 3(11), 2364-2383.
• van Leeuwen, W. J., Kariyeva, J., & Willem, J. (2011). Environmental Drivers of NDVI-based Vegetation Dynamics in Central Asia, Special Issue Remote Sensing in Climate Monitoring and Analysis. Kariyeva, Jahan, and Willem J.D. van Leeuwen.
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  ;Your Role: Collaborator and sharing ideas; helped with writing.Funded on NASA grant.;Full Citation: Kariyeva, Jahan, and Willem J.D. van Leeuwen, 2011. Environmental Drivers of NDVI-based Vegetation Dynamics in Central Asia, Special Issue Remote Sensing in Climate Monitoring and Analysis - Remote Sensing, 3(2), 203-246;Electronic: Yes;Collaborative with graduate student: Yes;
• van Leeuwen, W. J., Kariyeva, J., Willem, J., & Leeuwen, V. (2011). Environmental Drivers of NDVI-based Vegetation Dynamics in Central Asia, Special Issue Remote Sensing in Climate Monitoring and Analysis. Remote Sensing, 3(2), 203-246.
• van Leeuwen, W. J., Leeuwen, V., Willem, J., Hutchinson, C., Drake, S., Doorn, B., Kaupp, V., Haithcoat, T., Likholetov, V., Sheffner, E., & Tralli, D. (2011). Benchmarking enhancements to a decision support system for global crop production. Expert Systems with Applications, 38(7), 8054-806.
• van Leeuwen, W. J., Olsson, A., Willem, J., & Marsh, S. E. (2011). Feasibility of Invasive Grass Detection in a Desertscrub Community Using Hyperspectral Field Measurements and Landsat TM Imagery. Remote Sensing.
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  ;Your Role: Collaborator , providing ideas and spectral data;helped writing and editing;Full Citation: Olsson, A., Willem J.D. van Leeuwen, and Stuart E. Marsh. 2011. Feasibility of Invasive Grass Detection in a Desertscrub Community Using Hyperspectral Field Measurements and Landsat TM Imagery. Remote Sensing, 3(10):2283-2304.;Electronic: Yes;Collaborative with graduate student: Yes;Collaborative with faculty member in unit: Yes;
• van Leeuwen, W. J., Olsson, A., Willem, J., Leeuwen, V., & Marsh, S. (2011). Feasibility of Invasive Grass Detection in a Desertscrub Community Using Hyperspectral Field Measurements and Landsat TM Imagery. Remote Sensing, 3(10), 2283-2304.
• van Leeuwen, W. J., Villarreal, M. L., & Willem, J. (2011). Mapping and monitoring riparian vegetation distribution, structure and composition with regression tree models and post-classification change metrics. International Journal of Remote Sensing.
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  online Dec 2011;Your Role: Directed CART classification; sponsored by NPSHelped design research project;Full Citation: Villarreal, M.L., Willem J.D. van Leeuwen, Jose Raul Romo-Leon. 2012. Mapping and monitoring riparian vegetation distribution, structure and composition with regression tree models and post-classification change metrics, International Journal of Remote Sensing, 33:13, 4266-4290.;Electronic: Yes;Collaborative with graduate student: Yes;
• van Leeuwen, W. J., sensed, R., & along, p. (2011). Remotely sensed vegetation phenology and productivity along a climatic gradient: on the value of incorporating the dimension of woody plant cover. Global Ecology and Biogeography.
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  ;Your Role: [This manuscript came about as part of my phenology research program and Breshears' woody plant cover interests. I supervised and partially funded M.S. student Davison and worked with post-doc Casady, contributing to research ideas, writing, provided extensive pre-submission comments, and supported submission and final revisions.];Full Citation: Davison, J.E., Breshears, D.D., van Leeuwen, W.J.D., & Casady, G.M., 2011. Remotely sensed vegetation phenology and productivity along a climatic gradient: on the value of incorporating the dimension of woody plant cover. Global Ecology and Biogeography, 20, 101 113;Collaborative with graduate student: Yes;Collaborative with faculty member in unit: Yes;
• Casady, G. M., van, L., & Marsh, S. E. (2010). Evaluating Post-wildfire Vegetation Regeneration as a Response to Multiple Environmental Determinants. ENVIRONMENTAL MODELING & ASSESSMENT, 15(5), 295-307.
• Hartfield, K. A., Landau, K. I., & van Leeuwen, W. J. (2010). Fusion of High Resolution Aerial Multispectral and LiDAR Data: Land Cover in the Context of Urban Mosquito Habitat. REMOTE SENSING, 3(11), 2364-2383.
• J., W., Casady, G. M., Neary, D. G., Bautista, S., Alloza, J. A., Carmel, Y., Wittenberg, L., Malkinson, D., & Orr, B. J. (2010). Monitoring post-wildfire vegetation response with remotely sensed time-series data in Spain, USA and Israel. International Journal of Wildland Fire, 19(1), 75-93.
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  Abstract: Due to the challenges faced by resource managers in maintaining post-fire ecosystem health, there is a need for methods to assess the ecological consequences of disturbances. This research examines an approach for assessing changes in post-fire vegetation dynamics for sites in Spain, Israel and the USA that burned in 1998, 1999 and 2002 respectively. Moderate Resolution Imaging Spectroradiometer satellite Normalized Difference Vegetation Index (NDVI) time-series data (200007) are used for all sites to characterise and track the seasonal and spatial changes in vegetation response. Post-fire trends and metrics for burned areas are evaluated and compared with unburned reference sites to account for the influence of local environmental conditions. Time-series data interpretation provides insights into climatic influences on the post-fire vegetation. Although only two sites show increases in post-fire vegetation, all sites show declines in heterogeneity across the site. The evaluation of land surface phenological metrics, including the start and end of the season, the base and peak NDVI, and the integrated seasonal NDVI, show promising results, indicating trends in some measures of post-fire phenology. Results indicate that this monitoring approach, based on readily available satellite-based time-series vegetation data, provides a valuable tool for assessing post-fire vegetation response. © 2010 IAWF.
• Leeuwen, v., J.D., W., J.E., D., G.M., C., & S.E., M. (2010). Phenological Characterization of Desert Sky Island Vegetation Communities with Remotely Sensed and Climate Time Series Data. Remote Sensing.
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  ;Your Role: This paper explored how climate impacts remotely sensed phenology of vegetation communities along an elevation gradient in AZ. I led this project and had help from graduate students Davison and Casady and Dr. Marsh;Full Citation: van Leeuwen, Willem J.D., Davison J.E.MS, Casady G.M.PhD, and Marsh S.E., 2010. Phenological Characterization of Desert Sky Island Vegetation Communities with Remotely Sensed and Climate Time Series Data. Remote Sens., 2, 388-415.;Collaborative with graduate student: Yes;Collaborative with faculty member in unit: Yes;
• Leeuwen, v., J.D., W., M., G., Neary, D. G., , S. B., Alloza, J. A., , Y. C., , L. W., , D. M., & Orr, B. J. (2010). Monitoring post-wildfire vegetation response with remotely sensed time-series data in Spain, USA and Israel.. International Journal of Wildland Fire.
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  This article was featured on the Int J of Wildland Fire's website.;Your Role: This multi-country collaborative wildfire research was based on an IALC funded proposal I was co-PI on. I led the research effort and manuscript authoring. Graduate student Casady helped with data analysis and manuscript preparations.;Full Citation: van Leeuwen, Willem J.D., G. M. Casady PhD, D. G. Neary, S. Bautista, J. A. Alloza, Y. Carmel, L. Wittenberg, D. Malkinson, B. J. Orr, 2010. Monitoring post-wildfire vegetation response with remotely sensed time-series data in Spain, USA and Israel. International Journal of Wildland Fire, 19: 75-93. ;Collaborative with graduate student: Yes;Collaborative with faculty member in unit: Yes;Other collaborative: Yes;Specify other collaborative: Collaborative research with University of Alicante,Spain, University of Haifa and Technion, Israel, and USDA-FS;
• Marsh, S. E., Leeuwen, W. J., & Casady, G. M. (2010). Evaluating Post-wildfire Vegetation Regeneration as a Response to Multiple Environmental Determinants. Environmental Modeling & Assessment. doi:10.1007/s10666-009-9210-x
• Olsson, A. D., van Leeuwen, W. J., & Marsh, S. E. (2010). Feasibility of Invasive Grass Detection in a Desertscrub Community Using Hyperspectral Field Measurements and Landsat TM Imagery. REMOTE SENSING, 3(10), 2283-2304.
• Yingxin, G. u., Brown, J. F., Miura, T., J.D., W., & Reed, B. C. (2010). Phenological classification of the United States: A geographic framework for extending multi-sensor time-series data. Remote Sensing, 2(2), 526-544.
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  Abstract: This study introduces a new geographic framework, phenological classification, for the conterminous United States based on Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) time-series data and a digital elevation model. The resulting pheno-class map is comprised of 40 pheno-classes, each having unique phenological and topographic characteristics. Cross-comparison of the pheno-classes with the 2001 National Land Cover Database indicates that the new map contains additional phenological and climate information. The pheno-class framework may be a suitable basis for the development of an Advanced Very High Resolution Radiometer (AVHRR)-MODIS NDVI translation algorithm and for various biogeographic studies. © 2010 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland.
• van Leeuwen, W. J., Casady, G. M., & Willem, J. (2010). Evaluating post wildfire vegetation dynamics as a response to multiple environmental determinants.. Environmental Modeling and Assessment.
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  ;Your Role: [This paper examined the impact of environmental factors on wildfire as part of the Rodeo-Chediski Fire research that I have been working on. I worked with student Casady, contributing to his research with ideas, writing, and edits to the final paper.;Full Citation: Casady, G.M.PhD, Willem J.D. van Leeuwen, S.E. Marsh. 2010. Evaluating post wildfire vegetation dynamics as a response to multiple environmental determinants. Environmental Modeling and Assessment. 15(5): 295-307. ;Collaborative with graduate student: Yes;Collaborative with faculty member in unit: Yes;
• van Leeuwen, W. J., Casady, G. M., Neary, D. G., Bautista, S., Antonio Alloza, J., Carmel, Y., Wittenberg, L., Malkinson, D., & Orr, B. J. (2010). Monitoring post-wildfire vegetation response with remotely sensed time-series data in Spain, USA and Israel. INTERNATIONAL JOURNAL OF WILDLAND FIRE, 19(1), 75-93.
• van Leeuwen, W. J., Gu, Y., Jesslyn, F., Willem, J., & Reed., B. C. (2010). Phenological classification of the United States: A geographic framework for extending multi-sensor time-series data. Remote Sensing.
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  ;Your Role: This paper came together as part of some preliminary research I worked on in AZ, which was then extended by the USGS to a continental scale to inform multi-sensor continuity research. I contributed to this research with ideas, writing, and edits to the preliminary drafts and final paper.;Full Citation: Gu, Yingxin, Jesslyn F. Brown, Tomoaki Miura, Willem J.D. van Leeuwen, and Bradley C. Reed. 2010. Phenological classification of the United States: A geographic framework for extending multi-sensor time-series data, Remote Sens., 2, 526-544.;Other collaborative: Yes;Specify other collaborative: Collabortive research with University of Hawaii and the USGS (Sioux Falls);
• van Leeuwen, W. J., van Leeuwen, W. J., J.E., D., J.E., D., Breshears, ., Breshears, ., J.D., W., J.D., W., Casady, ., & Casady, . (2010). Remotely sensed vegetation phenology and productivity along a climatic gradient: on the value of incorporating the dimension of woody plant cover.. Global Ecology and Biogeography..
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  Added Student annotation in full citation- MS-MS studentPhD -PhD student;Your Role: This manuscript came about as part of my phenology research program and Breshears' woody plant cover interests. I supervised and partially funded M.S. student Davison and worked with post-doc Casady, contributing to research ideas, writing, provided extensive pre-submission comments, and supported submission and final revisions.;Full Citation: Davison J.E.MS, Breshears, D.D., Willem J.D. van Leeuwen, Casady, G.M.PhD, 2010. Remotely sensed vegetation phenology and productivity along a climatic gradient: on the value of incorporating the dimension of woody plant cover. Global Ecology and Biogeography. In press; Online July 10, 2010. http://dx.doi.org/10.1111/j.1466-8238.2010.00571.x Accessed 10-2-2010.;Collaborative with graduate student: Yes;Collaborative with faculty member in unit: Yes;
• Leeuwen, W. V., & Kariyeva, J. (2009). An assessment of remotely sensed land surface phenology for detecting spatio-temporal landscape change patterns: Arizona and its National Parks. Proceedings, 33rd International Symposium on Remote Sensing of Environment, ISRSE 2009, 270-273.
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  Abstract: The Arizona landscape is undergoing changes in vegetation growth patterns that are due to disturbances related to wildfire, extreme drought and precipitation events, and human interactions. Vegetation phenology is one of the vital signs for evaluating and monitoring ecosystems that are of interest to the US National Park Monitoring Network. Long term MODIS and AVHRR time series vegetation index data (1989-current) are used to characterize and examine vegetation growth trajectories and phenology of the Arizona landscape with a focus on National Parks. The phenological metrics include: time of start, peak and end of the growing season and seasonally integrated vegetation index value metrics related to biomass production. Patterns in stable and anomalous vegetation dynamics were examined visually and quantified by using pheno-metrics and trend statistics. The spatio-temporal phenological characterization show distinctive vegetation response patterns and trajectories that provide a means to monitor the natural resources of Arizona and its National Parks.
• Marsh, S. E., Van Leeuwen, W. J., Huang, C., & Geiger, E. L. (2009). Discrimination of invaded and native species sites in a semi‐desert grassland using MODIS multi‐temporal data. International Journal of Remote Sensing, 30(4), 897-917. doi:10.1080/01431160802395243
• White, M. A., M., K., Didan, K., Inouye, D. W., Richardson, A. D., Jensen, O. P., O'Keefe, J., Zhang, G., Nemani, R. R., J.D., W., Brown, J. F., Wit, A. d., Schaepman, M., Lin, X., Dettinger, M., Bailey, A. S., Kimball, J., Schwartz, M. D., Baldocchi, D. D., , Lee, J. T., et al. (2009). Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982-2006. Global Change Biology, 15(10), 2335-2359.
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  Abstract: Shifts in the timing of spring phenology are a central feature of global change research. Long-term observations of plant phenology have been used to track vegetation responses to climate variability but are often limited to particular species and locations and may not represent synoptic patterns. Satellite remote sensing is instead used for continental to global monitoring. Although numerous methods exist to extract phenological timing, in particular start-of-spring (SOS), from time series of reflectance data, a comprehensive intercomparison and interpretation of SOS methods has not been conducted. Here, we assess 10 SOS methods for North America between 1982 and 2006. The techniques include consistent inputs from the 8 km Global Inventory Modeling and Mapping Studies Advanced Very High Resolution Radiometer NDVIg dataset, independent data for snow cover, soil thaw, lake ice dynamics, spring streamflow timing, over 16000 individual measurements of ground-based phenology, and two temperature-driven models of spring phenology. Compared with an ensemble of the 10 SOS methods, we found that individual methods differed in average day-of-year estimates by ± 60 days and in standard deviation by ± 20 days. The ability of the satellite methods to retrieve SOS estimates was highest in northern latitudes and lowest in arid, tropical, and Mediterranean ecoregions. The ordinal rank of SOS methods varied geographically, as did the relationships between SOS estimates and the cryospheric/hydrologic metrics. Compared with ground observations, SOS estimates were more related to the first leaf and first flowers expanding phenological stages. We found no evidence for time trends in spring arrival from ground- or model-based data; using an ensemble estimate from two methods that were more closely related to ground observations than other methods, SOS trends could be detected for only 12% of North America and were divided between trends towards both earlier and later spring. © 2009 Blackwell Publishing Ltd.
• van Leeuwen, W. J., Huang, C., Geiger, E., Willem, J., Marsh, ., & S., . (2009). Discrimination of invaded and native species sites in a semi-desert grassland using MODIS multi-temporal data. International Journal of Remote Sensing.
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  ;Your Role: Provided guidance, input and feedback towards satellite data processing, data analysis and manuscript that was lead by a graduate student (first author).;Full Citation: Huang, C., Geiger, E., Willem J.D. van Leeuwen, and Marsh, S., 2009. Discrimination of invaded and native species sites in a semi-desert grassland using MODIS multi-temporal data. International Journal of Remote Sensing, Vol. 30, No. 4, pp 897-917. ;Collaborative with graduate student: Yes;Collaborative with faculty member in unit: Yes;
• van Leeuwen, W. J., White, M. A., M., K., Didan, K., Inouye, D. W., Richardson, A. D., Jensen, O. P., Magnuson, J., O'Keefe, J., Zhang, G., Nemani, R. R., J.D., W., Brown, J. F., de, A., Schaepman, M., & Xioam, . (2009). Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982 to 2006. Global Change Biology.
