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File AET2RET_Ratios.csv lists the AET to RET (actual to reference evapotranspiration) ratios, or AET/RET, used to calculate actual evapotranspiration for each land cover type. The daily measured AET data collected at the ET stations were used to calculate the monthly totals for each month of the year. These monthly AET totals were then used to calculate the average AET/RET monthly ratios for the land cover of the ET station by dividing the AET rates by the RET rates obtained from the Florida ET network (http://fl.water.usgs.gov/et/; USGS, 2016). The land cover types represented in these data are forest, grass, marsh, open water, ridge, urban, and agriculture. The AET/RET ratios for these land cover types were presented...
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We created a single map of surface water presence by intersecting water classes from available land cover products (National Wetland Inventory, Gap Analysis Program, National Land Cover Database, and Dynamic Surface Water Extent) across the U.S. state of Arizona. We derived classified samples for four wetland classes from the harmonized map: water, herbaceous wetlands, wooded wetlands, and non-wetland cover. In Google Earth Engine (GEE) we developed a random forest model that combined the training data with spatially explicit predictor variables of vegetation greenness indices, wetness indices, seasonal index variation, topographic variables, and hydrologic parameters. The final product is a wall-to-wall map of...
This spreadsheet dataset (.csv file) contains annual modeled output of land-use and land-cover change transitions in square kilometers (km2) by specified transition group, scenario, timestep, WEAP hydrologic zone, and 4 sub-regions within the broader California Central Valley, modeled using the LUCAS ST-SIM for the period 2011-2101 across 5 future scenarios. Four of the scenarios were developed as part of the Central Valley Landscape Conservation Project. The 4 original scenarios include a Bad-Business-As-Usual (BBAU; high water availability, poor management), California Dreamin’ (DREAM; high water availability, good management), Central Valley Dustbowl (DUST; low water availability, poor management), and Everyone...
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Polygons indicate the extent of urban (gridcode 5) and developed (gridcode 6) land cover in the greater Kabul area. Polygons were created from classification of Landsat 8 Operational Land Imagery (OLI) 30m resolution multispectral satellite imagery acquired on June 13, 2018.
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This dataset describes land cover and vegetation for the island of Maui, Hawaii, 2017, hereinafter the 2017 land-cover map. The 2017 land-cover map is a modified version of the 2010 land-cover map included in the geospatial dataset titled "Mean annual water-budget components for the Island of Maui, Hawaii, for average climate conditions, 1978-2007 rainfall and 2010 land cover (version 2.0)" by Johnson (2017). The 2010 land-cover map was generated by intersecting (merging) multiple spatial datasets that characterize the spatial distribution of rainfall, cloud-water (or fog) interception, irrigation, reference evapotranspiration, direct runoff, soil type, and land cover. Land-cover designations in the 2010 land-cover...


    map background search result map search result map Land-Cover Map for the Island of Maui, Hawaii, 2017 Actual to reference evapotranspiration (AET/RET) ratios for several land-cover types in east-central Florida State Class Transition Spreadsheet (Area of Land Transition into Each Class per Year, per Scenario) Urban and developed areas indicated by classification of Landsat 2018 multispectral imagery Wetlands in the state of Arizona Urban and developed areas indicated by classification of Landsat 2018 multispectral imagery Actual to reference evapotranspiration (AET/RET) ratios for several land-cover types in east-central Florida Wetlands in the state of Arizona State Class Transition Spreadsheet (Area of Land Transition into Each Class per Year, per Scenario)