Abstract
Landsat 8 is the most recent generation of Landsat satellite missions that provides remote sensing imagery for earth observation. The Landsat 7 Enhanced Thematic Mapper Plus (ETM+) images, together with Landsat-8 Operational Land Imager (OLI) and Thermal Infrared sensor (TIRS) represent fundamental tools for earth observation due to the optimal combination of the radiometric and geometric images resolution provided by these sensors. However, there are substantial differences between the information provided by Landsat 7 and Landsat 8. In order to perform a multi-temporal analysis, a cross-comparison between image from different Landsat satellites is required. The present study is based on the evaluation of specific intercalibration functions for the standardization of main vegetation indices calculated from the two Landsat generation images, with respect to main land use types. The NDVI (Normalized Difference Vegetation Index), NDWI (Normalized Difference Water Index), LSWI (Land Surface Water Index), NBR (Normalized Burn Ratio), VIgreen (Green Vegetation Index), SAVI (Soil Adjusted Vegetation Index), and EVI (Enhanced Vegetation Index) have been derived from August 2017 ETM+ and OLI images (path: 188; row: 32) for the study area (Basilicata Region, located in the southern part of Italy) selected as a highly representative of Mediterranean environment. Main results show slight differences in the values of average reflectance for each band: OLI shows higher values in the near-infrared (NIR) wavelength for all the land use types, while in the short-wave infrared (SWIR) the ETM+ shows higher reflectance values. High correlation coefficients between different indices (in particular NDVI and NDWI) show that ETM+ and OLI can be used as complementary data. The best correlation in terms of cross-comparison was found for NDVI, NDWI, SAVI, and EVI indices; while according to land use classes, statistically significant differences were found for almost all the considered indices calculated with the two sensors.
Highlights
In recent decades, an increasing number of satellite systems for Earth observation have provided large datasets of remote sensed imagery and indices, contributing to monitoring environmental changes at both regional and global scales
In Xu and Guo [27], the cross-comparison between the Normalized Difference Vegetation Index (NDVI) extracted from Landsat 8 and Landsat 7 images, showed larger differences between NDVI calculated from the two generations of Landsat in lower vegetation covered areas; the difference decreases at higher vegetation cover
The differences between Landsat 7 ETM+ and Landsat 8 Operational Land Imager (OLI) spectral responses have only been analyzed on a single derived vegetation index such as the NDVI, while in the present study, we extended the analysis to seven different indices and different land use types in order to achieve a more comprehensive analysis between the two sensors
Summary
An increasing number of satellite (and sensor) systems for Earth observation have provided large datasets of remote sensed imagery and indices, contributing to monitoring environmental changes at both regional and global scales. Despite their increasing availability, this information cannot be compared due to slight differences among sensors, and it is essential to define standards for cross-device validation, as well as reliable algorithms for dataset difference reductions [1,2]. The cross-comparison analysis covers most of the different optical- and radar-based satellite systems currently in use for earth observation. In Xu and Guo [27], the cross-comparison between the Normalized Difference Vegetation Index (NDVI) extracted from Landsat 8 and Landsat 7 images, showed larger differences between NDVI calculated from the two generations of Landsat in lower vegetation covered areas; the difference decreases at higher vegetation cover (i.e., the NDVI values increase)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
