US Irrigation | Early Warning and Environmental Monitoring Program

Moderate Resolution Imaging Spectroradiometer (MODIS) Irrigated Agriculture Dataset for the United States (MIrAD-US)

We have employed a geospatial modeling approach implemented for three time periods (2002, 2007 and 2012) to consistently map irrigated agriculture across the conterminous U.S. (Brown and Pervez 2014; Pervez and Brown 2010; Brown et al. 2009). Model inputs included the National Land Cover Dataset resampled to 250m, USDA Census of Agriculture irrigated area statistics, and annual maximum vegetation index (VI) calculated from NASA Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. These data can be used to help assess water-quality trends in ground and surface waters, explain drought impacts on vegetation, and support the application and refinement of current water volumes used for irrigation.

Download Data

2002 Data

Grid - 250m   |   Grid - 1km


Envi - 250m   |   Envi - 1km


2007 Data

Grid - 250m   |   Grid - 1km


Envi - 250m   |   Envi - 1km


2012 Data

Grid - 250m   |   Grid - 1km


Envi - 250m   |   Envi - 1km


  
Notice to Users:

Version 3 of the MODIS Irrigated Agriculture Dataset for the United States has now been released. In this version, consistent input data and processing procedures were used for each historical era (2002, 2007, and 2012) resulting in improved standardization. (Date: 04/16/2015)


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Publications

Brown, J.F. and Pervez, M.S., 2014, Merging remote sensing data and national agricultural statistics to model change in irrigated agriculture, Agricultural Systems, 127; doi:10.1016/j.agsy.2014.01.004.

Pervez, M.S. and Brown, J.F., 2010, Mapping irrigated lands at 250-m scale by merging MODIS data and national agricultural statistics, Remote Sensing, 2(10), 2388-2412; doi:10.3390/rs2102388. [Available online at http://www.mdpi.com/2072-4292/2/10/2388/]

Brown, J.F., Pervez, M.S., and Maxwell, S., 2009, Mapping irrigated lands across the United States using MODIS satellite imagery. in Thenkabail, P.S., and others, eds., Remote sensing of global croplands for food security: Boca Raton, Taylor & Francis, p. 177-198.