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  ;Your Role: I provided input to the original ideas and provided the output data related to one of the land surface phenology algorithms (Savitsky Golay multi-polynomial fit. I contributed and edited sections of the paper;Full Citation: Michael A. White, Kirsten M. de Beurs, Kamel Didan, David W. Inouye, Andrew D. Richardson, Olaf P. Jensen, John Magnuson, John O'Keefe, Gong Zhang, Ramakrishna R. Nemani, Willem J.D. van Leeuwen, Jesselyn F. Brown, Allard de Wit, Michael Schaepman, Xioamao Lin, Michael Dettinger, Amey Bailey, John Kimball, Mark D. Schwartz, Dennis D. Baldocchi, John T. Lee, William K. Lauenroth, 2009. Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982 to 2006. Global Change Biology, Volume 15, Number 10, October 2009, pp. 2335-2359(25);Collaborative with faculty member at UA: Yes;Other collaborative: Yes;Specify other collaborative: International collaborative project. Most collaborators are based in the US. Some are from Europe.The paper was a result of discussions at the 2008 AGU meetings, where we had a session on phenology. Mike White lead this paper with Kirsten deBeurs. ;
• van Leeuwen, W., Orr, B., Marsh, S., & Herrmann, S. (2009). Multi-sensor NDVI data continuity: Uncertainties and implications for vegetation monitoring applications. REMOTE SENSING OF ENVIRONMENT, 100(1), 67-81.
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  Consistent NDVI time series are paramount in monitoring ecological resources that are being altered by climate and human impacts. An increasing number of natural resource managers use web-based geospatial decision support tools that integrate time series of both historical and current NDVI data derived from multiple sensors to make better informed planning and management decisions. Representative canopy reflectance and NDVI data were simulated for historical, current and future AVHRR, MODIS and VIIRS land surface monitoring satellites to quantify the differences due to sensor-specific characteristics. Cross-sensor NDVI translation equations were developed for surface conditions. The effect of a range of atmospheric conditions (Rayleigh scattering, ozone, aerosol optical thickness, and water vapor content) on the sensor-specific reflectance and NDVI values were evaluated to quantify the uncertainty in the apparent NDVI for each sensor. MODIS and VIIRS NDVI data are minimally affected by the atmospheric water vapor, while AVHRR NDVI data are substantially reduced by water vapor.
• Huete, A., Didan, K., van Leeuwen, W., Miura, T., Glenn, E., Ramachandran, B., Justice, C., & Abrams, M. (2008). MODIS Vegetation Indices. LAND REMOTE SENSING AND GLOBAL ENVIRONMENTAL CHANGE: NASA'S EARTH OBSERVING SYSTEM AND THE SCIENCE OF ASTER AND MODIS, 11, 579-602.
• J., W. (2008). Monitoring the effects of forest restoration treatments on post-fire vegetation recovery with MODIS multitemporal data. Sensors, 8(3), 2017-2042.
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  Abstract: This study examines how satellite based time-series vegetation greenness data and phenological measurements can be used to monitor and quantify vegetation recovery after wildfire disturbances and examine how pre-fire fuel reduction restoration treatments impact fire severity and impact vegetation recovery trajectories. Pairs of wildfire affected sites and a nearby unburned reference site were chosen to measure the post-disturbance recovery in relation to climate variation. All site pairs were chosen in forested uplands in Arizona and were restricted to the area of the Rodeo-Chediski fire that occurred in 2002. Fuel reduction treatments were performed in 1999 and 2001. The inter-annual and seasonal vegetation dynamics before, during, and after wildfire events can be monitored using a time series of biweekly composited MODIS NDVI (Moderate Resolution Imaging Spectroradiometer - Normalized Difference Vegetation Index) data. Time series analysis methods included difference metrics, smoothing filters, and fitting functions that were applied to extract seasonal and inter-annual change and phenological metrics from the NDVI time series data from 2000 to 2007. Pre- and post-fire Landsat data were used to compute the Normalized Burn Ratio (NBR) and examine burn severity at the selected sites. The phenological metrics (pheno-metrics) included the timing and greenness (i.e. NDVI) for the start, peak and end of the growing season as well as proxy measures for the rate of green-up and senescence and the annual vegetation productivity. Pre-fire fuel reduction treatments resulted in lower fire severity, which reduced annual productivity much less than untreated areas within the Rodeo-Chediski fire perimeter. The seasonal metrics were shown to be useful for estimating the rate of post-fire disturbance recovery and the timing of phenological greenness phases. The use of satellite time series NDVI data and derived pheno-metrics show potential for tracking vegetation cover dynamics and successional changes in response to drought, wildfire disturbances, and forest restoration treatments in fire-suppressed forests. © 2008 by MDPI.
• Leeuwen, W. J. (2008). Monitoring the Effects of Forest Restoration Treatments on Post-Fire Vegetation Recovery with MODIS Multitemporal Data. Sensors. doi:10.3390/s8032017
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  This study examines how satellite based time-series vegetation greenness data and phenological measurements can be used to monitor and quantify vegetation recovery after wildfire disturbances and examine how pre-fire fuel reduction restoration treatments impact fire severity and impact vegetation recovery trajectories. Pairs of wildfire affected sites and a nearby unburned reference site were chosen to measure the post-disturbance recovery in relation to climate variation. All site pairs were chosen in forested uplands in Arizona and were restricted to the area of the Rodeo-Chediski fire that occurred in 2002. Fuel reduction treatments were performed in 1999 and 2001. The inter-annual and seasonal vegetation dynamics before, during, and after wildfire events can be monitored using a time series of biweekly composited MODIS NDVI (Moderate Resolution Imaging Spectroradiometer - Normalized Difference Vegetation Index) data. Time series analysis methods included difference metrics, smoothing filters, and fitting functions that were applied to extract seasonal and inter-annual change and phenological metrics from the NDVI time series data from 2000 to 2007. Pre- and post-fire Landsat data were used to compute the Normalized Burn Ratio (NBR) and examine burn severity at the selected sites. The phenological metrics (pheno-metrics) included the timing and greenness (i.e. NDVI) for the start, peak and end of the growing season as well as proxy measures for the rate of green-up and senescence and the annual vegetation productivity. Pre-fire fuel reduction treatments resulted in lower fire severity, which reduced annual productivity much less than untreated areas within the Rodeo-Chediski fire perimeter. The seasonal metrics were shown to be useful for estimating the rate of post-fire disturbance recovery and the timing of phenological greenness phases. The use of satellite time series NDVI data and derived pheno-metrics show potential for tracking vegetation cover dynamics and successional changes in response to drought, wildfire disturbances, and forest restoration treatments in fire-suppressed forests.
• van Leeuwen, W. J. (2008). Monitoring the Effects of Forest Restoration Treatments on Post-Fire Vegetation Recovery with MODIS Multitemporal Data. Sensors.
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  This article belongs to the special issue Remote Sensing of Natural Resources and the Environmenthttp://www.mdpi.com/1424-8220/8/3/2017;Your Role: Performed research and authored this solely;Full Citation: van Leeuwen, Willem J.D., 2008. Monitoring the Effects of Forest Restoration Treatments on Post-Fire Vegetation Recovery with MODIS Multitemporal Data. Sensors, 8, 2017-2042;
• Kaupp, V., Haithcoat, T., Likholetov, V., Hutchinson, C., Drake, S., & Leeuwen, W. V. (2007). Benchmarking: The end of the process. International Geoscience and Remote Sensing Symposium (IGARSS), 2211-2212.
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  Abstract: A typical NASA Applied Sciences Program project will involve transformation of a partner's national, state, or local decision support system (DSS) to accept and use new NASA research products. The baseline DSS is typically called State 1 and the transformed, enhanced DSS is State 2. Benchmarking measures the performance of a DSS before and after enhancement. It measures the differences in a partner's DSS resulting from enhancements to it arising from use of new Earth science results, and as such, it is the end of the process. We use the Defect Detection and Prevention [1,2] (DDP) process and tool for benchmarking. DDP is both a process for information collection and quantification, and a tool for analysis and visualization of changing "risk profiles" and levels of objectives attainment between DSS State 1 and State 2. Examples of Benchmarking are discussed. © 2007 IEEE.
• Losleben, M., & Leeuwen, W. v. (2007). Our changing biological and climate calendar, or, what is phenology and why should we care?. Arid Lands Newsletter.
• van Leeuwen, W. J., & Losleben, M. (2007). Our changing biological and climate calendar, or, what is phenology and why should we care?. Arid Lands Newsletter.
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  ;Your Role: Co-author;Full Citation: Losleben, Mark and Willem J.D. van Leeuwen, Our changing biological and climate calendar, or, what is phenology and why should we care? Arid Lands Newsletter No. 59, August, 2007. http://ag.arizona.edu/OALS/ALN/aln59/losleben.html.;Electronic: Yes;Other collaborative: Yes;Specify other collaborative: Collaborative with associate director of the National Phenology Network (NPN) and Office of Arid Lands staff member;
• Herrmann, S. M., Marsh, S. E., Orr, B. J., & Leeuwen, W. J. (2006). Multi-sensor NDVI data continuity: Uncertainties and implications for vegetation monitoring applications. Remote Sensing of Environment. doi:10.1016/j.rse.2005.10.002
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  Abstract Consistent NDVI time series are paramount in monitoring ecological resources that are being altered by climate and human impacts. An increasing number of natural resource managers use web-based geospatial decision support tools that integrate time series of both historical and current NDVI data derived from multiple sensors to make better informed planning and management decisions. Representative canopy reflectance and NDVI data were simulated for historical, current and future AVHRR, MODIS and VIIRS land surface monitoring satellites to quantify the differences due to sensor-specific characteristics. Cross-sensor NDVI translation equations were developed for surface conditions. The effect of a range of atmospheric conditions (Rayleigh scattering, ozone, aerosol optical thickness, and water vapor content) on the sensor-specific reflectance and NDVI values were evaluated to quantify the uncertainty in the apparent NDVI for each sensor. MODIS and VIIRS NDVI data are minimally affected by the atmospheric water vapor, while AVHRR NDVI data are substantially reduced by water vapor. Although multi-sensor NDVI continuity can be obtained by using the developed cross-sensor translation equations, the interactions between the spectral characteristics of surface vegetation and soil components, sensor-specific spectral band characteristics and atmospheric scattering and absorption windows will introduce uncertainty due to insufficient knowledge about the atmospheric conditions that affect the signal of the Earth's pixels at the time of data acquisitions. Processing strategies and algorithm preferences among data streams are also hindering cross-sensor NDVI continuity.
• J., W., & Orr, B. J. (2006). Spectral vegetation indices and uncertainty: Insights from a user's perspective. IEEE Transactions on Geoscience and Remote Sensing, 44(7), 1931-1933.
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  Abstract: The primary objectives of this response communication are to provide insight into the use of spectral vegetation indices (SVIs) and a user's perspective on the uncertainty in SVI values, especially when these are derived from multiple sensors. We review how two papers in this special issue address uncertainty, and we explore two practical applications of SVI products and how comprehensive quantification and spatially explicit visualization of uncertainty could enhance their use. Although researchers identify the causes of uncertainties in SVIs, there has been little advancement in connecting and integrating the associated uncertainties inherent to all steps of the processing and model chains (e.g., data capture, data input and SVI generation). Cross-comparison of uncertainty assessment is challenging to the end-product user because reporting of uncertainty tends to be research or data product-specific with limited emphasis on facilitating the interpretation of uncertainty associated with algorithm and processing quality for use by managers or decision makers. Consequently, the confidence in these data is often based on experience and visual confirmation of the spatial and temporal consistency in SVI imagery and time-series data. Although the level of accuracy required varies depending on use, overall product quality assurance and a comprehensive, site-specific uncertainty assessment bundled with SVI data fields could mean the difference between using SVIs to report on spatial-temporal patterns versus using these data to make natural resource management decisions. © 2006 IEEE.
• J., W., Hutchinson, C. F., Doorn, B., Sheffner, E., & Kaupp, V. H. (2006). Integrated crop production observations and information system. International Geoscience and Remote Sensing Symposium (IGARSS), 3506-3508.
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  Abstract: The US Department of Agriculture (USDA), the National Aeronautics and Space Administration (NASA) and several academic institutions partnered in transitioning selected NASA Earth science data products, knowledge, capacity, and systems into solutions to enhance a decision support system (DSS) of the Foreign Agricultural Services (FAS) Production Estimates and Crop Assessment Division (PECAD). This enhancement improves PECAD's decision support to the World Agricultural Outlook Board (WAOB) by providing improved monthly estimates of global production (based on crop yield and planted area) of selected agricultural commodities.
• Leeuwen, v., , B. O., , S. M., & , S. H. (2006). Multi-Sensor NDVI Data Continuity: Uncertainties and Implications for Vegetation Monitoring Applications. Remote Sensing Of Environment.
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  ;Your Role: Author and research;Full Citation: Multi-Sensor NDVI Data Continuity: Uncertainties and Implications for Vegetation Monitoring Applications van Leeuwen, W.J.D., B. Orr, S. Marsh, S. Herrmann, 2006. Multi-Sensor NDVI Data Continuity: Uncertainties and Implications for Vegetation Monitoring Applications. Remote Sensing Of Environment. Vol. 100 (1) 67-81.;Collaborative with graduate student: Yes;Collaborative with faculty member in unit: Yes;
• Leeuwen, v., J.D., W., & Orr, B. J. (2006). Spectral Vegetation Indices and Uncertainty: Insights from a Users' Perspective. IEEE Transactions on Geoscience and Remote Sensing.
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  ;Your Role: research and author;Full Citation: Spectral Vegetation Indices and Uncertainty: Insights from a Users' Perspective van Leeuwen, Willem J.D., Barron J. Orr, 2006. Spectral Vegetation Indices and Uncertainty: Insights from a User s Perspective. IEEE Transactions on Geoscience and Remote Sensing. Vol. 44, Issue: 7, Part 1, 1931- 1933. ;Collaborative with faculty member in unit: Yes;
• White, M. A., de Beurs, K. M., Didan, K., Inouye, D. W., Richardson, A. D., Jensen, O. P., O'Keefe, J., Zhang, G., Nemani, R. R., van Leeuwen, W. J., Brown, J. F., de Wit, A., Schaepman, M., Lin, X., Dettinger, M., Bailey, A. S., Kimball, J., Schwartz, M. D., Baldocchi, D. D., , Lee, J. T., et al. (2006). Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982-2006. GLOBAL CHANGE BIOLOGY, 15(10), 2335-2359.
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  Shifts in the timing of spring phenology are a central feature of global change research. Long-term observations of plant phenology have been used to track vegetation responses to climate variability but are often limited to particular species and locations and may not represent synoptic patterns. Satellite remote sensing is instead used for continental to global monitoring. Although numerous methods exist to extract phenological timing, in particular start-of-spring (SOS), from time series of reflectance data, a comprehensive intercomparison and interpretation of SOS methods has not been conducted. Here, we assess 10 SOS methods for North America between 1982 and 2006. The techniques include consistent inputs from the 8 km Global Inventory Modeling and Mapping Studies Advanced Very High Resolution Radiometer NDVIg dataset, independent data for snow cover, soil thaw, lake ice dynamics, spring streamflow timing, over 16 000 individual measurements of ground-based phenology, and two temperature-driven models of spring phenology. Compared with an ensemble of the 10 SOS methods, we found that individual methods differed in average day-of-year estimates by +/- 60 days and in standard deviation by +/- 20 days. The ability of the satellite methods to retrieve SOS estimates was highest in northern latitudes and lowest in arid, tropical, and Mediterranean ecoregions. The ordinal rank of SOS methods varied geographically, as did the relationships between SOS estimates and the cryospheric/hydrologic metrics. Compared with ground observations, SOS estimates were more related to the first leaf and first flowers expanding phenological stages. We found no evidence for time trends in spring arrival from ground- or model-based data; using an ensemble estimate from two methods that were more closely related to ground observations than other methods, SOS trends could be detected for only 12% of North America and were divided between trends towards both earlier and later spring.
• Leeuwen, W. V., Drake, S., Hutchinson, C., Doorn, B., Tralli, D., Kaupp, V., Haithcoat, T., & Likholetov, V. (2005). Assimilating NASA data into a crop production estimation system: Risk management. Proceedings, 31st International Symposium on Remote Sensing of Environment, ISRSE 2005: Global Monitoring for Sustainability and Security.
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  Abstract: National Aeronautics and Space Administration (NASA) data and products are being assimilated into an existing decision support system (DSS) operated by the Production Estimates and Crop Assessment Division (PECAD) of the United States Department of Agriculture - Foreign Agricultural Service (USDA-FAS). The primary goal of PECAD is to disseminate global crop condition and agricultural production information for selected commodities. The perceived benefits of the assimilation of NASA data in PECAD's evolving DSS are: improved quality of crop assessment and production estimates and decisions, cost reduction and time savings. The main objectives of this research were to design a benchmarking strategy and develop a protocol that can help define DSS requirements and provide insight into the risks and mitigations that are critical factors for the adaptation and assimilation of enhancements to a DSS. Both qualitative and quantitative information were gathered to benchmark PECAD's present DSS using data from questionnaires and interviews. An interactive risk management tool (DDP-Defect Detection and Prevention) was used to 1) identify and formulate PECAD's DSS requirements, 2) estimate the impact of risks on the requirements, and 3) evaluate the effectiveness of mitigation factors that alleviate risks and enhance attainment of requirements. The DDP tool allowed us to evaluate mitigation scenarios that balanced and minimized the residual risk factors and achieved the best requirements attainment. Performance metrics were used to examine the effectiveness of the assimilation of NASA products into PECAD's DSS.
