Year: 2024 | Month: June | Volume: 11 | Issue: 6 | Pages: 68-78
DOI: https://doi.org/10.52403/ijrr.20240609
Geothermal Prospect Zone Estimation Based on Landsat 8 Satellite Imagery (Case Study Around Gedongsongo)
Alma Izzatinavia1, Tony Yulianto1, M. Irham Nurwidyanto1
1Department of Physics, Faculty of Science and Mathematics, Diponegoro University, Semarang Indonesia.
Corresponding Author: Tony Yulianto
ABSTRACT
Indonesia possesses significant geothermal potential due to its geographical location situated among three active tectonic plates. The vast geothermal potential has led to a portion of it being underexploited due to the difficulty in identifying the exact locations field of geothermal potential. Hence, exploration activities are required to discover these potential geothermal sites without direct field explorations. The geothermal potential that needs further development lies in the Gedongsongo area, District, Semarang, Central Java, specifically on the southern slopes of Mount Ungaran. This research aims to map the surface temperature and estimate geothermal potential areas in the study area using Landsat 8 satellite image data. The analysis of surface temperature mapping can utilize remote sensing by leveraging thermal images from satellite data using the Normalized Difference Vegetation Index (NDVI) method, Land Surface Temperature (LST) method, and Fault Fracture Density (FFD) method. The overlay results of these three parameters produced a geothermal potential map in the areas of Candi Village and Kenteng Vilage, indicating several areas predicting geothermal potential. In Candi Village, three potential geothermal areas were identified with high and very high potential levels, having a moderate lineament density ranging from 1.07 to 1.8 km2, with ground surface temperatures ranging from 21 to 26 °C. For the potential areas in Kenteng Village, two potential geothermal areas were found with high and very high potential levels, showing a density of 1.8 to 5.78 km2, and ground surface temperatures ranging from 21 to 26 °C.
Keywords: Gedongsongo, remote sensing, vegetation density, land surface temperature, fracture density
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