NASS USDA estimates the irrigated croplands at county level every five years. But this estimation does not provide the geospatial information of the irrigated croplands. To provide a comprehensive, consistent, and timely geospatially detailed information about irrigated cropland conterminous U.S. (CONUS), the “Moderate Resolution Imaging Spectroradiometer (MODIS) Irrigated Agriculture Dataset for the United States (MIrAD-US)” product was produced by the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center with funding from several USGS programs (National Land Imaging and National Water-Quality Assessment). A primary objective was to identify, and map irrigated agricultural areas to factor into water quality studies and drought monitoring investigations. This product uses three primary data inputs, (a) USDA county-level irrigation area statistics for 2002, (b) annual peak eMODIS Normalized Difference Vegetation Index (NDVI), and (c) a land cover mask for agricultural lands derived from NLCD to map the spatial distribution of irrigated lands across the conterminous United States. The MIrAD Version 4 offers the datasets for the years 2002, 2007, 2012, and 2017 at 250-m and 1-km spatial resolutions. The validation of MIrAD-US is a challenge because no other single-source current datasets are available at a national scale for comparison. Thus, this dataset should be considered provisional until a formal accuracy assessment can be completed. The product update is planned for every 5 years, synchronized with the update of the Census of Agriculture by the U.S Department of Agriculture (USDA) but contingent upon availability of Collection 6 (C6) Aqua eMODIS data and funding.

These datasets are continuous parameter grids (CPG) of irrigated agriculture data (percent of basin classified as irrigated) for the years 2002, 2007, and 2012 in the Pacific Northwest. Source data was the Moderate Resolution Imaging Spectroradiometer (MODIS) Irrigated Agriculture Dataset for the United States (MIrAD-US), produced by the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center.

These datasets are continuous parameter grids (CPG) of irrigated agriculture data (percent of basin classified as irrigated) for the years 2002, 2007, and 2012 in the Pacific Northwest. Source data was the Moderate Resolution Imaging Spectroradiometer (MODIS) Irrigated Agriculture Dataset for the United States (MIrAD-US), produced by the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center.

The spatial extents of verified irrigated lands were compiled from various federal and state sources across the nation and combined into a single Geographic Information System (GIS) geodatabase for the purpose of model training and validation. In cooperation with U.S. Geological Survey (USGS), researchers at the University of Wisconsin (UW) generated a nation-wide map of irrigated lands using remote-sensing techniques that will be incorporated into future irrigation water-use models. The verified spatial data varies in scope, accuracy, and time period represented, but in general represents GIS coverages (polygons) of agricultural land irrigated for at least some period during 2002–17. Data from 14 states were provided to UW (Arizona, California, Colorado, Florida, Georgia, Idaho, Illinois, Mississippi, Montana, New Mexico, Texas, Utah, Washington, and Wyoming). It is important to validate that the remote sensing techniques correctly identify both irrigated and non-irrigated land. Varying data sources prevent this approach from being applied throughout the United States, but most datasets used for validation include at least some “non irrigated” land identification.

The spatial extents of verified irrigated lands were compiled from various federal and state sources across the nation and combined into a single Geographic Information System (GIS) geodatabase for the purpose of model training and validation. In cooperation with U.S. Geological Survey (USGS), researchers at the University of Wisconsin (UW) generated a nation-wide map of irrigated lands using remote-sensing techniques that will be incorporated into future irrigation water-use models. The verified spatial data varies in scope, accuracy, and time period represented, but in general represents GIS coverages (polygons) of agricultural land irrigated for at least some period during 2002–17. Data from 14 states were provided to UW (Arizona, California, Colorado, Florida, Georgia, Idaho, Illinois, Mississippi, Montana, New Mexico, Texas, Utah, Washington, and Wyoming). It is important to validate that the remote sensing techniques correctly identify both irrigated and non-irrigated land. Varying data sources prevent this approach from being applied throughout the United States, but most datasets used for validation include at least some “non irrigated” land identification.