• van Leeuwen, W. J., Fang, H., S., L., W.J.D., v., S., E., & R., C. (2005). Biophysical characterization and management effects on semiarid rangeland observed from Landsat ETM+ data. IEEE Transactions on Geoscience and Remote Sensing.
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  ;Your Role: Field work logistics and measurements,data analysis, research discussions, paper editing;Full Citation: Fang, H, S. Liang, M. P. McClaran, W.J.D. van Leeuwen, S. Drake, S. E. Marsh, A. Thomson, R. C. Izaurralde, J. Norman, 2005. Biophysical characterization and management effects on semiarid rangeland observed from Landsat ETM+ data. IEEE Transactions on Geoscience and Remote Sensing 43(1):125-134. [Field work and data analysis];Collaborative with faculty member in unit: Yes;Collaborative with faculty member at UA: Yes;Other collaborative: Yes;Specify other collaborative: University of Maryland Geography Department;
• Kaupp, V., Hutchinson, C., Leeuwen, W. V., Drake, S., & Tuyahov, A. (2003). Assimilation of NASA Earth Science Results and Data in National Decision Support Systems. International Geoscience and Remote Sensing Symposium (IGARSS), 2, 1065-1070.
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  Abstract: NASA Earth Observing System (EOS) has generated science results derived from its unique observational data that are now becoming readily available in unprecedented quantity and quality. Though originally designed for specific scientific research, the EOS sensor suite offers unparalleled operational value for relevant applications. Similarly, the science results (e.g., models) that are developed from these observations have profound value for their ability to predict future conditions. Twelve priority National Applications owned by other federal agencies have been identified as potentially benefiting from newly available EOS capabilities. The Decision Making Systems (DMSs) of these National Applications incorporate at least one Decision Support System (DSS). The purpose of this work is to report a process for assimilating NASA geospatial data, mission products, and/or science results into these DSSs in partnership with their Federal owners.
• J.D., W., & Roujean, J. (2002). Land surface albedo from the synergistic use of polar (EPS) and geo-stationary (MSG) observing systems: An assessment of physical uncertainties. Remote Sensing of Environment, 81(2-3), 273-289.
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  Abstract: This investigation aims at quantifying the various sources of uncertainties in the derivation of albedo products from geo-stationary and polar orbiting optical systems with emphasis on the sensor and surface type (soil, snow, vegetation) spectral characteristics, atmospheric condition, and angular sampling issues. This research specifically takes into account the uncertainties in albedo that we can expect due to the synergistic use of the European Polar System (EPS)/Advanced Very High Resolution Radiometer (AVHRR) and Meteosat Second Generation (MSG)/Scanning Enhanced Visible and Infrared Imager (SEVIRI) instruments data. Satellite orbital models and a Scattering by Arbitrarily Inclined Leaves (SAIL)-hotspot canopy radiative transfer model were used to simulate synthetic bidirectional reflectance data sets for a broad range of vegetation canopies. The surface bidirectional reflectance distribution function (BRDF) database derived from the Polarization and Directionality of Earth Reflectance (POLDER) data was used in support of the simulations. Spectral atmospheric effects were generated using the 6S atmospheric radiative transfer code. Linear BRDF models, which are candidates for operational use, were inverted with the synthetic reflectance data sets of MSG, AVHRR and MSG-AVHRR combined. The BRDF parameters were then used to derive albedo by hemispherical angular integration. The retrieved model coefficients are discussed with regard to angular sampling and the implications these yield on spectral and broadband albedo determinations. It appears that the sampling problem is better conditioned thanks to the synergistic nature of MSG and AVHRR data. This synergy contributed to enhanced albedo retrievals, but can introduce larger uncertainties due to issues related to the differences in spectral bands and atmospheric state. Hence, the quality of the operational albedo products derived from one or more sources of satellite data will depend to a large extent on sensor characteristics (spectral, radiometric, and geometric), cloud detection, atmospheric correction, the angular distribution of the observations, and finally, the narrow-to-broadband albedo conversion. © 2002 Elsevier Science Inc. All rights reserved.
• J.D., W., Roujean, J., & Lacaze, R. (2001). Uncertainties in albedo derived from geostationary and polar orbiting satellite data. International Geoscience and Remote Sensing Symposium (IGARSS), 4, 1823-1825.
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  Abstract: This investigation evaluated the uncertainties in albedo derived from geostationary and polar orbiting optical sensors with emphasis on the spectral characteristics, angular sampling and atmospheric correction issues. Albedo simulations were achieved by using satellite orbital models and the SAIL code to produce synthetic bidirectional reflectance data sets for a range of vegetation canopies. Among the list of BRDF model candidates for operational use, two BRDF models were inverted with the simulated data of MSG, AVHRR and MSG-AVHRR combined. The values of retrieved model coefficients were used to derive spectral albedo. The synergistic use of data from different sensors raised issues related to the differences in spectral bands, atmospheric effects, and the assumption of the reciprocity principle.
• Miura, T., Huete, A. R., Didan, K., J.D., W., & Yoshioka, H. (2000). Assessment of the MODIS vegetation index compositing algorithm using quality assurance flags and sun/view angles. International Geoscience and Remote Sensing Symposium (IGARSS), 2, 545-547.
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  Abstract: The compositing algorithm of the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index (VI) is described. The algorithm uses a bidirectional reflectance distribution function (BRDF) model to produce nadir looking equivalent reflectance values if enough cloud free observations are available during a 16-day compositing period. Preliminary results show that the MODIS compositing algorithm has improved upon the conventional maximum value composite (MVC) technique. The view zenith angles of the composite pixels were found to be closer to nadir for the MODIS algorithm than for the MVC.
• Huete, A., Didan, K., Leeuwen, W. v., & Vermote, E. (1999). Global-scale analysis of vegetation indices for moderate resolution monitoring of terrestrial vegetation. Proceedings of SPIE - The International Society for Optical Engineering, 3868, 141-151.
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  Abstract: Vegetation indices have emerged as important tools in the seasonal and inter-annual monitoring of the Earth's vegetation. They are radiometric measures of the amount and condition of vegetation. In this study, the Sea-viewing Wide Field-of-View sensor (SeaWiFS) is used to investigate coarse resolution monitoring of vegetation with multiple indices. A 30-day series of SeaWiFS data, corrected for molecular scattering and absorption, was composited to cloud-free, single channel reflectance images. The normalized difference vegetation index (NDVI) and an optimized index, the enhanced vegetation index (EVI), were computed over various `continental' regions. The EVI had a normal distribution of values over the continental set of biomes while the NDVI was skewed toward higher values and saturated over forested regions. The NDVI resembled the skewed distributions found in the red band while the EVI resembled the normal distributions found in the NIR band. The EVI minimized smoke contamination over extensive portions of the tropics. As a result, major biome types within continental regions were discriminable in both the EVI imagery and histograms, whereas smoke and saturation considerably degraded the NDVI histogram structure preventing reliable discrimination of biome types.
• J.D., W., Huete, A. R., & Laing, T. W. (1999). MODIS vegetation index compositing approach: A prototype with AVHRR data. Remote Sensing of Environment, 69(3), 264-280.
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  Abstract: In this study, the 16-day MODIS (MODerate resolution Imaging Spectroradiometer) vegetation index (VI) compositing algorithm and product were described, evaluated, and compared with the current AVHRR (Advanced Very High Resolution Spectroradiometer) maximum value composite (MVC) approach. The MVC method selects the highest NDVI (normalized difference vegetation index) over a certain time interval. The MODIS VI compositing algorithm emphasizes a global and operational view angle standardization approach: a reflectance-based BRDF (Bidirectional Reflectance Distribution Function) model, succeeded by a back-up MVC algorithm that includes a view angle constraint. A year's worth of daily global AVHRR data was used to prototype the MODIS vegetation index compositing algorithm. The composite scenarios were evaluated with respect to: 1) temporal evolution of the VI for different continents and vegetation types, 2) spatial continuity of the VI, 3) quality flags related to data integrity, cloud cover, and composite method, and 4) view angle distribution of the composited data. On a continental scale, the composited NDVI values from the MODIS algorithm were as much as 30% lower than the mostly, off-nadir NDVI results based on the MVC criterion. The temporal evolution of the NDVI values derived with the MODIS algorithm were similar to the NDVI values derived from the MVC algorithm. A simple BRDF model was adequate to produce nadir equivalent reflectance values from which the NDVI could be computed. Application of the BRDF and 'back-up' components in the MODIS algorithm were dependent on geographic location and season, for example, the BRDF interpolation was most frequently applied in arid and semiarid regions, and during the dry season over humid climate vegetation types. Examples of a MODIS-like global NDVI map and associated quality flags were displayed using a pseudo color bit mapping scheme.
• J.D., W., Huete, A. R., Laing, T. W., & Didan, K. (1999). Vegetation change monitoring with spectral indices: The importance of view and sun angle standardized data. Proceedings of SPIE - The International Society for Optical Engineering, 3868, 445-454.
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  Abstract: Remotely sensed reflectance data are often acquired at variable view and solar geometric configurations. Vegetation change monitoring with the NDVI (Normalized Difference Vegetation Index) is sensitive to the effects of solar and view angle geometry. However, by using a BRDF (Bidirectional Reflectance Distribution Function) model, the view and sun angle variability in the NDVI can be standardized. If multi-sun angle data are not available, a second method allows us to extrapolate (nadir) satellite observations to a standard sun angle by using predetermined linear regression relationships between sun angle and ground-based nadir NDVI values for a range of vegetation types. Both methods were applied to one month of daily, atmospherically corrected, multi-angle SeaWiFS (Sea viewing Wide Field-of-view Spectroradiometer) land reflectance data, with promising results. The difference in NDVI due to a sun angle change from 20° to 70° can be up to 50%. The NDVI values for very dense vegetated and bare soil surface areas are less affected by changes in solar zenith angles. This research shows that the sun and view angle effects on the widely used spectral indices could be standardized to improve the accuracy of regional and global vegetation and crop monitoring efforts.
• van Leeuwen, W., Huete, A., & Laing, T. (1999). MODIS vegetation index compositing approach: A prototype with AVHRR data. REMOTE SENSING OF ENVIRONMENT, 69(3), 264-280.
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  In this study, the 16-day MODIS (MODerate resolution Imaging Spectroradiometer) vegetation index (VI) compositing algorithm and product were described evaluated, and compared with the current AVHRR (Advanced Very High Resolution Spectroradiometer) maximum value composite (MVC) approach. The MVC method selects the highest NDVI (normalized difference vegetation index) oner a certain time interval. The MODIS Til compositing algorithm emphasizes a global and operational view angle standardization approach: a reflectance-based BRDF (Bidirectional Reflectance Distribution Function) model, succeeded by a back-up MV algorithm that includes a view angle constraint. A year's worth of daily global AVHRR data tons used to prototype the MODIS vegetation index compositing algorithm. The composite scenarios were evaluated with respect to: 1) temporal evolution of the VI for different continents and vegetation types, 2) spatial continuity of the VI, 3) quality flags related to data integrity, cloud cover, and composite method and 4) view angle distribution of the composited data. On a continental scale, the composited NDVI values from the MODIS algorithm were as much as 30% lower than the mostly, off-nadir NDVI results based on the MVC criterion. The temporal evolution of the NDVI values derived with the MODIS algorithm were similar to the NDVI values derived from the MVC algorithm. A simple BRDF model was adequate to produce nadir equivalent reflectance values from which the NDVI could be computed. Application of the BRDF and "back-up" components in the MODIS algorithm were dependent on geographic location and season, for example, the BRDF interpolation was most frequently applied in arid and semiarid regions, and during the dry season over humid climate vegetation types. Examples of a MODIS-like global NDVI map and associated quality flags were displayed using a pseudo color bit mapping scheme. (C) Elsevier Science Inc., 1999.
• Huete, A. R., Kerola, D., Didan, K., J.D., W., & Ferreira, L. (1998). Terrestrial biosphere analysis of SeaWiFS data over the Amazon region with MODIS and GLI prototype vegetation indices. International Geoscience and Remote Sensing Symposium (IGARSS), 2, 785-787.
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  Abstract: A stream of multitemporal SeaWiFS (Sea-viewing Wide Field-of-view Sensor) data was extracted and analyzed over the Amazon region and surrounding land-community validate sites representing a wide range of vegetation conditions. The data successfully mapped the vegetation cover of the Amazon region. The various vegetation indices yielded very contrasting results in their ability to discriminate vegetation and land-use differences. These results lead to the conclusion that multiple indices are required to fully characterize the spatial/temporal variations of the Amazon region, 250 m pixel sizes.
• J.D., W., Huete, A. R., & Laing, T. W. (1998). Evaluation of the MODIS vegetation index compositing algorithm using SeaWiFS data. International Geoscience and Remote Sensing Symposium (IGARSS), 3, 1445-1447.
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  Abstract: Vegetation index data were composited in space and time to monitor vegetation changes in a spatial continuous fashion. Sixteen days of SeaWiFS (Sea-viewing Wide Field-of-view Sensor) data were composited to prototype and test the MODIS (MODerate resolution Imaging Spectroradiometer) algorithm for 'standardized' MODIS vegetation indices. It is shown that the MODIS composite algorithm is most reliable if accurate cloud information is available so that cloud affected pixel is rejected in the BRDF part of the MODIS algorithm.
• Justice, C. O., Vermote, E., R., J., Defries, R., Roy, D. P., Hall, D. K., Salomonson, V. V., Privette, J. L., Riggs, G., Strahler, A., Lucht, W., Myneni, R. B., Knyazikhin, Y., Running, S. W., Nemani, R. R., Wan, Z., Huete, A. R., Leeuwen, W. V., Wolfe, R. E., , Giglio, L., et al. (1998). The moderate resolution imaging spectroradiometer (MODIS): Land remote sensing for global change research. IEEE Transactions on Geoscience and Remote Sensing, 36(4), 1228-1249.
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  Abstract: The first Moderate Resolution Imaging Spectroradiometer (MODIS) instrument is planned for launch by NASA in 1998. This instrument will provide a new and improved capability for terrestrial satellite remote sensing aimed at meeting the needs of global change research. The MODIS standard products will provide new and improved tools for moderate resolution land surface monitoring. These higher order data products have been designed to remove the burden of certain common types of data processing from the user community and meet the more general needs of global-to-regional monitoring, modeling, and assessment. The near-daily coverage of moderate resolution data from MODIS, coupled with the planned increase in high-resolution sampling from Landsat 7, will provide a powerful combination of observations. The full potential of MODIS will be realized once a stable and well-calibrated time-series of multispectral data has been established. In this paper the proposed MODIS standard products for land applications are described along with the current plans for data quality assessment and product validation. © 1998 IEEE.
• Justice, C., Vermote, E., Townshend, J., Defries, R., Roy, D., Hall, D., Salomonson, V., Privette, J., Riggs, G., Strahler, A., Lucht, W., Myneni, R., Knyazikhin, Y., Running, S., Nemani, R., Wan, Z., Huete, A., van Leeuwen, W., Wolfe, R., , Giglio, L., et al. (1998). The Moderate Resolution Imaging Spectroradiometer (MODIS): Land remote sensing for global change research. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 36(4), 1228-1249.
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  The first Moderate Resolution Imaging Spectroradiometer (MODIS) instrument is planned for launch by NASA in 1998. This instrument will provide a new and improved capability for terrestrial satellite remote sensing aimed at meeting the needs of global change research, The MODIS standard products will provide new and improved tools for moderate resolution land surface monitoring, These higher order data products have been designed to remove the burden of certain common types of data processing from the user community and meet the more general needs of global-to-regional monitoring, modeling, and assessment. The near-daily coverage of moderate resolution data from MODIS, coupled with the planned increase in high-resolution sampling from Landsat 7, will provide a powerful combination of observations, The full potential of MODIS will be realized once a stable and well-calibrated time-series of multispectral data has been established. In this paper the proposed MODIS standard products for land applications are described along with the current plans for data quality assessment and product validation.
• Miura, T., Huete, A. R., Leeuwen, W. V., & Didan, K. (1998). Vegetation detection through smoke-filled AVIRIS images: An assessment using MODIS band passes. Journal of Geophysical Research D: Atmospheres, 103(D24), 32001-32011.
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  Abstract: Radiometrically calibrated, Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) images acquired during the Smoke, Clouds and Radiation in Brazil (SCAR-B) experiment were processed to simulate vegetation index (VI) imagery with the Moderate Resolution Imaging Spectroradiometer (MODIS) band passes. Data sets were extracted from tropical forested areas, burned fields, and shrub/grassland areas over both clear and variable smoke conditions with average aerosol optical thickness (AOT) values at 0.67 Jim of 0.14, 1.1, and 1.9, respectively. The atmospheric resistant VIs and various middle-infrared (MIR) derived VIs were then analyzed with respect to their ability to minimize atmospheric "smoke" contamination. The atmospheric resistant VIs utilized the blue band for correction of the red band, while the MIR-derived VIs used the MIR region (1.3 - 2.5 μm) as a substitute for the red band since it is relatively transparent to smoke, yet remains sensitive to green vegetation. The performance of these indices were assessed and compared with the normalized difference vegetation index (NDVI) and the soil-adjusted vegetation index (SAVI). Over the tropical forests the NDVI and SAVI had high relative errors over all smoke-filled atmospheric conditions (50-80% error), while the atmospheric resistant VIs resulted in a 50-80% relative error only over thick levels of smoke. Over optically thin levels (AOT at 0.67 μm < 1.1) they performed much better with a 20-40% relative error. The MIR-derived VIs, on the other hand, outperformed all other VIs over forested areas (≤ 5% error). However, over burned fields with minimal amounts of green biomass the MIR-derived VIs had the highest levels of error due to smoke (> 40%), while all other indices had errors below 20%. In the shrub/grassland site, the atmospheric resistant indices behaved similarly with the MIR-derived indices, with both less sensitive to smoke than the NDVI and SAVI. We conclude that the MIR indices, particularly with MODIS band 7 (2.13 μm), are useful in vegetation monitoring over forested areas during the burning season. However, they did not perform well in areas outside of forests such as burned areas and shrub/grassland. Copyright 1998 by the American Geophysical Union.
