These data represent the extent and spatial distribution of irrigated acreage delineated from maximum Normalized Difference Vegetation Index (NDVI) derived from Landsat scenes in the Walker River Basin, California and Nevada, at five-year intervals from 1975-2010. The field boundaries in this data set are digitized from one-year composite maximum NDVI data derived from atmospherically corrected Landsat 2 Multispectral Scanner (MSS), Landsat 5 MSS, and Landsat 5 Thematic Mapper (TM) scenes. NDVI was calculated from the corrected reflectance data for each selected scene during the growing season (May through early October) and a single, composite image of maximum NDVI values was derived for each five-year interval. Selecting the maximum NDVI value removed low values associated with plant phenology, harvest cycles, and irrigation operations. Initial field boundaries were digitized from the 2010 National Agriculture Imagery Program (NAIP) data and boundary geometries were divided and shaped based on temporal changes in irrigation practices, crop rotations, and other changes identified in the Landsat-derived maximum NDVI data. Each polygon is attributed with an estimated irrigation status of irrigated or non-irrigated. Mapped fields were classified as irrigated during a growing season if more than 45-percent of a field had a maximum NDVI value greater than or equal to 0.4.

Agricultural land cover for the western United States. This dataset was developed from Sagestitch, the Eastern Washington Shrubsteppe Mapping Project, and several state level GAP products (AZ, CA, NM, OR, and WA).

Agricultural land cover for the western United States. This dataset was developed from Sagestitch, the Eastern Washington Shrubsteppe Mapping Project, and several state level GAP products (AZ, CA, NM, OR, and WA).

These operational land imager (OLI) value added data sets, maps, and associated ancillary data were compiled as part of an ongoing research aimed at quantifying the riparian vegetation greenness and water use in the lower Colorado River Delta in Mexico. In order to create trend and anomaly maps that characterize these ecosystems Vegetation Index (NDVI) time series imagery from Landsat OLI were acquired and processed over time and space along seven predefined reaches that capture different natural states and management conditions. We used Landsat OLI 30m data as an improvement upon past studies that were based on coarser remote sensing data from the NASA MODIS sensor (250 m). The OLI 30m images provide better characterization and performance over these rather narrow riparian corridors. To capture the change over time we used a simple differencing technique that compares two annual average growing season VI cycles (limited to May-October). These anomaly maps capture how the corridor vegetation health responds to both natural and anthropogenic changes. We limited this study to the full OLI record (2013-2019) since we were interested in understanding the response to Minute 319 pulse flow of 2014. The difference maps are an ideal tool for capturing how the released water impacted vegetation immediately and over long time. The Minute 319 pulse flow science team in collaboration with the University of Arizona have developed a data processing system to support this effort with focus on understanding how the riparian corridor is responding to these natural and anthropogenic stressors. All data associated with this project were acquired from the LP-DAAC and pre-processed to remove and capture issues prior to further processing (see below) which involved reprojection to a common projection, masking to only retain the area of interest, quality analysis to discard poor data, and then value addition to generate the NDVI and the difference maps. The data acquisition and analysis were performed at the University of Arizona VIP lab (vip.arizona.edu) using their large Linux cluster of computing and storage resources. A mix of off the shelf software and specialized in-house tools were used to carry the different steps and analyses.

These operational land imager (OLI) value added data sets, maps, and associated ancillary data were compiled as part of an ongoing research aimed at quantifying the riparian vegetation greenness and water use in the lower Colorado River Delta in Mexico. In order to create trend and anomaly maps that characterize these ecosystems Vegetation Index (NDVI) time series imagery from Landsat OLI were acquired and processed over time and space along seven predefined reaches that capture different natural states and management conditions. We used Landsat OLI 30m data as an improvement upon past studies that were based on coarser remote sensing data from the NASA MODIS sensor (250 m). The OLI 30m images provide better characterization and performance over these rather narrow riparian corridors. To capture the change over time we used a simple differencing technique that compares two annual average growing season VI cycles (limited to May-October). These anomaly maps capture how the corridor vegetation health responds to both natural and anthropogenic changes. We limited this study to the full OLI record (2013-2019) since we were interested in understanding the response to Minute 319 pulse flow of 2014. The difference maps are an ideal tool for capturing how the released water impacted vegetation immediately and over long time. The Minute 319 pulse flow science team in collaboration with the University of Arizona have developed a data processing system to support this effort with focus on understanding how the riparian corridor is responding to these natural and anthropogenic stressors. All data associated with this project were acquired from the LP-DAAC and pre-processed to remove and capture issues prior to further processing (see below) which involved reprojection to a common projection, masking to only retain the area of interest, quality analysis to discard poor data, and then value addition to generate the NDVI and the difference maps. The data acquisition and analysis were performed at the University of Arizona VIP lab (vip.arizona.edu) using their large Linux cluster of computing and storage resources. A mix of off the shelf software and specialized in-house tools were used to carry the different steps and analyses.