This data release contains field sampling data collected on a farm located in Talbot County. Maryland, roadside survey data from the area surrounding the farm, and WorldView-3 satellite data of the study area. Datasets include: 1) CropResidueDataset.csv: Tabular data for 174 photo sampling locations with crop residue cover ranging from 0% to 98%, as well as line-point transect residue cover measurements and lat-long geolocations 2) Roadside_Survey_May14th2015.zip: Zipfile containing roadside survey data for 63 fields documenting percent crop residue cover, including shapefile of field boundaries 3) GroundCoverPhotographs.zip: Zipfile containing 174 nadir photographs that were the basis for ground cover calculations 4) WorldView-3 satellite imagery collected May 14, 2015 and converted to surface reflectance using MODTRAN. The data support a manuscript published in Remote Sensing journal: Hively, W.D; Lamb, B.T. Daughtry, C.S.T. Shermeyer, J. McCarty, G.W., and Quemada, M., 2018, Mapping Crop Residue and Tillage Intensity Using WorldView-3 Satellite Shortwave Infrared Residue Indices: Remote Sensing, vol. 10, p. 1657. https://doi.org/10.3390/rs10101657

This data release contains field sampling data collected on a farm located in Talbot County. Maryland, roadside survey data from the area surrounding the farm, and WorldView-3 satellite data of the study area. Datasets include: 1) CropResidueDataset.csv: Tabular data for 174 photo sampling locations with crop residue cover ranging from 0% to 98%, as well as line-point transect residue cover measurements and lat-long geolocations 2) Roadside_Survey_May14th2015.zip: Zipfile containing roadside survey data for 63 fields documenting percent crop residue cover, including shapefile of field boundaries 3) GroundCoverPhotographs.zip: Zipfile containing 174 nadir photographs that were the basis for ground cover calculations 4) WorldView-3 satellite imagery collected May 14, 2015 and converted to surface reflectance using MODTRAN. The data support a manuscript published in Remote Sensing journal: Hively, W.D; Lamb, B.T. Daughtry, C.S.T. Shermeyer, J. McCarty, G.W., and Quemada, M., 2018, Mapping Crop Residue and Tillage Intensity Using WorldView-3 Satellite Shortwave Infrared Residue Indices: Remote Sensing, vol. 10, p. 1657. https://doi.org/10.3390/rs10101657

This dataset contains summary tables of land cover from the Cropland Data Layer (CDL) for individual stream catchments of the conterminous United States from the National Hydrography Dataset Plus Version 2.1 (United States Department of Agriculture National Agricultural Statistics Service, 2024; McKay and others, 2012). These data were summarized from primarily 30 meter grid cell raster data for the years 2000 through 2022. This data release contains 23 parquet tables that can be linked to the NHD Plus v2 dataset using the COMID unique identifier and a column for each CDL land cover class. From 2008 onwards, these data are available for the conterminous United States. From 2000 to 2007, the CDL is only available for select states. For convenience, an additional parquet table is included with a column for COMID and columns containing a flag indicating whether CDL data exist for each year from 2000 through 2022. Parquet tables can be accessed using the "arrow" package in RStudio. An example command to open a file is: arrow::read_parquet(filepath, "cdl_2000_table.parquet"))

This dataset contains summary tables of land cover from the Cropland Data Layer (CDL) for individual stream catchments of the conterminous United States from the National Hydrography Dataset Plus Version 2.1 (United States Department of Agriculture National Agricultural Statistics Service, 2024; McKay and others, 2012). These data were summarized from primarily 30 meter grid cell raster data for the years 2000 through 2022. This data release contains 23 parquet tables that can be linked to the NHD Plus v2 dataset using the COMID unique identifier and a column for each CDL land cover class. From 2008 onwards, these data are available for the conterminous United States. From 2000 to 2007, the CDL is only available for select states. For convenience, an additional parquet table is included with a column for COMID and columns containing a flag indicating whether CDL data exist for each year from 2000 through 2022. Parquet tables can be accessed using the "arrow" package in RStudio. An example command to open a file is: arrow::read_parquet(filepath, "cdl_2000_table.parquet"))

,A Modelling dataset containing a DSSAT cultivar file, AgMIPS platform dome code and USDA ARS LIRF drip irrigated field experiment in Greeley, Colorado average Maize biomass and yield by treatment. Irrigation treatments vary from 40% to 100% of ET. This dataset is used with the DSSAT and RZWQM2 models as part of an Agricultural Model Inter-comparison and Improvement Project (AgMIP) data node maintained at National Agricultural Library for USDA-AgMIP data. Additional data are available from https://data.agmip.org/,The complete experiment dataset in readable Excel format is USDA-ARS Colorado Maize Water Productivity Dataset 2008-2011 and can be found at http://dx.doi.org/10.15482/USDA.ADC/1254006,,