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A shapefile of the extent of irrigated agricultural fields which includes an attribute table of the irrigated acreage for the period between January and December 2020 was compiled for Alachua, Baker, Bradford, Columbia, Dixie, Gilchrist, Hamilton, Jefferson, Lafayette, Levy, Madison, Suwannee, Taylor, and Union Counties, Florida. These counties are fully or partially within the Suwannee River Water Management District boundaries. Attributes for each polygon that represents a field include a general or specific crop type, irrigation system, and primary water source for irrigation.
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A shapefile of the extent of irrigated agricultural fields which includes an attribute table of the irrigated acreage for the period between January and December 2020 was compiled for Lake, Marion, and Orange Counties, Florida. Attributes for each polygon that represents a field include a general or specific crop type, irrigation system, and primary water source for irrigation.
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The GIS shapefile and summary tables provide irrigated agricultural land-use for Citrus, Hernando, Pasco, and Sumter Counties, Florida through a cooperative project between the U.S Geological Survey (USGS) and the Florida Department of Agriculture and Consumer Services (FDACS), Office of Agricultural Water Policy. Information provided in the shapefile includes the location of irrigated land field verified for 2019, crop type, irrigation system type, and primary water source used in Citrus, Hernando, Pasco, and Sumter Counties, Florida. A map image of the shapefile is provided in the attachment.
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This dataset is the third (circa 2013) in a series of three 1-kilometer land use land cover (LULC) time-periods datasets (1975, 2000, and 2013) aids in monitoring change in West Africa’s land resources. To monitor and map these changes, a 26 general LULC class system was used. The classification system that was developed was primarily inspired by the “Yangambi Classification” (Trochain, 1957). This fairly broad class system for LULC was used because the classes can be readily identified on Landsat satellite imagery. A visual photo-interpretation approach was used to identify and map the LULC classes represented on Landsat images. The Rapid Land Cover Mapper (RLCM) was used to facilitate the photo-interpretation...
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This data set consists of a detailed digital map of the areal extent of fields and a summary of the irrigated acreage for the 2018 growing season developed for Hillsborough County, Florida. Selected attribute data that include crop type, irrigation system, and primary water source were collected for each irrigated field.
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A detailed inventory of irrigated crop acreage is not available at the level of resolution needed to accurately estimate agricultural water-use or to project future water demands in many Florida counties. A detailed summary table of irrigated acreage for the 2016 growing season was developed by the U.S. Geological Survey (USGS) for Santa Rosa County, Florida, and includes totals of acreage by irrigation system. It also provides a comparison between published acreage totals for previous years by the U.S. Department of Agriculture (USDA) Census of Agriculture and those determined from the 2016 inventory. The irrigated acreage estimated by the USGS for the 2016 inventory was 560 acres.
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This data set consists of a detailed digital map of the areal extent of fields and a summary of the irrigated acreage for the 2018 growing season developed for Charlotte County, Florida. Selected attribute data that include crop type, irrigation system, and primary water source were collected for each irrigated field.
These datasets are created during the irrigation reanalysis workflow (irrigation_reanalysis.zip). The actet_openet.cbh, potet_openet.cbh, and dyn_ag_frac.param area created during step one of the workflow when converting daily OpenET/SSEBop results into input for the NHM. The nhm_2000_2020_ag_irrigation_add.csv, and nhm_2000_2020_ag_irrigation_add_vol.csv area estimated daily results output by the NHM.
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A detailed inventory of irrigated crop acreage is not available at the level of resolution needed to accurately estimate agricultural water-use or to project future water demands in many Florida counties. A detailed summary table of irrigated acreage for the 2016 growing season was developed by the U.S. Geological Survey (USGS) for Escambia County, Florida, and includes totals of acreage by irrigation system. It also provides a comparison between published acreage totals for previous years by the U.S. Department of Agriculture (USDA) Census of Agriculture and those determined from the 2016 inventory. The irrigated acreage estimated by the USGS for the 2016 inventory was 3,018 acres.
