Enhanced Vegetation Index (EVI) parameter data products from Landsat 5, Landsat 8 MODIS and the Visible Infrared Imaging Radiometer Suite (VIIRS), Colorado River Delta, Mexico
Data for journal manuscript: Application and Comparison of the MODIS-Derived Enhanced Vegetation Index to VIIRS, Landsat 5 TM and Landsat 8 OLI Platforms: A Case Study in the Arid Colorado River Delta, Mexico
Dates
Publication Date
2019-07-31
Start Date
2001
End Date
2016
Citation
Jarchow, C.J., and Nagler, P.L., 2019, Enhanced Vegetation Index (EVI) parameter data products from Landsat 5, Landsat 8 MODIS and the Visible Infrared Imaging Radiometer Suite (VIIRS), Colorado River Delta, Mexico: U.S. Geological Survey data release, https://doi.org/10.5066/P9UMMJ9S.
Summary
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 [...]
Summary
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.
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Related External Resources
Type: Related Primary Publication
Application and Comparison of the MODIS-Derived Enhanced Vegetation Index to VIIRS, Landsat 5 TM and Landsat 8 OLI Platforms: A Case Study in the Arid Colorado River Delta, Mexico
The purpose of these data are to assess the relationship between MODIS, Landsat and VIIRS-derived EVI data for corresponding time periods and geographic locations in support of multi-sensor continuity and remote sensing-based biophysical parameter validation. We acquired and compared temporally and geographically-coincident early, mid and late growing season EVI scenes of all four platforms from 2001–2016 for the lower Colorado River Delta (CRD) in Mexico. Although MODIS and VIIRS are typically applied to significantly larger areas, we purposefully chose a smaller area for our comparison, as the application of MODIS data to such scales has increased in recent years and this allowed us to more easily control the effect of extraneous variables. The CRD is also well characterized by a variety of land cover conditions (i.e., soil and vegetation), allowing for a comparison across different surface types, vegetation conditions and scales. We further sub-divided our analysis by sensor, size (area) and land cover type and provided band-specific comparisons to help explain differences between these key sensors and their respective data records.
Rights
The author(s) of these data request that data users contact them regarding intended use and to assist with understanding limitations and interpretation. Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data for other purposes, nor on all computer systems, nor shall the act of distribution constitute any such warranty.
