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 spatially explicit Enhanced Vegetation Index (EVI) and evapotranspiration (ET) map derived from time series Landsat images, maps, and associated ancillary data were compiled as part of 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, both EVI and ET from-Landsat-OLI were processed over time and space along seven pre-defined reaches that capture different natural states and management conditions. We used EVI from the Landsat operational land imager (OLI) sensor (30 m) as an input to our ET algorithm that was previously based on coarser resolution EVI from the NASA MODIS sensor (250 m). The work explored how to improve the spatial resolution of the ET estimates of riparian plant water use. OLI 30 m images provide better characterization and performance over these rather narrow riparian corridors and thus provide better estimation of riparian-area greenness and plant water use at this scale. To capture the trends and changes over time needed for estimating ET, which is dependent upon the EVI input data, we used a simple differencing technique that compares two annual average growing season EVI and ET cycles (limited to May-October). The EVI and ET 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 and its water use immediately after the release 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 remote sensing data analysis techniques can aid in assessing the riparian corridor response 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 analyses (see below). Preprocessing involves reprojection to a common map system, masking to only retain the area of interest, quality analysis to discard poor data, and then value addition to generate the EVI and difference maps as well as water use difference maps produced with ET-from-Landsat-EVI. 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 spatially explicit Enhanced Vegetation Index (EVI) and evapotranspiration (ET) map derived from time series Landsat images, maps, and associated ancillary data were compiled as part of 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, both EVI and ET from-Landsat-OLI were processed over time and space along seven pre-defined reaches that capture different natural states and management conditions. We used EVI from the Landsat operational land imager (OLI) sensor (30 m) as an input to our ET algorithm that was previously based on coarser resolution EVI from the NASA MODIS sensor (250 m). The work explored how to improve the spatial resolution of the ET estimates of riparian plant water use. OLI 30 m images provide better characterization and performance over these rather narrow riparian corridors and thus provide better estimation of riparian-area greenness and plant water use at this scale. To capture the trends and changes over time needed for estimating ET, which is dependent upon the EVI input data, we used a simple differencing technique that compares two annual average growing season EVI and ET cycles (limited to May-October). The EVI and ET 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 and its water use immediately after the release 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 remote sensing data analysis techniques can aid in assessing the riparian corridor response 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 analyses (see below). Preprocessing involves reprojection to a common map system, masking to only retain the area of interest, quality analysis to discard poor data, and then value addition to generate the EVI and difference maps as well as water use difference maps produced with ET-from-Landsat-EVI. 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 NOAA-20 Visible Infrared Imaging Radiometer Suite (VIIRS) (https://lpdaac.usgs.gov/dataset_discovery/viirs) Vegetation Indices (VJ113A3) Version 2 data product provides vegetation indices by a process of selecting the best available pixel over a monthly acquisition period at 1 kilometer (km) resolution. The VJ113 data products are designed after the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua Vegetation Indices product suite to promote the continuity of the Earth Observation System (EOS) mission. The VJ113 algorithm process produces three vegetation indices: The Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), and the Enhanced Vegetation Index-2 (EVI2). NDVI is one of the longest continual remotely sensed time series observations, using both the red and near-infrared (NIR) bands. EVI is a slightly different vegetation index that is more sensitive to canopy cover, while NDVI is more sensitive to chlorophyll. EVI2 is a reformation of the standard 3-band EVI, using the red band and NIR band. This reformation addresses arising issues when comparing VIIRS EVI to other EVI models that do not include a blue band. EVI2 will eventually become the standard EVI. Along with the three Vegetation Indices layers, this product also includes layers for NIR reflectance; three shortwave infrared (SWIR) reflectance; red, blue, and green reflectance; pixel reliability; pixel reliability; relative azimuth, view, and sun angles; and a quality layer. Two low resolution browse images are also available for each VJ113A3 product: EVI and NDVI.