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A detailed table summarizing the irrigated acreage by crop type and irrigation system was developed for the 2018 growing season (November 2017 and September 2018) for Hillsborough County, Florida. The acreage totals presented are derived from the results of a cooperative project that mapped and field-verified irrigated fields in Hillsborough County, Florida. In addition, the table provides acreage totals by crop type published by the U.S. Department of Commerce for 1978 and 1982 and the U.S. Department of Agriculture for years between 1987 and 2012.
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A detailed table summarizing the irrigated acreage by crop type and irrigation system was developed for the 2018 growing season (November 2017 and September 2018) for Charlotte County, Florida. The acreage totals presented are derived from the results of a cooperative project that mapped and field-verified irrigated fields in Charlotte County, Florida. In addition, the table provides acreage totals by crop type published by the U.S. Department of Commerce for 1978 and 1982 and the U.S. Department of Agriculture for years between 1987 and 2012.
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This data release provides a monthly irrigation water use reanalysis for the period 2000-20 for all USGS Watershed Boundary Dataset of Subwatersheds (HUC12) in the conterminous United States (CONUS). Results include reference evapotranspiration (ETo), actual evapotranspiration (ETa), irrigated areas, consumptive use, and effective precipitation for each HUC12. ETo and ETa were estimated using the operational Simplified Surface Energy Balance (SSEBop, Senay and others, 2013; Senay and others, 2020) model executed in the OpenET (Melton and others, 2021) web-based application implemented in Google Earth Engine. Results provided by OpenET/SSEBop were summarized to hydrologic response units (HRUs) in the National Hydrologic...
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This dataset is the second (2013) of two 500-meter land use land cover (LULC) time-periods datasets (2000, and 2013) aids in monitoring change in West Africa’s land resources. To monitor and map these changes, a 26 general LULC class system was used. The classification system that was developed was primarily inspired by the “Yangambi Classification” (Trochain, 1957). This fairly broad class system for LULC was used because the classes can be readily identified on Landsat satellite imagery. A visual photo-interpretation approach was used to identify and map the LULC classes represented on Landsat images. The Rapid Land Cover Mapper (RLCM) was used to facilitate the photo-interpretation using Esri’s ArcGIS Desktop...
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This data set consists of a detailed digital map of the areal extent of fields and a summary of the irrigated acreage for the 2018 growing season developed for Lee County, Florida. Selected attribute data that include crop type, irrigation system, and primary water source were collected for each irrigated field.
The Landsat-based Irrigation Dataset (LANID) uses a random-forest machine-learning model with greenness and vegetative indices, climate data, and crop masks to identify irrigated crops (Xie and others, 2021, Xie and Lark, 2021). Separate western US and eastern US methods are used to train and validate the model. Annual LANID maps for 2018-20 were created using the same techniques in Xie and others, 2021, and Xie and Lark, 2021.
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This dataset is the second (circa 2000) in a series of three 1-kilometer land use land cover (LULC) time-periods datasets (1975, 2000, and 2013) aids in monitoring change in West Africa’s land resources. To monitor and map these changes, a 26 general LULC class system was used. The classification system that was developed was primarily inspired by the “Yangambi Classification” (Trochain, 1957). This fairly broad class system for LULC was used because the classes can be readily identified on Landsat satellite imagery. A visual photo-interpretation approach was used to identify and map the LULC classes represented on Landsat images. The Rapid Land Cover Mapper (RLCM) was used to facilitate the photo-interpretation...
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A detailed table summarizing the irrigated acreage by crop type and irrigation system was developed for the 2018 growing season (November 2017 and September 2018) for Lee County, Florida. The acreage totals presented are derived from the results of a cooperative project that mapped and field-verified irrigated fields in Lee County, Florida. In addition, the table provides acreage totals by crop type published by the U.S. Department of Commerce for 1978 and 1982 and the U.S. Department of Agriculture for years between 1987 and 2012.
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A detailed inventory of irrigated crop acreage is not available at the level of resolution needed to accurately estimate agricultural water-use or to project future water demands in many Florida counties. A detailed summary table of irrigated acreage for the 2016 growing season was developed for Okaloosa County by the U.S. Geological Survey (USGS) and includes totals of acreage by irrigation system. It also provides a comparison between published acreage totals for previous years by the U.S. Department of Agriculture (USDA) Census of Agriculture and those determined from the 2016 inventory. The irrigated acreage estimated by the USGS for the2016 inventory was 351 acres.