• Huete, A. R., Liu, H. Q., Batchily, K., & Leeuwen, W. V. (1997). A comparison of vegetation indices over a global set of TM images for EOS-MODIS. Remote Sensing of Environment, 59(3), 440-451.
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  Abstract: A set of Landsat Thematic Mapper images representing a wide range of vegetation conditions from the NASA Landsat Pathfinder, global land cover test site (GLCTS) initiative were processed to simulate the Moderate Resolution Imaging Spectroradiometer (MODIS), global vegetation index imagery at 250 m pixel size resolution. The sites included boreal forest, temperature coniferous forest, temperate deciduous forest, tropical rainforest, grassland, savanna, and desert biomes. Differences and similarities in sensitivity to vegetation conditions were compared among various spectral vegetation indices (VIs). All VIs showed a qualitative relationship to variations in vegetation. However, there were significant differences among the VIs over desert, grassland, and forested biomes. The normalized difference vegetation index (NDVI) was sensitive to and responded primarily to the highly absorbing red reflectance band, while other indices such as the soil and atmosphere resistant vegetation index (SARVI) were more responsive to variations in the near-infrared (NIR) band. As a result, we found the NDVI to mimic red reflectances and saturate over the forested sites while the SARVI, by contrast, did not saturate and followed variations in NIR reflectances. In the arid and semiarid biomes, the NDVI was much more sensitive to canopy background variations than the SARVI. Maximum differences among vegetation index behavior occurred over the evergreen needleleaf forest sites relative to the deciduous broadleaf forests and drier, grassland, and shrub sites. These differences appear to be useful in complementing the NDVI for improved monitoring of vegetation, with the NDVI sensitive to fraction of absorbed photosynthetic active radiation and the SARVI more sensitive to structural canopy parameters such as leaf area index and leaf morphology.
• Huete, A. R., Liu, H., & J.D., W. (1997). Use of vegetation indices in forested regions: Issues of linearity and saturation. International Geoscience and Remote Sensing Symposium (IGARSS), 4, 1966-1968.
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  Abstract: Numerous problems and difficulties have been reported with the use of vegetation indices in high biomass, forested regions. In this study we analyzed Landsat-5 Thematic Mapper (TM) scenes from various temperate and tropical forested biomes, representing needleleaf and broadleaf canopy structures in the Pacific Northwest (Oregon), Eastern U.S. (Harvard Forest), southern Chile, the Amazon, and Central America. The TM scenes were atmospherically corrected and reduced to MODIS surface reflectance data at 250 m pixel sizes. Various vegetation indices (VIs) were then computed including the normalized difference vegetation index (NDVI), simple ratio, soil-adjusted vegetation index (SAVI), enhanced vegetation index (EVI), and green vegetation index (GVI). The NDVI was also tested utilizing the green and middle-infrared (MIR) bands. All of the NDVIs were non-linear and were fairly saturated across the forested biomes. In contrast, the remaining indices remained sensitive to canopy structure variations over all of the forested biomes with minimal saturation problems. The high `penetrating' capability of the near:infrared band through forested canopies was the dominant factor in vegetation index sensitivity and performance. We found that indices with higher weighing coefficients in the `near-infrared' to be the best approach in extending vegetation index performance over forested and dense vegetated canopies.
• J.D., W., Laing, T. W., & Huete, A. R. (1997). Quality assurance of global vegetation index compositing algorithm using AVHRR data. International Geoscience and Remote Sensing Symposium (IGARSS), 1, 341-343.
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  Abstract: In this study the quality control aspects of the vegetation index produced by the MODIS (MODerate resolution Imaging Spectroradiometer) algorithm were evaluated and compared with the results of the currently used maximum value composite (MVC), which chooses the highest NDVI (normalized difference vegetation index) over a certain time interval. The composite scenarios were evaluated with respect to: 1) quality flags related to data integrity, cloud cover and composite method, 2) temporal evolution of the VI for different continents and vegetation cover types, and 3) accuracy of the standardization of reflectance values to standard view angles (nadir). On a continental scale the composited NDVI results from the MODIS algorithm were 1 to 24% lower than the off-nadir NDVI results based on the MVC criteria. A simple BRDF (Bidirectional Reflectance Distribution Function) model was adequate to produce nadir equivalent reflectance values from which the NDVI could be computed. The temporal evolution of the NDVI derived with the MODIS algorithm was similar to or smoother than the NDVI derived from the MVC algorithm. The composite method applied in the MODIS algorithm, was dependent on the global position and season, e.g. the BRDF interpolation was most frequently applied in arid and semi-arid regions and during the dry season over tropical rain forests. Examples of a global NDVI and quality flags were displayed using a pseudo color bit mapping scheme.
• Leeuwen, W. V., Huete, A. R., Walthall, C. L., Prince, S. D., Bégué, A., & Roujean, J. L. (1997). Deconvolution of remotely sensed spectral mixtures for retrieval of LAI, fAPAR and soil brightness. Journal of Hydrology, 188-189(1-4), 697-724.
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  Abstract: Linear mixture models have been used to invert spectral reflectances of targets at the Earth's surface into proportions of plant and soil components. However, operational use of mixture models has been limited by a lack of biophysical interpretation of the results. The main objectives of this study were (1) to relate the deconvolved components of mixture model with biophysical properties of vegetation and soil at the surface and (2) to apply the mixture model results to remotely sensed imagery. A radiative transfer model (SAIL: Scattering by Arbitrarily Inclined Leaves) was used to generate reflectance 'mixtures' from leaf and bare soil spectral measurements made at HAPEX-Sahel (Hydrological Atmospheric Pilot EXperiment) study sites. The SAIL model was used to create canopy reflectances and fractions of absorbed photosynthetically active radiation (fAPAR) for a range of mixed targets with varying leaf area index (LAI) and soils. A spectral mixture model was used to deconvolve the simulated reflectance data into component fractions, which were then calibrated to the SAIL-generated LAI, fAPAR and soil brightness. The calibrated relationships were validated with observational ground data (LAI, fAPAR and reflectance) measured at the HAPEX Sahel fallow bush/grassland, fallow grassland and millet sites. Both the vegetation and soil component fractions were found to be dependent upon soil background brightness, such that inclusion of the soil fraction information significantly improved the derivation of vegetation biophysical parameters. Soil brightness was also shown to be a useful parameter to infer soil properties. The deconvolution methodology was then applied to a nadir image of a HAPEX-Sahel site measured by the Advanced Solid State Array Spectroradiometer (ASAS). Site LAI and fAPAR were successfully estimated by combining the fractional estimates of vegetation and soils, obtained through deconvolution of the ASAS image, with the calibrated relationships between vegetation fraction, LAI and fAPAR, obtained from the SAIL data.
• Leeuwen, W. V., & Huete, A. R. (1996). Effects of standing litter on the biophysical interpretation of plant canopies with spectral indices. Remote Sensing of Environment, 55(2), 123-138.
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  Abstract: Litter is frequently present within vegetation canopies and thus contributes to the overall spectral response of a canopy. Consequently, litter will affect spectral indices designed to be sensitive to green vegetation, soil brightness or other features. The main objectives of the current research were to 1) evaluate the spectral properties of green vegetation and litter and 2) quantify the effect of standing litter on the performance of spectral indices. The SAIL (scattering by arbitrarily inclined leaves) model was used to generate canopy reflectance "mixtures" and to estimate fractions of absorbed photosynthetically active radiation (fAPAR) with varying leaf area index (LAI), soil background, combinations of vegetation component spectral properties, and one or two horizontal vegetation layers. Spectral measurements of different bare soils and mature green and senescent leaves of representative plant species at the HAPEX-Sahel (Hydrological Atmospheric Pilot Experiment) study sites were used as input. The normalized difference vegetation index (NDVI), the soil adjusted vegetation index (SAVI), and the modified NDVI (MNDVI) and mixture model spectral indices were selected to evaluate their performance with respect to standing litter and green vegetation mixtures. Spectral reflectance signatures of leaf litter varied significantly, but strongly resembled soil spectral characteristics. The biophysical parameters (LAI, fAPAR), derived from spectral vegetation indices, tended to be overestimated for randomly distributed, sparse green and litter vegetation cover mixtures, and underestimated for randomly distributed dense green and litter vegetation cover mixtures. All spectral indices and their biophysical interpretation were significantly altered by variability in 1) green leaf, leaf litter, and bark optical properties, 2) the amount and position of standing leaf litter, 3) leaf angle distribution, and 4) soil background. The NDVI response to these variables was inconsistent, and was the most affected by litter. The spectral mixture model indices, designed to be sensitive to litter, were shown to be promising for the identification of litter present among different ecosystems.
• Leeuwen, W. v., Huete, A. R., Jia, S., & Walthall, C. L. (1996). Comparison of vegetation index compositing scenarios: BRDF versus maximum VI approaches. International Geoscience and Remote Sensing Symposium (IGARSS), 3, 1423-1425.
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  Abstract: Satellite sensors, acquire bidirectional reflectance data under different solar illumination angles. These systems will capture the strong anisotropic properties that vary with relative amounts and types of vegetation and soil within each pixel. Therefore, some knowledge of the bidirectional reflectance distribution function (BRDF) is a requirement for successful interpretation of directional reflectance data and vegetation indices, and derivation of land-cover-specific biophysical parameters. The objectives of this research were: a) to parameterize empirical and semi-empirical BRDF models for different land cover types and MODIS spectral bands, b) utilize the BRDF models to correct off-nadir measurements to nadir-equivalent values for vegetation index (VI) compositing and biophysical interpretation and c) compare different vegetation index compositing scenarios.
• Franklin, J., Duncan, J., Huete, A. R., Leeuwen, W. v., Xiaowen, L. i., & Bégué, A. (1994). Radiative transfer in shrub savanna sites in Niger: preliminary results from HAPEX-Sahel. 1. Modelling surface reflectance using a geometric-optical approach. Agricultural and Forest Meteorology, 69(3-4), 223-245.
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  Abstract: To use optical remote sensing to monitor land surface-climate interactions over large areas, algorithms must be developed to relate multispectral measurements to key variables controlling the exchange of matter (water, carbon dioxide) and energy between the land surface and the atmosphere. The proportion of the ground covered by vegetation and the interception of photosynthetically active radiation (PAR) by vegetation are examples of two variables related to evapotranspiration and primary production, respectively. An areal-proportion model of the multispectral reflectance of shrub savanna, composed of scattered shrubs with a grass, forb or soil understory, predicted the reflectance of two 0.5 km2 sites as the area-weighted average of the shrub and understory or 'background' reflectances. Although the shaded crown and shaded background have darker reflectances, ignoring them in the area-weighted model is not serious when shrub cover is low and solar zenith angle is small. A submodel predicted the reflectance of the shrub crown as a function of the foliage reflectance and amount of plant material within the crown, and the background reflectance scattered or transmitted through canopy gaps (referred to as a soil-plant 'spectral interaction' term). One may be able to combine these two models to estimate both the fraction of vegetation cover and interception of PAR by green vegetation in a shrub savanna. © 1994.
• J.D., W., Huete, A. R., & Walthall, C. L. (1994). Biophysical interpretation of a spectral mixture model based on a radiative transfer model and observational data. International Geoscience and Remote Sensing Symposium (IGARSS), 3, 1458-1460.
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  Abstract: Linear spectral mixture models used to invert mixed spectral responses of a target into proportions of plant and soil components at the Earth's surface lack the biophysical interpretation of the results. The paper aims to relate the decomposed properties of the surface with the known biophysical properties of the surface. A radiative transfer model was used to generate mixture reflectances using the measured optical properties of pure components. The method is applied to subsets of a nadir image of the Advanced Solid State Array Spectroradiometer.
• Leeuwen, W. v., Huete, A. R., Duncan, J., & Franklin, J. (1994). Radiative transfer in shrub savanna sites in Niger: preliminary results from HAPEX-Sahel. 3. Optical dynamics and vegetation index sensitivity to biomass and plant cover. Agricultural and Forest Meteorology, 69(3-4), 267-288.
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  Abstract: A shrub savannah landscape in Niger was optically characterized utilizing blue, green, red and near-infrared wavelengths. Selected vegetation indices were evaluated for their performance and sensitivity to describe the complex Sahelian soil/vegetation canopies. Bidirectional reflectance factors (BRF) of plants and soils were measured at several view angles, and used as input to various vegetation indices. Both soil and vegetation targets had strong anisotropic reflectance properties, rendering all vegetation index (VI) responses to be a direct function of sun and view geometry. Soil background influences were shown to alter the response of most vegetation indices. N-space greenness had the smallest dynamic range in VI response, but the n-space brightness index provided additional useful information. The global environmental monitoring index (GEMI) showed a large VI dynamic range for bare soils, which was undesirable for a vegetation index. The view angle response of the normalized difference vegetation index (NDVI), atmosphere resistant vegetation index (ARVI) and soil atmosphere resistant vegetation index (SARVI) were asymmetric about nadir for multiple view angles, and were, except for the SARVI, altered seriously by soil moisture and/or soil brightness effects. The soil adjusted vegetation index (SAVI) was least affected by surface soil moisture and was symmetric about nadir for grass vegetation covers. Overall the SAVI, SARVI and the n-space vegetation index performed best under all adverse conditions and were recommended to monitor vegetation growth in the sparsely vegetated Sahelian zone. © 1994.
• Huete, A. R., Hua, G., Qi, J., Chehbouni, A., & Leeuwen, W. v. (1992). Normalization of multidirectional red and NIR reflectances with the SAVI. Remote Sensing of Environment, 41(2-3), 143-154.
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  Abstract: Directional reflectance measurements were made over a semidesert gramma (Bouteloua spp.) grassland at various times of the growing season. Azimuthal strings of view angle measurements from + 40° to - 40° were made for various solar zenith angles and soil moisture conditions. The sensitivity of the normalized difference vegetation index (NDVI) and the soil-adjusted vegetation index (SAVI) to these bidirectional measurements was assessed for purposes of improving remote temporal monitoring of vegetation activity. The NDVI response from the grassland canopy was strongly anisotropic about nadir view angles while the SAVI response was symmetric about nadir. This occurred for all sun angles, soil moisture condition, and grass densities. This enabled variations in SAVI-view angle response to be minimized with a cosine function. It is expected that this study will aid in improving the characterization of vegetation temporal activity from Landsat TM, SPOT, AVHRR, and the Earth Observing System MODIS sensor. © 1992.
• Huete, A. R., Qi, J., Chehbouni, A., Leeuwen, W., & Hua, G. (1991). Normalization of multidirectional red and NIR reflectances with the SAVI. Physical measurements and signatures in remote sensing. Proc. 5th international colloquium, Courchevel, 1991. Vol.1, 419-422.
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  Abstract: Directional reflectance measurements were made over a semi-desert gramma (Bouteloua spp.) grassland at various times of the growing season. View angle measurements from +40° to -40° were made at various solar zenith angles and soil moisture conditions. The sensitivity of the normalized difference vegetation index (NDVI) and the soil-adjusted vegetation index (SAVI) to bidirectional measurements was assessed for purposes of improving remote temporal monitoring of vegetation dynamics. -from Authors

Proceedings Publications

• Leeuwen, v., J.D., W., & salam, A. (2011). Remotely Sensed Vegetation Phenology of Sky Islands in the Madrean Archipelago.
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  ;Your Role: lead author/research;Full Citation: van Leeuwen, Willem J.D. and Abd salam El Vilaly. 2011. Remotely Sensed Vegetation Phenology of Sky Islands in the Madrean Archipelago. Proceedings of the 34th International Symposium on Remote Sensing of Environment, April 10 - 15, 2011, Sydney, Australia.;Electronic: Yes;Collaborative with graduate student: Yes;
• van Leeuwen, W. J., Leeuwan, v., J.D., W., & , J. K. (2009). An Assessment of Land Surface Phenology for Detecting Spatio-Temporal Landscape Change Patterns: Arizona and its National Parks.
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  ;Your Role: Lead research and wrote the paper;Full Citation: van Leeuwan, Willem J.D. and J. Kariyeva. 2009. An Assessment of Land Surface Phenology for Detecting Spatio-Temporal Landscape Change Patterns: Arizona and its National Parks. Proceedings of the 33rd International Symposium on Remote Sensing of Environment, May 4 - 8, 2009, Stresa, Lago Maggiore, Italy.;Electronic: Yes;Collaborative with graduate student: Yes;
• van Leeuwen, W. J., J., D., J.D., W., , G. C., & , S. M. (2007). Phenological characterization of a sky island: insights into vegetation patterns across space and time.
