Using the band ratio approach, Full-Pixel (SAM and SFF) and SUB-Pixel (MF and SID) methodologies to discover areas with alteration using the Aster sensor
A case study in north westen Iran - Sivardaghi Area
Bibliographic Data
| ID | 12945173 |
|---|---|
| Authors | Majid Bagheri (0000-0001-6259-9723, Islamic Azad University North Tehran Branch), Afshin Ashja Ardalan (Islamic Azad University North Tehran Branch), Alireza Ganji (0000-0002-8670-6869, Islamic Azad University, Lahijan Branch), Saeed Hakimi Asiabar (Islamic Azad University, Lahijan Branch), Mohammad Ali Arin (Islamic Azad University North Tehran Branch) |
| Year | 2023 |
| Volume | 36 |
| Issue | 03 |
| Pages | 422-438 |
| Publication date | 2023-06-30 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Nexo Revista Científica (JOURNAL) |
| Journal identifiers | ISSN: 1818-6742 • E-ISSN: 1995-9516 |
| Publisher | Consejo Nacional de Rectores (PUBLISHER) |
| DOI | 10.5377/nexo.v36i03.16464 |
| OpenAlex | W4385197550 |
| Language | EN |
| References cited | 1 |
ASTER sensor data is among the most potent satellite data accessible for doing geological investigations, with images for the whole earth's surface. In order to test the capability of this sensor to detect places with geochemical alterations, photographs of Mount Seiver Daghi in the western Iranian province of Samal were utilized in this study. This region, which comprises of magmatic and volcanic terrain, is part of the Arsbaran territory and is covered by intrusive masses with alluvial and sedimentary deposits. To conduct this study, an ASTER measuring frame was utilized, which, after performing atmospheric corrections using the internal average relative reflectance (IARR) method of false color composite images and principal component analysis (PCA), was able to differentiate between different lithological units using the Band assignment method, full-pixel methods of spectral angle mapper (SAM) and base spectrum algorithm of spectral feature fitting (SFF) as well as sub-pixel methods of matched filtering. The study demonstrates that the approach of principal component analysis and false color composition is efficient for distinguishing sedimentary rock units from igneous rock units, and its application is suggested for the designated rock units. Due to the lack of spectral characteristics of feldspars and quartz in the short infrared wavelength range, the basic spectrum methods utilized in this work are incapable of identifying such minerals. It is not advised to use these algorithms to distinguish between various magmatic units
Advanced Spaceborne Thermal Emission and Reflection Radiometer · Cartography · Digital elevation model · Feature (linguistics · Geochemistry · Geologic map · Geomorphology · Igneous rock · Mineralogy · Pixel · Principal component analysis · Remote sensing · Satellite · Satellite imagery · Terrain · Thematic Mapper · Atmospheric and Environmental Gas Dynamics · Computer Science · Geochemistry and Geologic Mapping · Remote-Sensing Image Classification · Artificial Intelligence · Geology
| Highly cited | No |
|---|