Case Study Comparing Multiple Irrigated Land Datasets in Arizona and Colorado,USA |
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| Authors: | Hua Shi Roger F Auch James E Vogelmann Min Feng Matthew Rigge Gabriel Senay James P Verdin |
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| Affiliation: | 1. ASRC Federal InuTeq, Contractor to the U.S. Geological Survey Earth Resources Observation and Science Center, Sioux Falls, South Dakota;2. Earth Resources Observation and Science Center, U.S. Geological Survey, Sioux Falls, South Dakota;3. Department of Geographical Sciences, University of Maryland, College Park, Maryland |
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| Abstract: | While there are currently a number of irrigated land datasets available for the western United States (U.S.), there is uncertainty regarding in how they relate to each other. To help understand the characteristics of available irrigated datasets, we compared (1) the Cropland Data Layer (CDL), (2) Moderate Resolution Imaging Spectroradiometer Irrigated Agriculture Dataset (IAD), (3) Digitized Irrigated Land (DIL), and (4) Consumptive Use for Irrigation (CUI) data in Arizona and Colorado, U.S. These datasets were derived from multiple sources at various spatial resolutions and temporal scales. We found spatial and temporal trends among all of them. The datasets showed decreases in irrigated land area in Arizona during the 2000–2010 time period. The change ranges and ratios were similar in all Arizona datasets. Irrigated land in Colorado decreased in DIL and CUI but increased in IAD and CDL. The agreement within the same type of dataset during different time periods was from 60% to 80% (R2 from 0.35 to 0.72) in Arizona and from 50% to 80% (R2 from 0.23 to 0.68) in Colorado. DIL had the highest agreement (80%) in both states. The agreement among different datasets acquired at approximately the same time frame ranged from 51% to 63% (R2 from 0.14 to 0.31) in Arizona and from 47% to 69% (R2 from 0.32 to 0.40) in Colorado. The results from this study support a greater understanding of the multiresolution and multitemporal nature of these datasets for various applications. |
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| Keywords: | spatiotemporal analysis irrigation datasets comparison change and shift and agreement |
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