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  ;Your Role: Senior Research lead - co-author;Full Citation: Davison J., Willem J.D. van Leeuwen, G. Casady, S. Marsh, 2007. Phenological characterization of a sky island: insights into vegetation patterns across space and time. Proceeding of the 32nd International Symposium on Remote Sensing of Environment, San José, Costa Rica June 25 - 29, 2007.;Collaborative with graduate student: Yes;Collaborative with faculty member in unit: Yes;
• van Leeuwen, W. J., Orr, B. J., S., B. J., W.J.D., v., J.E., D., D., M., & D.G., N. (2007). Satellite-derived vegetation dynamics applied to post-fire vulnerability assessment in eastern Spain.
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  http://www.fire.uni-freiburg.de/sevilla-2007/contributions/doc/SESIONES_TEMATICAS/ST4/Orr_et_al_SPAIN_Alicante.pdf;Your Role: Data analysis - research experimental design;Full Citation: Orr, B.J. , S. Bautista, J.A.Alloza , W.J.D. van Leeuwen, G.M. Casady, J.E. Davison, L. Wittenberg , D. Malkinson, Y. Carmel, and D.G. Neary. “Satellite-derived vegetation dynamics applied to post-fire vulnerability assessment in eastern Spain”. Proceedings of the 4th International Wildland Fire Conference, Seville, Spain, May 13 - 17, 2007. http://www.fire.uni-freiburg.de/sevilla-2007/contributions/doc/SESIONES_TEMATICAS/ ST4/ Orr_et_al_SPAIN_Alicante.pdf (Accessed 10-30-2007);Electronic: Yes;Collaborative with graduate student: Yes;Collaborative with faculty member in unit: Yes;Other collaborative: Yes;Specify other collaborative: - Departamento de Ecología, Universidad de Alicante, Apdo. Correos, 99, 03080 Alicante, Spain- Fundación Centro de Estudios Ambientales del Mediterráneo (CEAM), C/Charles Darwin, 14, 46980 - Paterna (Valencia), Spain- Department of Geography & Environmental Studies, University of Haifa, Haifa 31905 Israel- Faculty of Civil and Environmental Engineering, The Technion - Israel Institute of Technology, Technion City, 32000 Israel- Rocky Mountain Research Station, USDA Forest Service, 2500 South Pine Knoll Drive Flagstaff, Arizona, 86001 USA;
• Tucker, C. J., Hall, F. G., Leeuwen, W. J., Xiao, X., Miura, T., Huemmrich, K. F., & Huete, A. (2006). Vegetation Index greenness global data set White Paper for NASA ESDR/CDR (April 2006). In Nasa Meeting.
• , T. H., , V. L., , V. K., , B. D., , D. T., Leeuwen, v., , S. D., & , C. H. (2005). Benchmark the performance of a decision support system.
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  ;Your Role: questionnaire development and research;Full Citation: T. Haithcoat, V. Likholetov, V. Kaupp, B. Doorn, D. Tralli, van Leeuwen, W., S. Drake, C. Hutchinson, 2005. Benchmark the performance of a decision support system. Proceedings of the 31st International Symposium on Remote Sensing of Environment, Global Monitoring for Sustainability and Security, June 20 - 24, 2005, Saint Petersburg, Russian Federation. ;Collaborative with faculty member in unit: Yes;Other collaborative: Yes;Specify other collaborative: University of MissouriJPL/NASAUSDA/FAS;
• Leeuwen, v., , S. D., , C. H., , B. D., , D. T., , V. K., , T. H., & , V. L. (2005). Assimilating NASA Data into a Crop Production Estimation System: Risk Management..
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  ;Your Role: Author and data collection and analysis;Full Citation: van Leeuwen, W., S. Drake, C. Hutchinson, B. Doorn, D. Tralli, V. Kaupp, T. Haithcoat, V. Likholetov, 2005. Assimilating NASA Data into a Crop Production Estimation System: Risk Management. C, Global Monitoring for Sustainability and Security, June 20 - 24, 2005, Saint Petersburg, Russian Federation. ;Collaborative with faculty member in unit: Yes;Other collaborative: Yes;Specify other collaborative: University of MissouriNASA/JPLUSDA.FAS;
• Marsh, S. E., McDonald, C. I., Baker, L. E., Leeuwen, W. J., Tuttle, D. G., Casady, G. M., & Orr, B. J. (2005). Phenology and trend indicators derived from spatially dynamic bi-weekly satellite imagery to support ecosystem monitoring. In Connecting mountain islands and desert seas: biodiversity and management of the Madrean Archipelago II. Proc. RMRS-P-36. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station: 206-211.
• Didan, K., Vermote, E., Leeuwen, W. J., & Huete, A. (1999). Global-scale analysis of vegetation indices for moderate resolution monitoring of terrestrial vegetation. In AGU.

Presentations

• Broxton, P. D., Van Leeuwen, W. J., & Biederman, J. (2019, Nov). A Satellite Data and Model Driven Decision Support Tool for monitoring snowpack, precipitation, and streamflow. American Water Resources Association Annual Water Resources Conference. Salt Lake City: SRP.
• Broxton, P. D., Van Leeuwen, W. J., & Biederman, J. (2019, Sept). Using multi-angle aerial photography from a UAV and Structure from Motion to improve snowpack monitoring in Northern Arizona. Arizona Hydrological Society Annual Symposium. Tucson: SRP.
• Broxton, P. D., Van Leeuwen, W. J., Biederman, J., & Hafield, K. (2019, Dec). The impact of forest cover on snowpack in the semi-arid southwestern US. AGU, San Francisco.
• Smith, W. K., Cinthia, N., Yan, D., Van Leeuwen, W. J., & et al, . (2019, Dec). Improved understanding of land cover and land use change impacts on ecosystem functioning using high spatiotemporal resolution satellite observations. AGU, San Francisco.
• Van Leeuwen, W. J. (2019, Sept). Advances in UAV Imagery for Management Decisions. 24th Annual Arizona Pecan Grower's Conference. Tucson Diamond Desert Casina: Arizona Pecan Grower's.
• vanderLeeuw, E., Van Leeuwen, W. J., Marsh, S. E., & Hartfield, K. (2019, Oct). Remotely Sensed Vegetation Cover and Species Information for Detecting Vegetative States on Ecological Sites – Preliminary Results. RISE symposium. Tucson: -.
• Van Leeuwen, W. J., Biederman, J., & Broxton, P. (2018, November). Snowpack Monitoring along Arizona’s Mogollon Rim. Colorado Basin River Forecast Center Stakeholder Meeting. Phoenix: SRP.
• Wang, X., Yang, D., Dannenberg, M., Jones, M., Kimball, J., Moore, D. J., Van Leeuwen, W. J., Didan, K., & Smith, W. K. (2018, 12). B54C-07 Comparisons of Global Land Surface Phenology Derived from Vegetation Greenness, Optical Depth, and Solar-induced Chlorophyll Fluorescence. American Geophysical Union. Washington DC.
• Van Leeuwen, W. J., Broxton, P., & Biederman, J. (2017, september). Leveraging LiDAR derived forest and snow information intosnow models to inform water resource management. 2nd Annual Airborne Snow Observatory WorkshopSRP.
• Van Leeuwen, W. J., Broxton, P., & Biederman, J. (2017, september). Snow monitoring in the Salt/Verde Watersheds. Arizona Hydrological SocietySRP.
• Van Leeuwen, W. J. (2016, october). Remotely Sensed Mapping and Monitoring of Ecosystem and Species Biodiversity Indicators. Geospatial Information Forum 3. Villahermosa, Tabasco, Mexico: Centro del Cambio Global y la Sustentabilidad en el Sureste, A. C..
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  Keynote address
• Van Leeuwen, W. J. (2015, September). REMOTE SENSING LAND SURFACE PHENOLOGY AND LAND COVER CHANGE. Geospatial Workshop, Centro del Cambio Global y la Sustentabilidad en el Sureste,. Villahermosa, Mexico.: Centro del Cambio Global y la Sustentabilidad en el Sureste.
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  van Leeuwen, Willem J.D, “REMOTE SENSING LAND SURFACE PHENOLOGY AND LAND COVER CHANGE.” 24 de septiembre 2015 at Geospatial Workshop, Centro del Cambio Global y la Sustentabilidad en el Sureste, Villahermosa, Mexico.
• Czyzowska, E., van Leeuwen, W. J., Marsh, S., Hirschboeck, K., & Wisniewski, W. (2013, ?). Alpine snow cover: monitoring challenges and possibilities. Davos Atmosphere and Cryosphere Assembly (DACA13). Davos Switzerland.
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  Czyzowska, E., van Leeuwen, W., Marsh, S., Hirschboeck, K., Wisniewski, W., 2013, Alpine snow cover &amp;amp;#8211; monitoring challenges and possibilities, Davos Atmosphere and Cryosphere Assembly (DACA13), Davos, Switzerland.
• Czyzowska, E., van Leeuwen, W. J., Marsh, S., Hirschboeck, K., & Wisniewski, W. (2013, Dec). Alpine snow cover: water resources in arid regions. AGU conference. San Francisco.
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  Czyzowska, E., van Leeuwen, W., Marsh, S., Hirschboeck, K., Wisniewski, W., 2013, Alpine snow cover &#8211; water resources in arid regions, AGU Fall Meeting, San Francisco, CA, USA.
• van Leeuwen, W. J. (2013, Jan, 2013). Trends and ENSO/AAO driven variability in productivity and phenology in South America: comparing NDVI-VIP and NDVI3g results. Vegetation Index and Phenology Workshop. Tucson: NASA.
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  van Leeuwen, Willem J.D. “Trends and ENSO/AAO driven variability in productivity and phenology in South America: comparing NDVI-VIP and NDVI3g results” Vegetation Index and Phenology Workshop - 30 Years of VI and Phenology Observations. Tucson, Arizona. Jan 24, 2013.
• van Leeuwen, W. J. (2012). Scaling workshop. NEON workshop. Boulder CO.
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  Internet/intranet
• van Leeuwen, W. J. (2012, 2012-06-01). A Hierarchical Landscape Inventory, Monitoring, Assessment and Modeling Framework: Impact of Scales on Land Use and Land Cover. NEON scaling workshop. Boulder.
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  ;Your Role: Created PPT and Presented;Invited: Yes;Type of Presentation: Academic Conference/Workshop;
• van Leeuwen, W. J. (2012, October). Land and Water Assessments: GIS and Remote Sensing tools. La Serena, Chile.
• van Leeuwen, W. J., & none, . (2012, 2012-10-01). Land and Water Assessments: GIS and Remote Sensing tools. IAI workshop. La Serena, Chile.
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  Land and Water Assessments: GIS and Remote Sensing tools. http://iaibr3.iai.int/twiki/bin/view/TIAdaptativeManagementWaterResources2012 Presented at La Serena, Chile on 10/11/2012.;Invited: Yes;Type of Presentation: Academic Conference/Workshop;
• van Leeuwen, W. J., Czyzowska, E. H., J., W., Marsh, S. E., Hirschboeck, K. K., & Wisniewski, W. T. (2012, 2012-12-01). Improved Remotely Sensed Snow Cover Estimation Using an Artificial Neural Network. AGU. San Francsico.
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  Elzbieta H. Czyzowska,Willem J. D. van Leeuwen, Stuart E. Marsh, Katherine K. Hirschboeck, Wit T. Wisniewski, Improved Remotely Sensed Snow Cover Estimation Using an Artificial Neural Network AGU Conference, Dec San Francisco.;Your Role: Advise and editing;Interdisciplinary: Yes;Collaborative with undergraduate student: Yes;Collaborative with graduate student: Yes;Collaborative with faculty member in unit: Yes;Collaborative with faculty member at UA: Yes;Type of Presentation: postyer;
• van Leeuwen, W. J., Landau, K. I., J.D., W., Willott, E., Morin, C. W., & Comrie, A. C. (2012, 2012-02-01). Land cover and climate impacts on the spatial distribution of mosquito abundance in Tucson. AAG. New York.
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  Katheryn I. Landau and Willem J.D. van Leeuwen, Elizabeth Willott, Cory W. Morin, Andrew C. Comrie, Land cover and climate impacts on the spatial distribution of mosquito abundance in Tucson, Arizona AAG Annual Meeting New York, Feb 24-28, 2012.;Your Role: Advise and research design;Interdisciplinary: Yes;Collaborative with graduate student: Yes;Collaborative with faculty member in unit: Yes;Collaborative with faculty member at UA: Yes;Type of Presentation: Academic Conference;
• van Leeuwen, W. J., Vilaly, M. E., , K. D., J.D., W., & Crimmins, M. A. (2012, 2012-12-01). A Remote Sensing Approach to Drought Monitoring for Range management at the Hopi Tribe and Navajo Nation. AGU. San Francisco.
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  M.A. El Vilaly, K. Didan, Willem J.D. van Leeuwen Stuart E. Marsh, M A. Crimmins 2012. A Remote Sensing Approach to Drought Monitoring for Range management at the Hopi Tribe and Navajo Nation. AGU Conference, Dec San Francisco.;Your Role: Advise and editing;Interdisciplinary: Yes;Collaborative with graduate student: Yes;Collaborative with faculty member in unit: Yes;Collaborative with faculty member at UA: Yes;Type of Presentation: poster;
• Leeuwen, v., J.D., W., & salam, A. (2011, 2011-04-01). Vegetation Phenology of Sky Islands in the Madrean Archipelago. ISRSE. Sydney.
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  van Leeuwen, Willem J.D. and Abd salam El Vilaly. 2011. Remotely SensedVegetation Phenology of Sky Islands in the Madrean Archipelago. Proceedings of the34th International Symposium on Remote Sensing of Environment, April 10 - 15, 2011, Sydney, Australia.;Submitted: Yes;Collaborative with graduate student: Yes;Type of Presentation: Academic Conference;
• van Leeuwen, W. J. (2011, 2011-10-01). Innovation in remote sensing: multi-scale applications. emote Sensing Workshop. Santiago, Chile.
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  Innovation in remote sensing: multi-scale applications - Keynote. 2011 van Leeuwen, Willem J.D. "Innovation in remote sensing: multi-scale applications". Keynote: Remote Sensing Workshop "Remote Sensing and Environmental Monitoring: Productivity and Carbon Capture on Natural Ecosystems". Santiago, Chile October 25-28, 2011.;Invited: Yes;Type of Presentation: Invited/Plenary Speaker;
• van Leeuwen, W. J. (2011, 2011-10-01). Phenology and climate. Catolica University, Santiago, Chile.
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  van Leeuwen, Willem J.D. "Phenology and climate". Catolica University, Santiago, Chile October 27, 2011.;Invited: Yes;Type of Presentation: Invited/Plenary Speaker;
• van Leeuwen, W. J., Abdsalam, M., Leeuwen, W. v., & Crimmins, . (2011, 2011-10-01). Remotely Sensed Vegetation Dynamics of Sky Islands in the Madrean Archipelago. PHENOLOGY RESEARCH AND OBSERVATIONS OF SOUTHWEST ECOSYSTEMS SYMPOSIUM (PROSE)U.S.A. National Phenology Network (USA-NPN) & Southwest U.S. Region, American Society of Photogrammetry & Remote Sensing (SW-ASPRS). Tucson.
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  Mohamed Abdsalam El Vilaly et al.: A Remote Sensing Approach to Drought monitoring to Inform Range Management at the Hopi Tribe and Navajo Nation.PHENOLOGY RESEARCH AND OBSERVATIONS OF SOUTHWEST ECOSYSTEMS SYMPOSIUM (PROSE)U.S.A. National Phenology Network (USA-NPN) & Southwest U.S. Region, American Society of Photogrammetry & Remote Sensing (SW-ASPRS)28 October 2011. University of Arizona, Tucson, AZ, USA.;Your Role: Advise, editing;Submitted: Yes;Collaborative with graduate student: Yes;Collaborative with faculty member in unit: Yes;Type of Presentation: Academic Conference;
• van Leeuwen, W. J., Landau, K., W.J.D., v., & K.A., H. (2011, 2011-04-01). Classification of Vegetation Lifeforms Using LIDAR and Multispectral Data to Identify Urban Mosquito Habitat. AAG. Seattle.
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  Landau, Katy, W.J.D. van Leeuwen, E. Willott, K.A. Hartfield, 2011. Classification of Vegetation Lifeforms Using LIDAR and Multispectral Data to Identify Urban Mosquito Habitat. AAG Annual meeting. Seattle WA, 12-16 April 2011.;Your Role: Providing, funding, advise, and scientific input;Submitted: Yes;Collaborative with graduate student: Yes;Collaborative with faculty member in unit: Yes;Collaborative with faculty member at UA: Yes;Type of Presentation: Academic Conference;
• van Leeuwen, W. J., Raul, J., J.D., W., , C. A., , G. C., & Vilaly, M. E. (2011, 2011-10-01). Effects of Land Use Dynamics and Environmental Trends on the Timing and Magnitude of Phenological Stages in Arid Agro-Ecosystems of Northwestern Mexico. PHENOLOGY RESEARCH AND OBSERVATIONS OF SOUTHWEST ECOSYSTEMS SYMPOSIUM (PROSE)U.S.A. National Phenology Network (USA-NPN) & Southwest U.S. Region, American Society of Photogrammetry & Remote Sensing (SW-ASPRS). Tucson.
