Kyle A Hartfield

Interests

Research

Remote Sensing, GIS

Teaching

Remote Sensing, GIS

Courses

Scholarly Contributions

Chapters

• Schneier-madanes, G., Valdes, J. B., Valdes, J. B., Curley, E. F., Maddock, T., Marsh, S. E., Hartfield, K., Maddock Iii, T., & Hartfield, K. A. (2017). Water and urban development challenges in the Tucson metropolitan area: An interdisciplinary perspective. In Water Bankruptcy in the Land of Plenty. CRC Press. doi:10.1201/B21583
• Schneier-madanes, G., Valdes, J. B., Valdes, J. B., Curley, E. F., Maddock, T., Marsh, S., Marsh, S. E., Maddock Iii, T., & Hartfield, K. A. (2016). Water and urban development challenges of urban growth. In Water for a new America. CRC Press. doi:10.1201/B21583-14

Journals/Publications

• Jones, S. A., Archer, S. R., Hartfield, K. A., & Marsh, S. E. (2023). Topoedaphic constraints on woody plant cover in a semi-arid grassland. Ecological Indicators, 151, 110226.
• Marsh, S. E., Hartfield, K. A., Archer, S. R., & Jones, S. A. (2023). Topoedaphic constraints on woody plant cover in a semi-arid grassland. Ecological Indicators, 151. doi:https://doi.org/10.1016/j.ecolind.2023.110226
• Hartfield, K., Gillan, J. K., Norton, C. L., Conley, C., & van Leeuwen, W. J. (2022). A Novel Spectral Index to Identify Cacti in the Sonoran Desert at Multiple Scales Using Multi-Sensor Hyperspectral Data Acquisitions. Land, 11(6), 11. doi:https://doi.org/10.3390/land11060786
• Norton, C. L., Hartfield, K., Holifield Collins, C. D., van Leeuwen, W. J., & Metz, L. J. (2022). Multi-Temporal LiDAR and Hyperspectral Data Fusion for Classification of Semi-Arid Woody Cover Species. Remote Sensing, 14(12), 2896. doi:https://doi.org/10.3390/rs14122896
• Khatri-Chhetri, P., Hendryx, S. M., Hartfield, K. A., Crimmins, M. A., Leeuwen, W., & Kane, V. R. (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), 1103. doi:https://doi.org/10.3390/rs13061103
• Lee, R. H., Navarro-Navarro, L. A., Ley, A., Hartfield, K., Tolleson, D. R., & Scott, C. A. (2021). Spatio-temporal dynamics of climate change, land degradation, and water insecurity in an arid rangeland: The Rí­o San Miguel watershed, Sonora, Mexico. Journal of Arid Environments, 193, 104539. doi:104539
• Cornejo-Denman, L., Romo-Leon, J. R., Hartfield, K., J, W., 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), 2519.
• 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. 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
• Hausermann, H., Ferring, D., Atosona, B., Mentz, G., Amankwah, R., Chang, A., Hartfield, K., Effah, E., Asuamah, G. Y., Mansell, C., & Sastri, N. (2018). Land-grabbing, land-use transformation and social differentiation: Deconstructing "small-scale" in Ghana's recent gold rush. World Development, 108, 103-114. doi:https://doi.org/10.1016/j.worlddev.2018.03.014
• Mendez-Estrella, R., Romo-Leon, J., Castellanos, A., Gandarilla-Aizpuro, F., & Hartfield, K. (2016). Analyzing Landscape Trends on Agriculture, Introduced Exotic Grasslands and Riparian Ecosystems in Arid Regions of Mexico. Remote Sensing, 8(8). doi:10.3390/rs8080664
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  Riparian Zones are considered biodiversity and ecosystem services hotspots. In arid environments, these ecosystems represent key habitats, since water availability makes them unique in terms of fauna, flora and ecological processes. Simple yet powerful remote sensing techniques were used to assess how spatial and temporal land cover dynamics, and water depth reflect distribution of key land cover types in riparian areas. Our study area includes the San Miguel and Zanjon rivers in Northwest Mexico. We used a supervised classification and regression tree (CART) algorithm to produce thematic classifications (with accuracies higher than 78%) for 1993, 2002 and 2011 using Landsat TM scenes. Our results suggest a decline in agriculture (32.5% area decrease) and cultivated grasslands (21.1% area decrease) from 1993 to 2011 in the study area. We found constant fluctuation between adjacent land cover classes and riparian habitat. We also found that water depth restricts Riparian Vegetation distribution but not agricultural lands or induced grasslands. Using remote sensing combined with spatial analysis, we were able to reach a better understanding of how riparian habitats are being modified in arid environments and how they have changed through time.