The NOAA-20 Visible Infrared Imaging Radiometer Suite (VIIRS) Vegetation Indices (VJ113A3) Version 2 data product provides vegetation indices by a process of selecting the best available pixel over a monthly acquisition period at 1 kilometer (km) resolution. The VJ113 data products are designed after the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua Vegetation Indices product suite to promote the continuity of the Earth Observation System (EOS) mission. The VJ113 algorithm process produces three vegetation indices: The Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), and the Enhanced Vegetation Index-2 (EVI2). NDVI is one of the longest continual remotely sensed time series observations, using both the red and near-infrared (NIR) bands. EVI is a slightly different vegetation index that is more sensitive to canopy cover, while NDVI is more sensitive to chlorophyll. EVI2 is a reformation of the standard 3-band EVI, using the red band and NIR band. This reformation addresses arising issues when comparing VIIRS EVI to other EVI models that do not include a blue band. EVI2 will eventually become the standard EVI. Along with the three Vegetation Indices layers, this product also includes layers for NIR reflectance; three shortwave infrared (SWIR) reflectance; red, blue, and green reflectance; pixel reliability; pixel reliability; relative azimuth, view, and sun angles; and a quality layer. Two low resolution browse images are also available for each VJ113A3 product: EVI and NDVI.Known Issues* Due to missing critical inputs, this product lacks coverage for tiles h33v07 and h18v14, which are located over water.* For complete information about known issues please refer to the [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=VIIRS) and the User Guide and ATBD.Improvements/Changes from Previous Version* Improved calibration algorithm and coefficients for entire NOAA-20 mission.* Improved geolocation accuracy and applied updates to fix outliers around maneuver periods.* Corrected the aerosol quantity flag (low, average, high) mainly over brighter surfaces in the mid- to high-latitudes such as desert and tropical vegetation areas. This has an impact on the retrieval of other downstream data products such as VNP13 Vegetation Indices and VNP43 Bidirectional Reflectance Distribution Function (BRDF)/Albedo.* Improved cloud mask input product for corrections along coastlines and artifacts from use of coarse resolution climatology data. * Replaced the land/water mask input product with the eight-class land/water mask from the VNP03 geolocation product that better aligns with MODIS.* Modified QA VI Usefulness bits to ignore BRDF flag.* Implemented VI specific land/water mask.* More details can be found in this [VIIRS Land V2 Changes document](https://landweb.modaps.eosdis.nasa.gov/data/userguide/VIIRS_Land_C2_Changes_09152022.pdf).

These data were compiled for evaluating river-reach level plant water use, or evapotranspiration (ET), and vegetation greenness, or Normalized Difference Vegetation Index (NDVI), in the riparian corridor of the Colorado River delta as specified under Minute 319 of the 1944 Water Treaty. The seven reach areas from the Northerly International Boundary (NIB) to the end of the delta at the Sea of Cortez were defined for research activities. Also, these seven reaches are being monitored under Minute 323 of the 1944 Water Treaty. Additionally, these data were compiled for evaluating restoration-level evapotranspiration and vegetation greenness data in Reach 2 and Reach 4, as specified under Minute 323 of the 1944 Water Treaty. Objectives of our study were to measure the peak growing season ET and satellite vegetation index data, specifically using the Enhanced Vegetation Index (EVI) from Landsat, for the average of months in summer-fall (May to October) for the seven reaches, for the full riparian corridor, and for four restoration sites, from 2000 through 2020. The evapotranspiration data represent measurements of ET using the enhanced vegetation index (EVI), along with potential ET from meteorological station data in Yuma, Arizona. The vegetation greenness data represent measurements of enhanced vegetation index (EVI) Landsat imagery, and these EVI data were then used as an input for actual evapotranspiration ‘ET’, along with potential ET from meteorological station data in Yuma, Arizona. These data were collected using Landsat satellite data (30 m resolution) record from 2000 over the delta of the Colorado River starting near Yuma, AZ and continuing another 150km to the Sea of Cortez along the river corridor. These data were collected by Pamela Nagler, Ph.D. of the U.S. Geological Survey-Southwest Biological Science Center, and Armando Barreto-Muñoz, Ph.D. and Kamal Didan, Ph.D. of the University of Arizona, Vegetation Index and Phenology Lab. These data can be used to evaluate riparian vegetation community water use and vegetation greeness in the Lower Colorado River delta region where there is active restoration efforts. These ET and NDVI data depict a Landsat time series from three sensors over the 21-year period. The time-series data can be used by land and water managers to monitor spatial and temporal riparian zone trends and changes, document riparian ecosystem health and its water use, and the impact of both drought, fire, land clearing and/or non-native species biocontrol in the riparian corridor of the Lower Colorado River delta. End users of these data are federal, state, tribal partners and NGOs on both sides of the International border.