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  Jose Raul Romo Leon et al.: Effects of Land Use Dynamics and Environmental Trends on the Timing and Magnitude of Phenological Stages in Arid Agro-Ecosystems of Northwestern Mexico,PHENOLOGY RESEARCH AND OBSERVATIONS OF SOUTHWEST ECOSYSTEMS SYMPOSIUM (PROSE)U.S.A. National Phenology Network (USA-NPN) & Southwest U.S. Region, American Society of Photogrammetry & Remote Sensing (SW-ASPRS)28 October 2011. University of Arizona, Tucson, AZ, USA. Observations of Southwest Ecosystems (October 1st) and 7th RISE Symposium - Research Insights in Semiarid Ecosystems (October 2nd), Tucson, Arizona, October 1-2, 2010.;Submitted: Yes;Collaborative with graduate student: Yes;Other collaborative: Yes;Specify other collaborative: USGS collaboration;Type of Presentation: Academic Conference;
• van Leeuwen, W. J., & Leeuwen, W. v. (2010, 2010-09-01). Remotely Sensed Vegetation Dynamics of Sky Islands in the Madrean Archipelago. Climate Change Adaptation in the Arid Southwest: A Workshop for Land and Resource Management,. Tucson.
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  van Leeuwen Willem J.D., “Remotely Sensed Vegetation Dynamics of Sky Islands in the Madrean Archipelago” Presented at: Climate Change Adaptation in the Arid Southwest: A Workshop for Land and Resource Management, September 20-21, 2010, Tucson, Arizona.;Submitted: Yes;Other collaborative: Yes;Specify other collaborative: NA;Type of Presentation: Academic Conference/Workshop;
• van Leeuwen, W. J., Kariyeva, J., & J.D., W. (2010, 2010-04-01). Phenological Response to Changes in Land Use Practices and Climate Variability in Central Asia. AAG. Washington DC.
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  Jahan Kariyeva and Willem J.D. van Leeuwen. 2010. Phenological Response to Changes in Land Use Practices and Climate Variability in Central Asia, AAG meetings Washington DC, April 2010.;Your Role: Providing, funding, advise, and scientific input;Submitted: Yes;Collaborative with graduate student: Yes;Type of Presentation: Academic Conference;
• van Leeuwen, W. J., Landau, K., Hartfield, K., & J.D., W. (2010, 2010-10-01). Identifying Vegetation Lifeforms in the Santa Catalina Mountains Using Lidar and Multispectral Data: Preliminary Results. ASPRS. Tucson.
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  Katheryn Landau, Kyle Hartfield, Willem J.D. van Leeuwen “Identifying Vegetation Lifeforms in the Santa Catalina Mountains Using Lidar and Multispectral Data: Preliminary Results”. Presented at: 4th Annual Phenology Research and Observations of Southwest Ecosystems Symposium (PROSE); U.S.A. National Phenology Network (NPN) & Southwest U.S. Region, American Society of Photogrammetry & Remote Sensing (ASPRS), University of Arizona, Tucson, AZ. October 1st, 2010.;Your Role: Lead researcher;Submitted: Yes;Interdisciplinary: Yes;Collaborative with graduate student: Yes;Type of Presentation: Academic Conference;
• van Leeuwen, W. J., Raul, J., J.D., W., , C. A., , G. C., & Vilaly, M. E. (2010, 2010-10-01). Remote Sensing Shows Restoration Treatments Affect Post-Fire Responses of Forests in the Jemez Mountains, New Mexico. ASPRS RISE. Tucson.
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  Jose Raul Romo Leon, Willem J.D. van Leeuwen, C.A. Allen, G. Casady and M.A El Vilaly Remote Sensing Shows Restoration Treatments Affect Post-Fire Responses of Forests in the Jemez Mountains, New Mexico. Presented at the 4th annual PROSE symposium- Phenology Research and Observations of Southwest Ecosystems (October 1st) and 7th RISE Symposium - Research Insights in Semiarid Ecosystems (October 2nd), Tucson, Arizona, October 1-2, 2010.;Collaborative with graduate student: Yes;Other collaborative: Yes;Specify other collaborative: USGS collaboration;Type of Presentation: Academic Conference;
• van Leeuwen, W. J. (2009, 2009-10-01). Remotely Sensed Sky Island Phenology: Impacts of Fire and Climate Change. Phenology Research and Observations of Southwest Ecosystems Symposium (PROSE). TUcson.
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  van Leeuwen, Willem J.D., “Remotely Sensed Sky Island Phenology: Impacts of Fire and Climate Change” At: Phenology Research and Observations of Southwest Ecosystems Symposium (PROSE); U.S.A. National Phenology Network (NPN) & Southwest U.S. Region, American Society of Photogrammetry & Remote Sensing (ASPRS), University of Arizona, Tucson, AZ. October 2nd, 2009.;Invited: Yes;Type of Presentation: Invited/Plenary Speaker;
• van Leeuwen, W. J., & , J. K. (2009, 2009-05-01). An Assessment of Land Surface Phenology for Detecting Spatio-Temporal Landscape Change Patterns: Arizona and its National Parks. 33rd International Symposium on Remote Sensing of Environment. Stresa, Lago Maggiore, Italy..
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  van Leeuwen, Willem J.D. and J. Kariyeva. 2009. An Assessment of Land Surface Phenology for Detecting Spatio-Temporal Landscape Change Patterns: Arizona and its National Parks. 33rd International Symposium on Remote Sensing of Environment, May 4 - 8, 2009, Stresa, Lago Maggiore, Italy.;Submitted: Yes;Collaborative with graduate student: Yes;Type of Presentation: Academic Conference;
• van Leeuwen, W. J., Czyzowska, E. H., Hirschboeck, K. K., J.D., W., Marsh, S. E., & Wisniewski, W. T. (2009, 2009-12-01). Fractional Snow Cover Estimation in Complex Alpine-Forested Environments Using Ikonos/QuickBird, Landsat and MODIS. AGu. San Francisco.
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  Elzbieta H. Czyzowska, Katherine K. Hirschboeck,Willem J.D. van Leeuwen, Stuart E. Marsh, Wit T. Wisniewski “Fractional Snow Cover Estimation in Complex Alpine-Forested Environments Using Ikonos/QuickBird, Landsat and MODIS” AGU Fall Meetings, San Francisco, CA, Dec. 2009.;Your Role: Advised on several remote sensing science aspects;Submitted: Yes;Interdisciplinary: Yes;Collaborative with graduate student: Yes;Collaborative with faculty member in unit: Yes;Collaborative with faculty member at UA: Yes;Type of Presentation: Academic Conference;
• van Leeuwen, W. J., Davison, J. E., Breshears, D. D., J.D., W., & Casady, G. M. (2009, 2009-08-01). Remotely sensed vegetation dynamics along an elevation gradient: Interactive effects of woody plant cover.. 94th Symposium of the Ecological Society of America. Albuquerque.
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  Poster presentation - Jennifer E. Davison, David D. Breshears, Willem J.D. Van Leeuwen, Grant M. Casady, Remotely sensed vegetation dynamics along an elevation gradient: Interactive effects of woody plant cover. 94th Symposium of the Ecological Society of America, Albuquerque NM, USA, August 2-7, 2009.;Your Role: Provided data, advise and input to research along the way;Submitted: Yes;Collaborative with graduate student: Yes;Collaborative with faculty member in unit: Yes;Collaborative with faculty member at UA: Yes;Type of Presentation: Academic Conference;
• van Leeuwen, W. J., Kariyeva, J., & Brown., J. F. (2009, 2009-03-01). Characterization of Land Surface Phenology for Selected Rangeland Sites and Latitudinal Gradients. AAG. Las Vegas.
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  Willem J.D. van Leeuwen, Jahan Kariyeva, and Jesslyn F. Brown. Multi-Sensor “Characterization of Land Surface Phenology for Selected Rangeland Sites and Latitudinal Gradients” Annual Meeting Association of American Geographers (AAG), Las Vegas NV, USA, March 22-27, 2009.;Submitted: Yes;Interdisciplinary: Yes;Collaborative with graduate student: Yes;Other collaborative: Yes;Specify other collaborative: USGS collaboration;Type of Presentation: Academic Conference;
• van Leeuwen, W. J., Kariyeva, J., & J.D., W. (2009, 2009-03-01). Land Surface Phenological Responses to Changes in Land and Water Use, Climate and Socio-Economics: Central Asia before and after the USSR Collapse. AAG. Las Vegas.
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  3rd price awarded by the Remote sensing specialty group at the AAG meeting for best student paper submitted and presented:Jahan Kariyeva and Willem J.D. van Leeuwen. 2009. “Land Surface Phenological Responses to Changes in Land and Water Use, Climate and Socio-Economics: Central Asia before and after the USSR Collapse”. Annual Meeting Association of American Geographers (AAG), Las Vegas NV, USA, March 22-27, 2009.;Your Role: Providing, funding, advise, and scientific input;Submitted: Yes;Refereed: Yes;Collaborative with graduate student: Yes;Type of Presentation: Academic Conference;
• van Leeuwen, W. J., Kariyeva, J., & J.D., W. (2009, 2009-09-01). Land surface phenology dynamics in Central Asia: impacts of land use change and climate variability. NASA-Land Cover Land Use Change (LCLUC) Science Team Meeting and GOFC-GOLD/NERIN, NEESPI, and MAIRS workshop on monitoring land cover, land use, and fire in agricultural and arid regions of Northern Eurasia. Almaty, Kazakhstan.
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  Poster presentation - Jahan Kariyeva and Willem J.D. van Leeuwen, 2009. “Land surface phenology dynamics in Central Asia: impacts of land use change and climate variability”. NASA-Land Cover Land Use Change (LCLUC) Science Team Meeting and GOFC-GOLD/NERIN, NEESPI, and MAIRS workshop on monitoring land cover, land use, and fire in agricultural and arid regions of Northern Eurasia. Almaty, Kazakhstan, September 15-21, 2009. ;Your Role: helped with poster and research;Submitted: Yes;Collaborative with graduate student: Yes;Type of Presentation: Academic Conference/Workshop;
• van Leeuwen, W. J., Landau, K., J.D., W., Crimmins, T., Crimmins, M., & Bertelsen, D. (2009, 2009-10-01). Monitoring Species Flowering Observations and Remotely Sensed Vegetation Dynamics in the Santa Catalina Mountains. Phenology Research and Observations of Southwest Ecosystems Symposium (PROSE). Tucson.
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  Poster presentation - Katheryn Landau, Willem J.D. van Leeuwen, Theresa Crimmins, Mike Crimmins, David Bertelsen. “Monitoring Species Flowering Observations and Remotely Sensed Vegetation Dynamics in the Santa Catalina Mountains”. Phenology Research and Observations of Southwest Ecosystems Symposium (PROSE); U.S.A. National Phenology Network (NPN) & Southwest U.S. Region, American Society of Photogrammetry & Remote Sensing (ASPRS), University of Arizona, Tucson, AZ. October 2nd, 2009.;Your Role: Lead research project, Helped with abstract, poster content, research and writing.;Submitted: Yes;Interdisciplinary: Yes;Collaborative with undergraduate student: Yes;Collaborative with faculty member in unit: Yes;Collaborative with faculty member at UA: Yes;Other collaborative: Yes;Specify other collaborative: Dave Bertelsen is a citizen scientist collecting phenological data on Fingerrock trail Catalina Mountains;Type of Presentation: Professional Organization;
• van Leeuwen, W. J., M.L., V., , R. R., & J.D., W. (2009, 2009-03-01). National Park Service Landscape Dynamics Monitoring: Assessing Seventy Years of Change at Tumacácori National Historical Park. Biennial George Wright Society Conference on Parks, Protected Areas, and Cultural Sites,. Portland, OR, USA.
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  Poster presentation - Villareal M.L., R. Romo, Willem J.D. van Leeuwen, National Park Service Landscape Dynamics Monitoring: Assessing Seventy Years of Change at Tumacácori National Historical Park. Biennial George Wright Society Conference on Parks, Protected Areas, and Cultural Sites, Portland, OR, USA. March 2-6, 2009.;Your Role: Help development of new methodology and supervised project;Submitted: Yes;Type of Presentation: Professional Organization;
• van Leeuwen, W. J., Olsson, A. D., Crimmins, M. A., Orr, B. J., Marsh, S. E., & J.D., W. (2009, 2009-08-01). Coupling citizen science with precipitation and phenology monitoring and modeling to support invasive species management. Ecological Society of America. Albuquerque.
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  Aaryn D. Olsson, Michael A. Crimmins, Barron J. Orr, Start E. Marsh and Willem J.D. van Leeuwen. 2009. “Coupling citizen science with precipitation and phenology monitoring and modeling to support invasive species management”. 94th Symposium of the Ecological Society of America, Albuquerque NM, USA, August 2-7, 2009.;Your Role: Helped with buffelgrass mapping and monitoring method development;Submitted: Yes;Interdisciplinary: Yes;Collaborative with graduate student: Yes;Collaborative with faculty member in unit: Yes;Collaborative with faculty member at UA: Yes;Type of Presentation: Academic Conference;
• van Leeuwen, W. J., Yingxin, G. u., Brown, J. F., J.D., W., Reed, B. C., & Miura., T. (2009, 2009-03-01). Phenologic classification of the United States: A framework for vegetation drought monitoring. AAG. Las Vegas.
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  Yingxin Gu, Jesslyn F. Brown, Willem J.D. van Leeuwen, Bradley C. Reed, Tomoaki Miura. 2009. “Phenologic classification of the United States: A framework for vegetation drought monitoring”. Annual Meeting Association of American Geographers (AAG), Las Vegas NV, USA, March 22-27, 2009.;Your Role: Contributed to research idea and helped with abstract;Submitted: Yes;Interdisciplinary: Yes;Other collaborative: Yes;Specify other collaborative: USGS and University of Hawaii collaborators;Type of Presentation: Academic Conference;
• Kariyeva, J., & van, L. (2008, 2008-04-01). Remotely Sensed Phenology Data as a Tool to Examine Landscape Response and Vulnerability to Disturbance Events. AAG. Boston.
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  Kariyeva, J., van Leeuwen, Willem J.D., “Remotely Sensed Phenology Data as a Tool to Examine Landscape Response and Vulnerability to Disturbance Events”, oral presentation at the Association of American Geographers (AAG), Boston, Massachusetts, April 15-19, 2008.;Your Role: Chairing and guiding research of Jahan Kariyeva;Submitted: Yes;Collaborative with graduate student: Yes;Type of Presentation: Academic Conference;
• Leeuwen, v., & J.D., W. (2008, 2008-03-01). A Preliminary Assessment of Remotely Sensed Vegetation Phenology for Detecting Semiarid Spatio-Temporal Landscape Change Patterns. 52nd Annual Arizona-Nevada Academy of Sciences (ANAS) Meeting and Southwest US Region, American Society of Photogrammetry & Remote Sensing (ASPRS). Phoenix.
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  Kariyeva, J., van Leeuwen, Willem J.D.,“A Preliminary Assessment of Remotely Sensed Vegetation Phenology for Detecting Semiarid Spatio-Temporal Landscape Change Patterns”, 52nd Annual Arizona-Nevada Academy of Sciences (ANAS) Meeting and Southwest US Region, American Society of Photogrammetry & Remote Sensing (ASPRS), Phoenix, Arizona. March 29, 2008.;Your Role: Chairing and guiding research of graduate student Jahan Kariyeva;Submitted: Yes;Collaborative with graduate student: Yes;Type of Presentation: Professional Organization;
• Leeuwen, v., J.D., W., Kariyeva, ., Leon, R., & R., J. (2008, 2008-10-01). Phenology of National Parks in Arizona: a Multi-Sensor Approach to Land Surface Characterization and Assessments. U.S.A. National Phenology Network (NPN) & Southwest U.S. Region, American Society of Photogrammetry and Remote Sensing (ASPRS). Tucson.
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  van Leeuwen, Willem J.D., Kariyeva, J., Romo Leon, J. R., “Phenology of National Parks in Arizona: a Multi-Sensor Approach to Land Surface Characterization and Assessments”, National Phenology Network (NPN) and Southwest US Region, American Society of Photogrammetry & Remote Sensing (ASPRS), Tucson, Arizona, October 10, 2008.;Submitted: Yes;Collaborative with graduate student: Yes;Type of Presentation: Academic Conference;
• Leeuwen, v., J.D., W., Kariyeva, ., Leon, R., & R., J. (2008, 2009-04-01). Phenological Characterization of National Parks in Arizona Using Multiple Resolution Time Series of Spectral Vegetation Index Data. AAG. Boston.
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  van Leeuwen, Willem J.D., Kariyeva, J., Romo Leon, J. R.“Phenological Characterization of National Parks in Arizona Using Multiple Resolution Time Series of Spectral Vegetation Index Data”, Association of American Geographers (AAG), Boston, Massachusetts, April 15-19, 2008.;Submitted: Yes;Collaborative with graduate student: Yes;Type of Presentation: Academic Conference;
• van Leeuwen, W. J., & , S. M. (2008, 2008-02-01). Rangeland Decision Support. NIDIS Knowledge Assessment Workshop: Contributions of Satellite Remote Sensing to Drought Monitoring. David Skaggs Research Center, NOAA, Boulder, CO..