• Romo-leon, J. R., Mendez-estrella, R., Hartfield, K. A., Gandarilla-aizpuro, F. J., & Castellanos, A. E. (2016). Analyzing Landscape Trends on Agriculture, Introduced Exotic Grasslands and Riparian Ecosystems in Arid Regions of Mexico. Remote Sensing, 8(8), 664. doi:10.3390/rs8080664
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  Project: "Strengthening Resilience of Arid Region Riparian Corridors Ecohydrology and Decision-Making in the Sonora and San Pedro Watersheds"; National Science Foundation's Dynamics of Coupled Natural and Human (CNH) Systems Program; National Council for Science and Technology of Mexico (CONACYT); [CB2013-223525-R]; [INF2012/1-188387]
• Leeuwen, W. J., Hartfield, K. A., Leeuwen, W. J., Jacobs, S., Hutto, R. L., Hartfield, K. A., & Flesch, A. D. (2015). Correction: Spatial, Temporal, and Density-Dependent Components of Habitat Quality for a Desert Owl.. PloS one, 10(10), e0141178. doi:10.1371/journal.pone.0141178
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  The captions for Figs ​Figs22 and ​and33 are incorrectly switched. The caption for Fig 3 should be the caption for Fig 2, and the caption for Fig 3 should be the caption for Fig 2. Please see the corrected captions here. Fig 2 Effect of habitat factors on reproductive output of ferruginous pygmy-owls in northwest Mexico, 2001–2010. Fig 3 Interactive effects of abundance of potential nest sites and other habitat factors on reproductive output of ferruginous pygmy-owls in northwest Mexico, 2001–2010.
• Leeuwen, W. J., Hartfield, K. A., Leeuwen, W. J., Jacobs, S., Hutto, R. L., Hartfield, K. A., & Flesch, A. D. (2015). Spatial, temporal, and density-dependent components of habitat quality for a desert owl.. PloS one, 10(3), e0119986. doi:10.1371/journal.pone.0119986
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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. A., Palumbo, J. C., Nolte, K. D., Marsh, S. E., Liesner, L., Leeuwen, W. J., Hartfield, K. A., Ellers-kirk, C., Dutilleul, P., Degain, B. A., & Carriere, Y. (2014). Assessing transmission of crop diseases by insect vectors in a landscape context.. Journal of economic entomology, 107(1), 1-10. doi:10.1603/ec13362
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  Theory indicates that landscape composition affects transmission of vector-borne crop diseases, but few empirical studies have investigated how landscape composition affects plant disease epidemiology. Since 2006, Bemisia tabaci (Gennadius) has vectored the cucurbit yellow stunting disorder virus (CYSDV) to cantaloupe and honeydew melons (Cucumis melo L.) in the southwestern United States and northern Mexico, causing significant reductions in yield of fall melons and increased use of insecticides. Here, we show that a landscape-based approach allowing simultaneous assessment of impacts of local (i.e., planting date) and regional (i.e., landscape composition) factors provides valuable insights on how to reduce crop disease risks. Specifically, we found that planting fall melon fields early in the growing season, eliminating plants germinating from seeds produced by spring melons after harvest, and planting fall melon fields away from cotton and spring melon fields may significantly reduce the incidence of CYSDV infection in fall melons. Because the largest scale of significance of the positive association between abundance of cotton and spring melon fields and CYSDV incidence was 1,750 and 3,000 m, respectively, reducing areas of cotton and spring melon fields within these distances from fall melon fields may decrease CYSDV incidence. Our results indicate that landscape-based studies will be fruitful to alleviate limitations imposed on crop production by vector-borne diseases.
• Leeuwen, W. J., Hartfield, K. A., Szutu, D., Swetish, J. B., Sanchez-mejia, Z. M., Papuga, S. A., Leeuwen, W. J., & Hartfield, K. A. (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.
• Carrière, Y., Marsh, S. E., Hartfield, K. A., & Kirk, C. D. (2013). Contemporary and historical classification of crop types in Arizona. International Journal of Remote Sensing, 34(17), 6024-6036. doi:10.1080/01431161.2013.793861
• Leeuwen, W. J., Hartfield, K. A., Miranda, M., Meza, F., Leeuwen, W. J., & Hartfield, K. A. (2013). Trends and ENSO/AAO Driven Variability in NDVI Derived Productivity and Phenology alongside the Andes Mountains. Remote Sensing, 5(3), 1177-1203. doi:10.3390/rs5031177
