Abstract
Abstract. Recent developments in the image processing approaches and the availability of multi and/or hyper spectral remote sensing data with high spectral, spatial and temporal resolutions have made remote sensing technique of great interest in investigations of geological sciences. One of the biggest advantage of the application of remote sensing in geology is recognizing the type of unknown rocks and minerals. In this study, an investigation on spectral features of carbonate rocks (i.e. calcite, dolomite, and dolomitized calcite) were done in terms of main absorptions, the reasons of those absorptions and comparison of these absorption with Johns Hopkins University (JHU) spectral library and laboratory spectra of Analytical Spectral Devices (ASD) instrument. For this purpose, we used the VNIR and SWIR bands of ASTER and OLI datasets. Finally, we applied the Spectral Analyst Algorithm in order to comparison between the obtained spectra from ASTER dataset and carbonate spectra of JHU spectral library.
Highlights
The first earth observation satellite was launched into space by the United States on July 23, 1972, named ERTS which later renamed Landsat 1
This study aims to compare the capability of Operational Land Imager (OLI) and ASTER sensors in discriminating various carbonate minerals
To carry out this study, rock samples have been collected in the study area and their spectra were measured by an Analytical Spectral Devices (ASD) instrument
Summary
The first earth observation satellite was launched into space by the United States on July 23, 1972, named ERTS which later renamed Landsat 1. During the past several years, different satellites have been launched into the space that advanced sensors were embedded in them. These days, the application of satellite imagery data have an important role in recognizing and separating different rock units. Remote sensing can study and analyse the spectral and spatial connection of different geological phenomena from a so far distance. The main advantages of the remote sensing technique in geologic applications are providing information at different spectral and spatial resolutions, wide coverage, recognizing and separating rock units, preparation of the hazard maps, faults and fractures maps (Gupta, 2017).
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