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  http://www.drought.gov/portal/server.pt/community/drought_gov/202/remote_sensing_workshop_-_presentations;Submitted: Yes;Invited: Yes;Interdisciplinary: Yes;Collaborative with faculty member in unit: Yes;Type of Presentation: Invited/Plenary Speaker;
• van Leeuwen, W. J., Casady, G., Drake, S., Herrmann, S., Kariyeva, J., J.D., W., & Marsh, S. (2008, 2008-12-01). Methodologies: Overview and Needs. Expert Meeting on Defining a Roadmap for the Development of a New World Atlas on Desertification (WAD). Ispra, Italy.
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  Hutchinson, C., Grant Casady, Sam Drake, Stefanie Herrmann, Jahan Kariyeva, Willem J.D. van Leeuwen, Stuart Marsh, “Methodologies: Overview and Needs”. Expert Meeting on Defining a Roadmap for the Development of a New World Atlas on Desertification (WAD). Ispra, Italy, December 3-5, 2008.;Your Role: Provided input to talk and slides with regard to the topic of desertification. Presented by C. Hutchinson;Invited: Yes;Collaborative with graduate student: Yes;Collaborative with faculty member in unit: Yes;Type of Presentation: Invited/Plenary Speaker;
• van Leeuwen, W. J., Davison, J. E., & D.D.Breshears, W. (2008, 2008-01-01). Exploration of vegetation of vegetation response to wildfire across a gradient of woody cover. Association for Fire Ecology Regional Conference. Tucson.
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  Davison, J.E., D.D.Breshears, Willem J. D. van Leeuwen, “Exploration of vegetation response to wildfire across a gradient of woody cover” Association for Fire Ecology Regional Conference, Tucson, AZ, January 2008. ;Submitted: Yes;Collaborative with graduate student: Yes;Collaborative with faculty member at UA: Yes;Type of Presentation: Professional Organization;
• van Leeuwen, W. J., Didan, K., J.D., W., Miura, T., Friedl, M., Zhang, X., Czapla-Myers, J., Jenkerson, C. B., & Maiersperger, T. K. (2008, 2008-12-01). Vegetation Phenology and Vegetation Index Products from Multiple Long Term Satellite Data Records. AGU. San Francisco.
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  Kamel Didan, Willem J.D. van Leeuwen, Tomoaki Miura, Mark Friedl, Xiaoyang Zhang, Jeff Czapla-Myers, Calli B. Jenkerson, Thomas K. Maiersperger, “Vegetation Phenology and Vegetation Index Products from Multiple Long Term Satellite Data Records” AGU meetings, San Francisco, CA, Dec 15-19, 2008.;Your Role: Co-PI on this project sponsored by NASA; Contributed material to the presentation.;Submitted: Yes;Collaborative with faculty member at UA: Yes;Other collaborative: Yes;Specify other collaborative: Working with USGS and NOAA, Universities of Boston, Hawaii, ;Type of Presentation: Academic Conference;
• van Leeuwen, W. J., Hutchinson, C., Drake, S., Doorn, B., Kaupp, V., Haithcoat, T., Likholetov, V., Sheffner, E., & Tralli, D. (2008, 2008-12-01). Benchmarking Collaborative Inter- and Intra-agency Enhancements to a Decision Support System for Global Crop Production Assessments. AGU. San Francisco, USA..
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  van Leeuwen, Willem J.D., Chuck Hutchinson, Sam Drake, Brad Doorn, Verne Kaupp, Tim Haithcoat, Vladislav Likholetov, Ed Sheffner, Dave Tralli, “Benchmarking Collaborative Inter- and Intra-agency Enhancements to a Decision Support System for Global Crop Production Assessments”, AGU meetings, San Francisco, CA, Dec 15-19, 2008.;Your Role: Dr C. Hutchinson was invited, but I was first author because I did most of the research and prepared the PPT.;Invited: Yes;Interdisciplinary: Yes;Collaborative with faculty member in unit: Yes;Other collaborative: Yes;Specify other collaborative: collaboration with NASA, JPL, University of Missouri, USDA/FAS;Type of Presentation: Invited/Plenary Speaker;
• van Leeuwen, W. J., J.D., W., & , R. R. (2008, 2008-07-01). Protocol Development of Landscape Dynamics Monitoring for Sonoran Desert Network National Parks. National Park Service Sonoran Desert Network I&M Program Review. Tucson.
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  Villarreal, M.L., Willem J.D. van Leeuwen, and R. Romo. “Protocol Development of Landscape Dynamics Monitoring for Sonoran Desert Network National Parks” National Park Service Sonoran Desert Network I&M Program Review. Hilton Tucson East, Tucson, Arizona. July, 2008.;Submitted: Yes;Collaborative with graduate student: Yes;Type of Presentation: National Park Service Program Review;
• van Leeuwen, W. J., J.E., D., Breshears, D. D., & J.D., W. (2008, 2008-06-01). Drought-induced vegetation change in sky islands: remotely sensed phenology along gradients of woody plant cover. MTNCLIM 2008 Mountain Climate Research Conference. Silverton, CO.
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  Davison J.E., David D. Breshears, Willem J.D. Van Leeuwen, “Drought-induced vegetation change in sky islands: remotely sensed phenology along gradients of woody plant cover”, MTNCLIM 2008 Mountain Climate Research Conference, Silverton, Colorado, 9-12 June 2008. ;Your Role: Co-Chairing and guiding Graduate Student and research respectively.;Submitted: Yes;Collaborative with graduate student: Yes;Collaborative with faculty member at UA: Yes;Type of Presentation: Academic Conference;
• van Leeuwen, W. J., J.E., D., Breshears, D. D., & J.D., W. (2008, 2008-08-01). Sky Islands as barometers of change: Phenology and disturbance along woody plant gradients. Annual meeting of the Ecological Society of America. Milwaukee, Wisconsin.
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  Davison J.E., David D. Breshears, Willem J.D. Van Leeuwen, “Sky Islands as barometers of change: Phenology and disturbance along woody plant gradients”, Annual meeting of the Ecological Society of America, Milwaukee, Wisconsin, August 3-8, 2008.;Your Role: Co-chairing nad guiding research of Graduate Student Jennifer Davison;Submitted: Yes;Collaborative with graduate student: Yes;Collaborative with faculty member at UA: Yes;Type of Presentation: Professional Organization;
• van Leeuwen, W. J., Leeuwen, W. v., & , D. B. (2008, 2008-04-01). Remotely sensed vegetation dynamics along mountain gradients: characterization of Sky Islands and their responses to disturbance. Northern Arizona University's Geospatial Research and Information Library. Flagstaff.
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  Davison, J.E., D.D. Breshears, W.J.D. van Leeuwen, “Remotely sensed vegetation dynamics along mountain gradients: characterization of Sky Islands and their responses to disturbance” Northern Arizona University's Geospatial Research and Information Library, Flagstaff, AZ April 2008.;Your Role: Provided resources and guidance to the research efforts by the graduate Student who was invited to speak at this meeting.;Invited: Yes;Collaborative with graduate student: Yes;Collaborative with faculty member at UA: Yes;Type of Presentation: Invited/Plenary Speaker;
• van Leeuwen, W. J., M.L., V., , R. R., & J.D., W. (2008, 2008-11-01). Satellite Image-based classifications for landscape dynamics monitoring of Sonoran Desert national parks. Graduate Interdisciplinary Program community meeting and showcase. University of Arizona.
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  Villareal M.L., R. Romo, Willem J.D. van Leeuwen, “Satellite Image-based classifications for landscape dynamics monitoring of Sonoran Desert national parks”. Remote Sensing and Spatial Analysis Graduate Interdisciplinary Program community meeting and showcase, November 4, 2008.;Your Role: Helped prepare the poster. Results presented of a project WvL was a PI for.;Submitted: Yes;Invited: Yes;Collaborative with graduate student: Yes;Type of Presentation: University;
• van Leeuwen, W. J., Rasmussen, C., Crimmins, M., Schaap, M., & Willem, J. (2008, 2008-12-01). Soil Physical Properties Modulate the Effects of Climate Variability on Aboveground Productivity in a Semiarid Rangeland. AGU. San Francisco.
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  Rasmussen, C., Crimmins, M., Schaap, M., Willem J.D. van Leeuwen, “Soil Physical Properties Modulate the Effects of Climate Variability on Aboveground Productivity in a Semiarid Rangeland”, AGU meetings, San Francisco, CA, Dec 15-19, 2008.;Your Role: Providing remote sensing expertise, data and graphics, to this project.;Submitted: Yes;Interdisciplinary: Yes;Collaborative with faculty member at UA: Yes;Type of Presentation: Academic Conference;
• van Leeuwen, W. J., Thomas, A., M., C., & S.E., M. (2008, 2008-10-01). Exploring NDVI-Climate Relationships in Support of Drought Monitoring in Arizona”. Southwest US Region. American Society for Photogrammetry and Remote Sensing / USA-NPN annual meeting. Tucson.
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  Thomas, A., M. Crimmins, Willem J.D. van Leeuwen, S.E. Marsh, “Exploring NDVI-Climate Relationships in Support of Drought Monitoring in Arizona”. Southwest US Region, American Society for Photogrammetry and Remote Sensing / USA-NPN annual meeting, Tucson, AZ, October 10, 2008.;Your Role: Helped with guiding research and preparation of poster of graduate student Alys Thomas;Submitted: Yes;Collaborative with graduate student: Yes;Collaborative with faculty member in unit: Yes;Collaborative with faculty member at UA: Yes;Type of Presentation: Academic Conference;
• van Leeuwen, W. J., Villarreal, M. L., Willem, J., Romo, ., & R., . (2008, 2009-10-01). Integrating Phenology into Satellite-based Classifications for Landscape Dynamics Monitoring. U.S.A. National Phenology Network (NPN) & Southwest U.S. Region, American Society of Photogrammetry and Remote Sensing (ASPRS). Tucson.
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  Villarreal, M.L., Willem J.D. van Leeuwen, and Romo, R., “Integrating Phenology into Satellite-based Classifications for Landscape Dynamics Monitoring”. At Characterizing the Phenology of Southwest Landscapes. U.S.A. National Phenology Network (NPN) & Southwest U.S. Region, American Society of Photogrammetry and Remote Sensing (ASPRS). Tucson, Arizona. October 10, 2008.;Your Role: Guiding research of Graduate Students Miguel Villarreal and Raul Romo;Submitted: Yes;Collaborative with graduate student: Yes;Type of Presentation: Academic Conference;
• Leeuwen, v., J.D., W., Davison, J., Casady, G., & Marsh, S. (2007, 2007-04-01). Satellite derived vegetation phenology for a sky island in Arizona. AAG. San Francisco, USA..
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  van Leeuwen, Willem J.D., Jennifer Davison, Grant Casady, Stuart Marsh, “Satellite derived vegetation phenology for a sky island in Arizona” presented at the Association of American Geographers (AAG), San Francisco, USA. April 17 -21, 2007.;Collaborative with graduate student: Yes;Collaborative with faculty member in unit: Yes;Type of Presentation: Professional Organization;
• van Leeuwen, W. J. (2007, 2007-04-01). Remotely sensed monitoring of vegetation phenology before and after disturbance events in Arizona. International Association for Landscape Ecology. Tucson.
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  van Leeuwen, Willem J.D., “Remotely sensed monitoring of vegetation phenology before and after disturbance events in Arizona”. Presentation at the 22nd Annual Meeting of the US Regional Association of the International Association for Landscape Ecology. Tucson, Arizona, April 9 - 13, 2007.;Type of Presentation: Professional Organization;
• van Leeuwen, W. J. (2007, 2007-04-01). Vegetation Phenological Trajectories in Response to Drought and Wildfire. Seminar. Univerity of Arizona.
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  van Leeuwen, Willem J.D., Remotely Sensed Vegetation Phenological Trajectories in Response to Drought and Wildfire, University of Arizona, School of Natural Resources, April 4th, 2007.;Type of Presentation: University;
• van Leeuwen, W. J. (2007, 2007-10-01). Detecting phenological changes in vegetation response to climate variation on the Santa Rita Experimental Range and nearby areas. 4th RISE Symposium (Research Insights in Semiarid Ecosystems. Tucson.
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  van Leeuwen, Willem J.D., Detecting phenological changes in vegetation response to climate variation on the Santa Rita Experimental Range and nearby areas. 4th RISE Symposium (Research Insights in Semiarid Ecosystems), Tucson, Arizona, October 6, 2007.;Type of Presentation: Invited/Plenary Speaker;
• van Leeuwen, W. J. (2007, 2007-10-01). Satellite Derived Vegetation Dynamics: a Phenological Approach to Monitoring Changes in the Southwestern U.S.. seminar. NCAR, Boulder Colorado.
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  van Leeuwen, Willem J.D., Satellite Derived Vegetation Dynamics: a Phenological Approach to Monitoring Changes in the Southwestern U.S. NCAR, Boulder Colorado, October 19, 2007.;Type of Presentation: Invited/Plenary Speaker;
• van Leeuwen, W. J., Casady, G. M., Willem, J., & B.J., O. (2007, 2007-04-01). Investigating local scale variability in post-wildfire vegetation dynamics for a burned area in Central Arizona. IALE. Tucson.
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  Casady, G.M., Willem J.D. van Leeuwen, D. Neary, B.J. Orr, S.E. Marsh, “Investigating local scale variability in post-wildfire vegetation dynamics for a burned area in Central Arizona”. 22nd Annual Meeting of the US Regional Association of the International Association for Landscape Ecology. Tucson, Arizona, April 9 - 13, 2007. ;Your Role: research expertise;Collaborative with graduate student: Yes;Collaborative with faculty member in unit: Yes;Other collaborative: Yes;Specify other collaborative: Dan Neary - USDA Forest Service;Type of Presentation: Professional Organization;
• van Leeuwen, W. J., Casady, G. M., Willem, J., J.E., D., & Y., C. (2007, 2007-04-01). Using time-series satellite data to evaluate post-wildfire vegetation dynamics. US Regional Association of the International Association for Landscape Ecology. Tucson.
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  Casady, G.M., Willem J.D. van Leeuwen, B.J. Orr, J.E. Davison, S. Bautista, Y. Carmel, “Using time-series satellite data to evaluate post-wildfire vegetation dynamics”. 22nd Annual Meeting of the US Regional Association of the International Association for Landscape Ecology. Tucson, Arizona, April 9 - 13, 2007. ;Your Role: Time series analysis;Collaborative with graduate student: Yes;Collaborative with faculty member in unit: Yes;Other collaborative: Yes;Specify other collaborative: University of Alicante, SpainTechnion University, Israel;Type of Presentation: poster;
• van Leeuwen, W. J., Davison, J., & Willem, J. (2007, 2007-10-01). A preliminary evaluation of vegetation phenology, woody cover and drought. American Society of Photogrammetry and Remote Sensing Symposium. Tucson.
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  Davison, Jennifer, Willem J.D. van Leeuwen, D.D. Breshears, “A preliminary evaluation of vegetation phenology, woody cover and drought”. Southwest US Region, American Society of Photogrammetry and Remote Sensing Symposium, Tucson, Arizona, October 5, 2007.;Your Role: research advisor;Type of Presentation: Professional Organization;
• van Leeuwen, W. J., Davison, J., Willem, J., & Stuart, M. (2007, 2007-04-01). Phenological metrics and their response to drought in Arizona: The Santa Rita Mountains. US Regional Association of the International Association for Landscape Ecology. Tucson.
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  Davison, Jennifer, Willem J.D. van Leeuwen, Grant Casady, Stuart Marsh, “Phenological metrics and their response to drought in Arizona: The Santa Rita Mountains”. 22nd Annual Meeting of the US Regional Association of the International Association for Landscape Ecology. Tucson, Arizona. April 9 - 13, 2007.;Your Role: senior researcher;Collaborative with graduate student: Yes;Collaborative with faculty member in unit: Yes;Type of Presentation: poster;
• van Leeuwen, W. J., Davison, J., Willem, J., & Stuart, M. (2007, 2007-04-01). Vegetation phenology and climate variability in a sky island in Arizona. IALE. Tucson.
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  Davison, Jennifer, Willem J.D. van Leeuwen, Grant Casady, Stuart Marsh, “Vegetation phenology and climate variability in a sky island in Arizona”. 22nd Annual Meeting of the US Regional Association of the International Association for Landscape Ecology. Tucson, Arizona, April 9 - 13, 2007.;Your Role: Senior researcher;Collaborative with graduate student: Yes;Collaborative with faculty member in unit: Yes;Type of Presentation: Professional Organization;
• van Leeuwen, W. J., J., D., Kariyeva, ., & J.D., W. (2007, 2007-06-01). Phenological characterization of a sky island: insights into vegetation patterns across space and time. International Symposium on Remote Sensing of Environment. San Jose, Costa Rica.
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  Davison J., Kariyeva, J., Willem J.D. van Leeuwen. “Phenological characterization of a sky island: insights into vegetation patterns across space and time”. Proceeding of the 32nd International Symposium on Remote Sensing of Environment, San José, Costa Rica, June 25 - 29, 2007.;Your Role: Senior researcher;Collaborative with graduate student: Yes;Type of Presentation: Academic Conference;
• van Leeuwen, W. J., Kariyeva, J., Jennifer, D., & Willem, J. (2007, 2007-10-01). Phenological characterization of different vegetation types in Arizona based on two spectral vegetation indices. Southwest US Region, American Society of Photogrammetry and Remote Sensing Symposium. Tucson.