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  Increasing water use and droughts, along with climate variability and land use change, have seriously altered vegetation growth patterns and ecosystem response in several regions alongside the Andes Mountains. Thirty years of the new generation biweekly normalized difference vegetation index (NDVI3g) time series data show significant land cover specific trends and variability in annual productivity and land surface phenological response. Productivity is represented by the growing season mean NDVI values (July to June). Arid and semi-arid and sub humid vegetation types (Atacama desert, Chaco and Patagonia) across Argentina, northern Chile, northwest Uruguay and southeast Bolivia show negative trends in productivity, while some temperate forest and agricultural areas in Chile and sub humid and humid areas in Brazil, Bolivia and Peru show positive trends in productivity. The start (SOS) and length (LOS) of the growing season results show large variability and regional hot spots where later SOS often coincides with reduced productivity. A longer growing season is generally found for some locations in the south of Chile (sub-antarctic forest) and Argentina (Patagonia steppe), while central Argentina (Pampa-mixed grasslands and agriculture) has a shorter LOS. Some of the areas have significant shifts in SOS and LOS of one to several months. The seasonal Multivariate ENSO Indicator (MEI) and the Antarctic Oscillation (AAO) index have a significant impact on vegetation productivity and phenology in southeastern and northeastern Argentina (Patagonia and Pampa), central and southern Chile (mixed shrubland, temperate and sub-antarctic forest), and Paraguay (Chaco).
• Li, X., Ellsworth, P. C., Fournier, A., Hartfield, K. A., Tabashnik, B. E., Palumbo, J. C., Naranjo, S. E., Marsh, S. E., Li, X., Larocque, G., Hartfield, K. A., Fournier, A., Ellsworth, P. C., Ellers-kirk, C., Dutilleul, P., Dennehy, T. J., Degain, B., Crowder, D. W., Carriere, Y., & Antilla, L. (2012). Large-scale, spatially-explicit test of the refuge strategy for delaying insecticide resistance.. Proceedings of the National Academy of Sciences of the United States of America, 109(3), 775-80. doi:10.1073/pnas.1117851109
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  The refuge strategy is used worldwide to delay the evolution of pest resistance to insecticides that are either sprayed or produced by transgenic Bacillus thuringiensis (Bt) crops. This strategy is based on the idea that refuges of host plants where pests are not exposed to an insecticide promote survival of susceptible pests. Despite widespread adoption of this approach, large-scale tests of the refuge strategy have been problematic. Here we tested the refuge strategy with 8 y of data on refuges and resistance to the insecticide pyriproxyfen in 84 populations of the sweetpotato whitefly (Bemisia tabaci) from cotton fields in central Arizona. We found that spatial variation in resistance to pyriproxyfen within each year was not affected by refuges of melons or alfalfa near cotton fields. However, resistance was negatively associated with the area of cotton refuges and positively associated with the area of cotton treated with pyriproxyfen. A statistical model based on the first 4 y of data, incorporating the spatial distribution of cotton treated and not treated with pyriproxyfen, adequately predicted the spatial variation in resistance observed in the last 4 y of the study, confirming that cotton refuges delayed resistance and treated cotton fields accelerated resistance. By providing a systematic assessment of the effectiveness of refuges and the scale of their effects, the spatially explicit approach applied here could be useful for testing and improving the refuge strategy in other crop-pest systems.
• Hartfield, K. A., Leeuwen, W. J., Leeuwen, W. J., Landau, K. I., & Hartfield, K. A. (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. doi:10.3390/rs3112364
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  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.

Presentations

• Hartfield, K. A. (2019, June). State of the Eastern Mojave Desert - 2019. State of the Eastern Mojave Desert - 2019. Boulder City, Nevada: Eastern Mojave Conservation Collaborative.
• Hartfield, K. A. (2019, September). Developing a framework for assessing vulnerability of western cultural heritage.. 15th Biennial Conference ofScience & Management on the Colorado Plateau & Southwest Region. Flagstaff, Arizona.

Poster Presentations

• 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.