The raster-based Modified Soil Adjusted Vegetation Index was derived from Landsat Thematic Mapper imagery data acquired during June 1992 for the Death Valley regional flow system. The index has been shown to increase the dynamic range of the vegetation signal while further minimizing the soil background influences, resulting in greater vegetation sensitivity as defined by a "vegetation signal" to "soil noise" ratio. The data set was used in determining phreatophyte boundaries for a ground-water evapotranspiration study and relative differences in vegetation density between discharge areas.

The raster-based Modified Soil Adjusted Vegetation Index was derived from Landsat Thematic Mapper imagery data acquired during June 1992 for the Death Valley regional flow system. The index has been shown to increase the dynamic range of the vegetation signal while further minimizing the soil background influences, resulting in greater vegetation sensitivity as defined by a "vegetation signal" to "soil noise" ratio. The data set was used in determining phreatophyte boundaries for a ground-water evapotranspiration study and relative differences in vegetation density between discharge areas.

This dataset, created in support of USGS Scientific Investigations Report 2020-5075, Estimates of Groundwater Discharge by Evapotranspiration, Stump Spring and Hiko Springs, Clark County, Nevada, 2016-18, represents a Normalized Difference Vegetation Index calculated for vegetated areas in the Stump Spring groundwater discharge area (GDA) and Area of Critical Environmental Concern (ACEC). Vegetated areas within the GDA are composed of phreatophytic shrubs interspersed with xeric vegetation and bare soil. The GDA was delineated by visual interpretation of 1-meter National Agriculture Imagery Program (NAIP) aerial imagery acquired in May of 2015. The NDVI was calculated from a June 2017 WorldView 2 image resampled to 1-meter cell size and masked to remove bare ground areas identified from a supervised classification based on the same 2015 NAIP image used to define the GDA.

This dataset, created in support of USGS Scientific Investigations Report 2020-5075, Estimates of Groundwater Discharge by Evapotranspiration, Stump Spring and Hiko Springs, Clark County, Nevada, 2016-18, represents a Normalized Difference Vegetation Index calculated for vegetated areas in the Hiko Springs groundwater discharge area. Vegetated areas within the GDA are composed of phreatophytic shrubs interspersed with xeric vegetation and bare soil. The GDA was delineated by visual interpretation of 1-meter National Agriculture Imagery Program (NAIP) aerial imagery acquired in May of 2015. Areas of channel scour within the GDA resulting from a flood event in September 2015 were delineated from a 2016 1.84-meter resolution Worldview 2 image. The NDVI was calculated from the same WorldView 2 with bare ground areas masked and calculated as "no data".

This dataset, created in support of USGS Scientific Investigations Report 2020-5075, Estimates of Groundwater Discharge by Evapotranspiration, Stump Spring and Hiko Springs, Clark County, Nevada, 2016-18, represents a Normalized Difference Vegetation Index calculated for vegetated areas in the Hiko Springs groundwater discharge area. Vegetated areas within the GDA are composed of phreatophytic shrubs interspersed with xeric vegetation and bare soil. The GDA was delineated by visual interpretation of 1-meter National Agriculture Imagery Program (NAIP) aerial imagery acquired in May of 2015. Areas of channel scour within the GDA resulting from a flood event in September 2015 were delineated from a 2016 1.84-meter resolution Worldview 2 image. The NDVI was calculated from the same WorldView 2 with bare ground areas masked and calculated as "no data".