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  Kariyeva, Jahan, Jennifer Davison, Grant Casady, Willem J.D. van Leeuwen, “Phenological characterization of different vegetation types in Arizona based on two spectral vegetation indices”. Southwest US Region, American Society of Photogrammetry and Remote Sensing Symposium, Tucson, Arizona, October 5, 2007. ;Your Role: senior researcher;Type of Presentation: Professional Organization;
• van Leeuwen, W. J., Mattson, S., & Willem, J. (2007, 2007-04-01). Fire effects on vegetation recovery in the Santa Catalina Mountains. IALE. Tucson.
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  Mattson, Sarah, Willem J.D. van Leeuwen, Stephen R. Yool, “Fire effects on vegetation recovery in the Santa Catalina Mountains”. 22nd Annual Meeting of the US Regional Association of the International Association for Landscape Ecology. Tucson, Arizona. April 9 - 13, 2007.;Your Role: senior researcher;Type of Presentation: Professional Organization;
• van Leeuwen, W. J., Orr, B. J., S., B., Willem, J., J.E., D., D., M., & D.G., N. (2007, 2007-05-01). Satellite-derived vegetation dynamics applied to post-fire vulnerability assessment in eastern Spain. 4th International Wildland Fire Conference. Seville, Spain.
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  Orr, B.J. , S. Bautista, J.A. Alloza , Willem J.D. van Leeuwen, G.M. Casady, J.E. Davison, L. Wittenberg , D. Malkinson, Y. Carmel, and D.G. Neary. 2007. “Satellite-derived vegetation dynamics applied to post-fire vulnerability assessment in eastern Spain”. Seville, Spain, May 13-17, 2007.;Your Role: time series analysis;Collaborative with graduate student: Yes;Collaborative with faculty member in unit: Yes;Other collaborative: Yes;Specify other collaborative: USDA forest ServiceUniversity of Alicante, SpainTechnion University, IsraelUniversity of Haifa, Israel;Type of Presentation: poster;
• van Leeuwen, W. J., avison, J., & Kariyeva, J. (2007, 2007-10-01). Precipitation and vegetation phenology: comparison of remotely sensed greenness in the Santa Rita Mountains. 4th RISE Symposium (Research Insights in Semiarid Ecosystems). Tucson.
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  Davison, Jennifer, Kariyeva Jahan, Willem J.D. van Leeuwen, “Precipitation and vegetation phenology: comparison of remotely sensed greenness in the Santa Rita Mountains”. 4th RISE Symposium (Research Insights in Semiarid Ecosystems), Tucson, Arizona, October 6, 2007.;Your Role: Senior researcher;Collaborative with graduate student: Yes;Type of Presentation: poster;
• Leeuwen, v., Hutchinson, C., Sheffner, E., Doorn, B., & Kaupp, V. H. (2006, 2006-07-01). Integrated Crop Production Observations and Information. International Geoscience and Remote Sensing Symposium - 27th Canadian Symposium on Remote Sensing. Denver, CO, USA.
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  ;Your Role: Author and research;Submitted: Yes;Interdisciplinary: Yes;Collaborative with faculty member in unit: Yes;Other collaborative: Yes;Specify other collaborative: NASA HQUSDA/FAS;Type of Presentation: Academic Conference/Workshop;
• van Leeuwen, W. J. (2006, 2006-08-01). Insight into the Operational Use and Limitations of Spectral Vegetation Indices for Agriculture and Rangelands. CEOS Land Product Validation workshop: Validation of global vegetation indices and their time series. University of Montana, Missoula, Montana.
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  ;Your Role: Invited speaker;Invited: Yes;Type of Presentation: Academic Conference/Workshop;
• van Leeuwen, W. J. (2006, 2006-11-01). Integrating Crop Production Observations in a Decision Support System. American Society of Photogrammetry & Remote Sensing (ASPRS); Southwest Region Fall Technical Meeting. Tucson, AZ.
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  ;Your Role: Presentation;Submitted: Yes;Type of Presentation: Professional Organization;
• van Leeuwen, W. J., J.D., W., Huang, C., Casady, G., & Marsh, S. E. (2006, 2006-03-01). Satellite Derived Vegetation Phenology: Changes in the Southwestern U.S.. Association of American Geographers (AAG). Chicago.
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  ;Your Role: Research leader;Submitted: Yes;Collaborative with graduate student: Yes;Collaborative with faculty member in unit: Yes;Type of Presentation: Academic Conference;
• van Leeuwen, W. J., J.D., W., Huang, C., Davison, J., Marsh, S., & Casady, G. (2006, 2006-08-01). Vegetation Phenology of a Sky Island: the Santa Rita Mountains. International Global Vegetation Monitoring workshop. University of Montana, Missoula Montana.
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  ;Your Role: Research poster creation;Submitted: Yes;Collaborative with undergraduate student: Yes;Collaborative with graduate student: Yes;Collaborative with faculty member in unit: Yes;Type of Presentation: Academic Conference/Workshop;
• van Leeuwen, W. J., Leeuwen, W. v., , C. H., , S. D., , V. K., , T. H., & , V. L. (2005, 2005-01-01). Defect Detection and Prevention (DDP) ISFS application. Invasive Species Forecasting System benchmarking workshop. Tucson, AZ.
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  ;Your Role: co-directed research project ,Co-presented/created powerpoint;Interdisciplinary: Yes;Collaborative with faculty member in unit: Yes;Other collaborative: Yes;Specify other collaborative: University of Missouri;Type of Presentation: Academic Conference/Workshop;Type of Presentation: briefing;
• van Leeuwen, W. J., Leeuwen, W. v., , C. H., , S. D., , V. K., , T. H., & , V. L. (2005, 2005-03-01). Benchmarking PECAD's DSS. Washington DC.
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  ;Your Role: co-directed research project , Co-presented/created powerpoint;Interdisciplinary: Yes;Collaborative with faculty member in unit: Yes;Other collaborative: Yes;Specify other collaborative: University of Missouri;Type of Presentation: Project briefing at NASA headquarters;
• van Leeuwen, W. J., Leeuwen, W. v., Orr, B., Casady, G., Neary, D. G., Aguilar, S. B., Carmel, Y., & Wittenberg., L. (2005, 2005-12-01). SEASONAL ASSESSMENTS OF WILDFIRE EFFECTS ON LAND DEGRADATION AND VEGETATION DYNAMICS. 4th USGS Wildland Fire Science Workshop. Tucson, AZ.
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  ;Your Role: Directed research project - created poster;Submitted: Yes;Interdisciplinary: Yes;Collaborative with graduate student: Yes;Collaborative with faculty member in unit: Yes;Other collaborative: Yes;Specify other collaborative: University of Alicante, SpainTechnion, IsraelUSDA Forest service;Type of Presentation: Academic Conference/Workshop;
• van Leeuwen, W. J., Orr, B., Leeuwen, W. v., Casady, G., Marsh, S., Grunberg, W., Thwaits, A., & Benally, E. (2005, 2005-04-01). Decision Support Tools and Data for Land Management. USDA/NASA Workshop on Earth Science Information and Decision Support. New Orleans, Louisiana.
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  ;Your Role: Co-created poster;Submitted: Yes;Interdisciplinary: Yes;Collaborative with undergraduate student: Yes;Collaborative with graduate student: Yes;Collaborative with faculty member in unit: Yes;Type of Presentation: Academic Conference/Workshop;

Poster Presentations

• Falk, D. A., Gillan, J. K., Van Leeuwen, W. J., & Lee, K. (2023, December). Unraveling the Determinants of Burn Severity: Predictive Regression Analysis of the Bighorn Fire in Santa Catalina, Arizona. American Geophysical Union (AGU). San Francisco, CA: AGU.
• Broxton, P., Biederman, J., & Van Leeuwen, W. J. (2019, January). SnowView: A satellite data and model driven decision support tool for water resource management. 99th American Meteorological Society Annual Meeting. Phoenix, AZ: SRP.
• Broxton, P., Van Leeuwen, W. J., & Biederman, J. (2018, April). The Effect of Forest Structure on Snowpack along Arizona’s Mogollon Rim. 86th Annual Western Snow Conference. Albuquerque, NM.
• Van Leeuwen, W. J., Broxton, P., & Biederman, J. (2017, december). Evaluating UAV and LiDAR Retrieval of Snow Depth in a Coniferous Forest in Arizona. American Geophysical Union. New Orleans: SRP.
• Hartfield, K. A., & Van Leeuwen, W. J. (2016, june/july). Quantifying Woody Cover: Multi Spatio-Temporal Remote Sensing Classification and Regression Methods. ESRI conference June 27 - July 1, 2016. San Diego.. San Diego: ESRi.
• Hartfield, K. A., Van Leeuwen, W. J., Marsh, S. E., Crimmins, M. A., Weiss, J. L., Torrey, Y., Rahr, M. J., & K C, P. (2016, July). DroughtView: Satellite-based Drought Monitoring and Assessment – An update. ESRI. San Diego: ESRI.
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  Kyle Hartfield, Willem J.D. van Leeuwen, Michael Crimmins, Stuart Marsh, Yuta Torrey, Matt Rahr, Jeremy Weiss, and Pratima K C, DroughtView: Satellite-based Drought Monitoring and Assessment – An update. ESRI conference June 27 - July 1,2016. San Diego.
• Weiss, J. L., Hartfield, K. A., Van Leeuwen, W. J., Crimmins, M. A., Marsh, S. E., Torrey, Y., Rahr, M. J., & K C, P. (2016, April). DroughtView: Satellite-based Drought Monitoring and Assessment. University of Arizona – International Arid Lands Consortium : Cross-disciplinary Symposium on Arid Environments Research.
• Petrakis, R., & Van Leeuwen, W. J. (2015, Fall). Multi-Source Remote Sensing to Observe Impacts of Fluctuating Management and Climate on Riparian Vegetation of the Rio Grande: 1935 to 2014. AGU. San Francisco.
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  Roy Petrakis, Paul Tashjian, Gina Dello Russo, Bruce Thomson, and Willem J.D. van Leeuwen. “Multi-Source Remote Sensing to Observe Impacts of Fluctuating Management and Climate on Riparian Vegetation of the Rio Grande: 1935 to 2014” American Geophysical Union Fall Meeting, San Francisco, CA, December 15-19, 2015
• Hartfield, K., Van Leeuwen, W. J., Crimmins, M. A., Marsh, S. E., Torrey, Y., Rahr, M., & Orr, B. J. (2014, Dec). DroughtView: Satellite Based Drought Monitoring and Assessment.. AGU. San Francisco: AGU.
• Kautz, M., Holifield-Collins, C., Goodrich, D., Guertin, D. P., Keefer, T., & Van Leeuwen, W. J. (2014, Oct). A Sensitivity Analysis of Runoff and Erosion to Remotely Sensed Canopy Cover Estimates on Shrubland and Grassland Watersheds Located in the Walnut Gulch Experimental Wa-tershed. RISE symposium. Tucson.
• Petrakis, R., Hartfield, K., Barrera, P., Van Leeuwen, W. J., Papuga, S. A., & Scott, C. A. (2014, Dec). Multi-Temporal Remote Sensing Data for Modeling of Dryland Evapotranspiration and Land Cover Change. AGU.
• Van Leeuwen, W. J., & Hartfield, K. (2014, 12). Remote Sensing of Breaks and Trends in Vegetation Time Series Data Due to Fire and Drought. AGU. San Francisco.
• Van Leeuwen, W. J., Hartfield, K., Petrakis, R., & Scott, C. A. (2014, may). Applications of Multi Scale Remotely Sensed Public Data for Land and Water Use Change Assessments. International Climate Change Adaptation Conference - Adaptation Futures 2014. Fortaleza Brazil.
• Czyzowska, E., van Leeuwen, W. J., Marsh, S., Hirschboeck, K., & Wisniewski, W. (2013, April). Snow cover estimation using IKONOS and Landsat. Western Snow Conference. Jackson Hole, Wyoming, USA..
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  Czyzowska, E., van Leeuwen, Willem J.D., Hirschboeck, K., Marsh, S., Wisniewski, W., 2013, Snow cover estimation using IKONOS and Landsat, Western Snow Conference, April 15-18, Jackson Hole, Wyoming, USA.
• van Leeuwen, W. J., & Hartfield, K. (2013, Dec). Remotely Sensed Identification, Monitoring and Assessment of Natural Response and Disturbance Processes at Yearly and Decadal Scales. AGU. San Francsico.
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  Willem J.D. van Leeuwen, Kyle Hartfield, Remotely Sensed Identification, Monitoring and Assessment of Natural Response and Disturbance Processes at Yearly and Decadal Scales. AGU Conference, Dec 9-13, 2013 San Francisco, CA, USA.
• Czyzowska, E., van, L. W., Marsh, S., Hirschboeck, K., & Wisniewski, W. (2012, December). Snow cover estimation and its impact on water resources in arid environments. Graduate Interdisciplinary Program, University of Arizona. Tucson.

Creative Productions

• Hartfield, K., van Leeuwen, W. J., Moore, D. J., Orr, B. J., & Marsh, S. E. (2013. Remote Sensing and GIS - Natural Resource Applications at Multiple Spatial and Temporal Scales.. GIS career day. Tucson: ARSC.
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  2013 Kyle Hartfield, Willem J.D. van Leeuwen, Barron Orr, David Moore, Stuart Marsh, 2013. Remote Sensing and GIS - Natural Resource Applications at Multiple Spatial and Temporal Scales. GIS Career Day, University of Arizona, March 6, Tucson, AZ,USA.

Others

• Didan, K., Barreto Munoz, A., Miura, T., Tsend-Ayush, J., Zhang, X., Friedl, M., Grey, J., Van Leeuwen, W. J., Czapla-Myers, J. S., Jenkerson, C., Maiersperger, T., & Meyers, D. (2017, 06). Multi-Sensor Vegetation Index and Phenology Earth Science Data Records Algorithm Theoretical Basis Document and User Guide. NASA/LP-DAAC,. https://lpdaac.usgs.gov/sites/default/files/public/measures/docs/VIP_ESDRs_ATBD_And_UsersGuide.pdf. https://lpdaac.usgs.gov/sites/default/files/public/measures/docs/VIP_ESDRs_ATBD_And_UsersGuide.pdf
• van Leeuwen, W. J., Hartfield, K., Miranda, M., & Meza, F. (2014, Summer 2013). Linea de investigacion en monitoreo ambiental.. report.
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  van Leeuwen, Willem J.D., Kyle Hartfield, Marcelo Miranda, Francisco J. Meza, 2013. Linea de investigacion en monitoreo ambiental. Pp 29-32. In: Fortalecimiento de capacidades para enfrentar los desafios del cambio global en Chile. Edt F. Meza. http://cambioglobal.uc.cl/index.php/en/component/docman/doc_download/128-booklet-ccg-corfo.html. Accessed Dec 2013.
• van Leeuwen, W. J. (2010, Fall). Innovative Science and Influential Policy Dialugues for Water Security in the Arid Americas - Grant writing meeting preparations - Inter-American Institute grant.
• van Leeuwen, W. J., Huete, A. R., Huemmrich, K. F., Miura, T., Xiao, X., Didan, K., Leeuwen, W. v., Hall, F., & Tucker, C. J. (2006). Vegetation Index greenness global data set.
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  ;Your Role: Co-author;Full Citation: ftp://ftp.iluci.org/Land_ESDR/VI_Huete_whitepaper.pdfVegetation Index greenness global data setWhite Paper for NASA ESDR/CDR (April 2006)Alfredo R. Huete1, Karl F. Huemmrich2, Tomoaki Miura3, Xiangming Xiao4, Kamel Didan, Willem van Leeuwen, Forrest Hall, Compton J. Tucker;Electronic: Yes;Collaborative with faculty member at UA: Yes;Other collaborative: Yes;Specify other collaborative: NASA/GSFCUniv. of HawaiiUniv. of New Hampshire;
• van Leeuwen, W. J., Morisette, J., Nickeson, J. E., Garrigues, S., Baret, F., Huete, A., Didan, K., Miura, T., Leeuwen, W. v., & Friedl, M. (2006). Report from the CEOS Land Product Validation - Topical Workshop on the Validation of Global Vegetation Indices and their Time Series.
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  ;Your Role: Co-author;Full Citation: Jeffrey Morisette, Jaime E. Nickeson, Sebastien Garrigues, Fréderic Baret, Alfredo Huete, Kamel Didan, Tomoaki Miura, Willem van Leeuwen, Mark Friedl, 2006. Report from the CEOS Land Product Validation - Topical Workshop on the Validation of Global Vegetation Indices and their Time Series. The Earth Observer, November - December 2006, Volume 18, Issue 6http://eospso.gsfc.nasa.gov/eos_observ/pdf/Nov-Dec06.pdf;Electronic: Yes;Collaborative with faculty member at UA: Yes;Other collaborative: Yes;Specify other collaborative: NASAUniversity of MarylandUniversity of BostonUniversity of HawaiiINRA - FRANCE;