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This dataset is the second (circa 2000) in a series of three 2-kilometer land use land cover (LULC) time-periods datasets (1975, 2000, and 2013) aids in monitoring change in West Africa’s land resources (exception is Tchad at 4 kilometers). To monitor and map these changes, a 26 general LULC class system was used. The classification system that was developed was primarily inspired by the “Yangambi Classification” (Trochain, 1957). This fairly broad class system for LULC was used because the classes can be readily identified on Landsat satellite imagery. A visual photo-interpretation approach was used to identify and map the LULC classes represented on Landsat images. The Rapid Land Cover Mapper (RLCM) was used to...
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This dataset is the first (circa 1975) in a series of three 1-kilometer land use land cover (LULC) time-periods datasets (1975, 2000, and 2013) aids in monitoring change in West Africa’s land resources. To monitor and map these changes, a 26 general LULC class system was used. The classification system that was developed was primarily inspired by the “Yangambi Classification” (Trochain, 1957). This fairly broad class system for LULC was used because the classes can be readily identified on Landsat satellite imagery. A visual photo-interpretation approach was used to identify and map the LULC classes represented on Landsat images. The Rapid Land Cover Mapper (RLCM) was used to facilitate the photo-interpretation...
map background search result map search result map Table 1. Reported and inventoried crop and irrigated acreage in Escambia County, Florida, 1974–2016. Table 2. Reported and inventoried crop and irrigated acreage in Santa Rosa County, Florida, 1974–2016. Table 3. Reported and inventoried crop and irrigated acreage in Okaloosa County, Florida, 1974–2016. GIS shapefile: Charlotte County, Florida irrigated agricultural land-use for the 2018 growing season Table: Reported and inventoried crop and irrigated acreage in Charlotte County, Florida, 1978-2018 GIS shapefile: Lee County, Florida irrigated agricultural land-use for the 2018 growing season Table: Reported and inventoried crop and irrigated acreage in Lee County, Florida, 1978-2018 Table: Reported and inventoried crop and irrigated acreage in Hillsborough County, Florida, 1978-2018 GIS shapefile: Hillsborough County, Florida irrigated agricultural land-use for the 2018 growing season GIS shapefile and related summary data describing irrigated agricultural land-use in Citrus, Hernando, Pasco, and Sumter Counties, Florida for 2019 Gambia Land Use Land Cover 1975 Gambia Land Use Land Cover 2000 Gambia Land Use Land Cover 2013 Capo Verde, Land Use Land Cover 2013 West Africa Land Use Land Cover 2000 GIS Shapefile of Irrigated Agricultural Acreage for Lake, Marion, and Orange Counties, Florida in 2020 GIS shapefile of Irrigated Agricultural Acreage within the Suwannee River Water Management District in 2020 Irrigation water use reanalysis for the 2000-20 period by HUC12, month, and year for the conterminous United States Table 3. Reported and inventoried crop and irrigated acreage in Okaloosa County, Florida, 1974–2016. Table 2. Reported and inventoried crop and irrigated acreage in Santa Rosa County, Florida, 1974–2016. GIS shapefile: Lee County, Florida irrigated agricultural land-use for the 2018 growing season GIS shapefile: Hillsborough County, Florida irrigated agricultural land-use for the 2018 growing season Table: Reported and inventoried crop and irrigated acreage in Hillsborough County, Florida, 1978-2018 Table: Reported and inventoried crop and irrigated acreage in Lee County, Florida, 1978-2018 GIS shapefile and related summary data describing irrigated agricultural land-use in Citrus, Hernando, Pasco, and Sumter Counties, Florida for 2019 GIS Shapefile of Irrigated Agricultural Acreage for Lake, Marion, and Orange Counties, Florida in 2020 Gambia Land Use Land Cover 1975 Gambia Land Use Land Cover 2000 Gambia Land Use Land Cover 2013 GIS shapefile of Irrigated Agricultural Acreage within the Suwannee River Water Management District in 2020 Capo Verde, Land Use Land Cover 2013 West Africa Land Use Land Cover 2000 Irrigation water use reanalysis for the 2000-20 period by HUC12, month, and year for the conterminous United States