This raster dataset represents normalized difference vegetation index (NDVI) values calculated from National Agricultural Imagery Program (NAIP) spectral data for the vegetated evapotranspiration (ET) unit in the groundwater discharge areas for the Amargosa Wild and Scenic River and contributing areas. Estimated groundwater discharge by ET also is presented.

This raster dataset represents normalized difference vegetation index (NDVI) values calculated from National Agricultural Imagery Program (NAIP) spectral data for the vegetated evapotranspiration (ET) unit in the groundwater discharge areas for the Amargosa Wild and Scenic River and contributing areas. Estimated groundwater discharge by ET also is presented.

In 2014, the Alberta Energy Regulator (AER) initiated a Play-Based Regulation (PBR) pilot project as a step towards implementation of the Unconventional Regulatory Framework. One of the goals of the PBR pilot is to encourage companies in the unconventional play area to work together on plans for surface development to minimize the numbers of facilities and surface impacts. This dataset is one of a series created using earth observation imagery to assess surface change caused by energy exploration. The PBR area extends from Twp. 52, Rge. 7, W 5th Mer. to Twp. 70, Rge. 5, W 6th Mer., covering the towns of Edson, Fox Creek, Mayerthorpe, Whitecourt, Swan Hills, and Valleyview. Landsat multispectral imagery for 2006 and 2007 and Land Use and Land Cover (LULC) classification data derived from 2007 were used to produce this dataset. The LULC changes include vegetation loss from anthropogenic disturbances, such as infrastructure related to oil and gas exploration, forestry and agriculture, and vegetation recovery from these disturbances. This digital data release contains the vegetation recovery data, classified into 6 classes: 1 - shrub land, 2 - grassland, 3 - agricultural areas, 4 - coniferous forest, 5 - broadleaf forest and 6 - mixed forest.

The NOAA-20 Visible Infrared Imaging Radiometer Suite (VIIRS) (https://lpdaac.usgs.gov/dataset_discovery/viirs) Vegetation Indices (VJ113C2) Version 2 data product provides vegetation indices by a process of selecting the best available pixel over a monthly acquisition period at 0.05 degree (Deg) resolution. The VJ113 data products are designed after the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua Vegetation Indices product suite to promote the continuity of the Earth Observation System (EOS) mission. The VJ113 algorithm process produces three vegetation indices: The Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), and the Enhanced Vegetation Index-2 (EVI2). NDVI is one of the longest continual remotely sensed time series observations, using both the red and near-infrared (NIR) bands. EVI is a slightly different vegetation index that is more sensitive to canopy cover, while NDVI is more sensitive to chlorophyll. EVI2 is a reformation of the standard 3-band EVI, using the red band and NIR band. This reformation addresses arising issues when comparing VIIRS EVI to other EVI models that do not include a blue band. EVI2 will eventually become the standard EVI. Along with the three Vegetation Indices layers, this product also includes layers for the standard deviations of each Vegetation Index; NIR reflectance; three shortwave infrared (SWIR) reflectance; red, blue, and green reflectance; number of pixels, number of pixels used; pixel reliability; average sun angle, and a quality layer. Two low resolution browse images are also available for each VJ113C2 product: EVI and NDVI.