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Mapping irrigated lands at 250-m scale by merging MODIS data and National Agricultural Statistics

Remote Sensing

By:
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DOI: 10.3390/rs2102388

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Abstract

Accurate geospatial information on the extent of irrigated land improves our understanding of agricultural water use, local land surface processes, conservation or depletion of water resources, and components of the hydrologic budget. We have developed a method in a geospatial modeling framework that assimilates irrigation statistics with remotely sensed parameters describing vegetation growth conditions in areas with agricultural land cover to spatially identify irrigated lands at 250-m cell size across the conterminous United States for 2002. The geospatial model result, known as the Moderate Resolution Imaging Spectroradiometer (MODIS) Irrigated Agriculture Dataset (MIrAD-US), identified irrigated lands with reasonable accuracy in California and semiarid Great Plains states with overall accuracies of 92% and 75% and kappa statistics of 0.75 and 0.51, respectively. A quantitative accuracy assessment of MIrAD-US for the eastern region has not yet been conducted, and qualitative assessment shows that model improvements are needed for the humid eastern regions where the distinction in annual peak NDVI between irrigated and non-irrigated crops is minimal and county sizes are relatively small. This modeling approach enables consistent mapping of irrigated lands based upon USDA irrigation statistics and should lead to better understanding of spatial trends in irrigated lands across the conterminous United States. An improved version of the model with revised datasets is planned and will employ 2007 USDA irrigation statistics.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Mapping irrigated lands at 250-m scale by merging MODIS data and National Agricultural Statistics
Series title:
Remote Sensing
DOI:
10.3390/rs2102388
Volume
2
Issue:
10
Year Published:
2010
Language:
English
Contributing office(s):
Earth Resources Observation and Science (EROS) Center
Description:
25 p.
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
Larger Work Title:
Remote Sensing
First page:
2388
Last page:
2412
Number of Pages:
25