The raster-based Modified Soil Adjusted Vegetation Index was derived from Landsat Thematic Mapper imagery data acquired during June 1989 for Sarcobatus Flat. 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.

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, color-infrared composite was derived from Landsat Thematic Mapper imagery data acquired during June 1989 for the Sarcobatus Flat area of the Death Valley regional flow system. The image is a single-channel, parallelepiped classification that when displayed using a 256-color color table shows a simulation of a color-infrared composite. The data set was used in determining phreatophyte boundaries for a ground-water evapotranspiration study.

The raster-based, color-infrared composite was derived from Landsat Thematic Mapper imagery data acquired during June 1989 for the Sarcobatus Flat area of the Death Valley regional flow system. The image is a single-channel, parallelepiped classification that when displayed using a 256-color color table shows a simulation of a color-infrared composite. The data set was used in determining phreatophyte boundaries for a ground-water evapotranspiration study.

The mean MSAVI image is based on two Landsat 5 Thematic Mapper (TM) scenes representing midsummer conditions in 2007 and 2008. MSAVI was calculated for each image which were then combined by calculating the mean for each pixel in the scenes. The resultant MSAVI image was used to estimate vegetation assemblages (ET units) within a mapped groundwater discharge area.

The mean MSAVI image is based on two Landsat 5 Thematic Mapper (TM) scenes representing midsummer conditions in 2007 and 2008. MSAVI was calculated for each image which were then combined by calculating the mean for each pixel in the scenes. The resultant MSAVI image was used to estimate vegetation assemblages (ET units) within a mapped groundwater discharge area.

These data are a compilation of four mask layers (regions), and enhanced vegetation indices calculated from airborne or satellite imagery. The mask layers were used created to extract satellite EVI data from the four airborne or satellite imagery datasets. The Enhanced Vegetation Index (EVI) is a key Earth science parameter used to assess vegetation, originally developed and calibrated for the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra and Aqua satellites. With the impending decommissioning of the MODIS sensors by the year 2020/2022, alternative platforms will need to be used to estimate EVI. These data were created to compare Landsat 5 (2000–2011), 8 (2013–2016) and the Visible Infrared Imaging Radiometer Suite (VIIRS; 2013–2016) to MODIS EVI (2000–2016) over a 420,083-ha area of the arid lower Colorado River Delta in Mexico. Over large areas with mixed land cover or agricultural fields, a high correspondence was found between Landsat and MODIS EVI (R2 = 0.93 for the entire area studied and 0.97 for agricultural fields), but the relationship was weak over bare soil (R2 = 0.27) and riparian vegetation (R2 = 0.48). The correlation between MODIS and Landsat EVI was higher over large, homogeneous areas and was generally lower in narrow riparian areas. VIIRS and MODIS EVI were highly similar (R2 = 0.99 for the entire area studied) and did not show the same decrease in performance in smaller, narrower regions as Landsat. Landsat and VIIRS provide EVI estimates of similar quality and characteristics to MODIS, but scale, seasonality and land cover type(s) should be considered before implementing Landsat EVI in a particular area.

These data are a compilation of four mask layers (regions), and enhanced vegetation indices calculated from airborne or satellite imagery. The mask layers were used created to extract satellite EVI data from the four airborne or satellite imagery datasets. The Enhanced Vegetation Index (EVI) is a key Earth science parameter used to assess vegetation, originally developed and calibrated for the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra and Aqua satellites. With the impending decommissioning of the MODIS sensors by the year 2020/2022, alternative platforms will need to be used to estimate EVI. These data were created to compare Landsat 5 (2000–2011), 8 (2013–2016) and the Visible Infrared Imaging Radiometer Suite (VIIRS; 2013–2016) to MODIS EVI (2000–2016) over a 420,083-ha area of the arid lower Colorado River Delta in Mexico. Over large areas with mixed land cover or agricultural fields, a high correspondence was found between Landsat and MODIS EVI (R2 = 0.93 for the entire area studied and 0.97 for agricultural fields), but the relationship was weak over bare soil (R2 = 0.27) and riparian vegetation (R2 = 0.48). The correlation between MODIS and Landsat EVI was higher over large, homogeneous areas and was generally lower in narrow riparian areas. VIIRS and MODIS EVI were highly similar (R2 = 0.99 for the entire area studied) and did not show the same decrease in performance in smaller, narrower regions as Landsat. Landsat and VIIRS provide EVI estimates of similar quality and characteristics to MODIS, but scale, seasonality and land cover type(s) should be considered before implementing Landsat EVI in a particular area.