{
 "culture": "en-US",
 "name": "IrrMapper_historical",
 "guid": "",
 "catalogPath": "",
 "snippet": "IrrMapper Irrigated Lands, Version 1.2. 1986-2020. Cell values: 0 non-irrigated; 1 irrigated.\nKetchum, D.; Jencso, K.; Maneta, M.P.; Melton, F.; Jones, M.O.; Huntington, J. IrrMapper: A Machine Learning Approach for High Resolution Mapping of Irrigated Agriculture Across the Western U.S., Remote Sens. 2020, 12, 2328. doi:10.3390/rs12142328\nKetchum, D., Hoylman, Z.H., Huntington, J. et al. Irrigation intensification impacts sustainability of streamflow in the Western United States. Commun Earth Environ 4, 479 (2023). doi:10.1038/s43247-023-01152-2",
 "description": "",
 "summary": "IrrMapper Irrigated Lands, Version 1.2. 1986-2020. Cell values: 0 non-irrigated; 1 irrigated.\nKetchum, D.; Jencso, K.; Maneta, M.P.; Melton, F.; Jones, M.O.; Huntington, J. IrrMapper: A Machine Learning Approach for High Resolution Mapping of Irrigated Agriculture Across the Western U.S., Remote Sens. 2020, 12, 2328. doi:10.3390/rs12142328\nKetchum, D., Hoylman, Z.H., Huntington, J. et al. Irrigation intensification impacts sustainability of streamflow in the Western United States. Commun Earth Environ 4, 479 (2023). doi:10.1038/s43247-023-01152-2",
 "title": "IrrMapper_historical",
 "tags": [
  "BAGIS",
  "IrrMapper",
  "Irrigated lands",
  "bagisYearStart:1986",
  "bagisYearEnd:2020"
 ],
 "type": "Image Service",
 "typeKeywords": [
  "ArcGIS Server",
  "Data",
  "Image Service",
  "Service"
 ],
 "thumbnail": "",
 "url": "https://webservices.geog.pdx.edu/arcgis/",
 "minScale": 1.5595143952994827E7,
 "maxScale": 487348.24853108835,
 "spatialReference": "NAD_1983_2011_USA_Contiguous_Albers_Equal_Area_Conic_USGS_version",
 "accessInformation": "Portland State University",
 "licenseInfo": "Public",
 "portalUrl": ""
}