Mendeteksi Anomali Termal Pada Prospek Panas Bumi Lahendong Menggunakan Aster TIR dan Landsat 8

Mohammad Aftaf Muhajir (Master of Science in Information Technology for Natural Resources Management, Faculty of Mathematics and Natural Resources, IPB University, IPB Darmaga Campus, Bogor, 16680, Indonesia)
Kudang Boro Seminar (Department of Mechanical and Biosystem Engineering, Faculty of Agricultural Technology, IPB University, IPB Darmaga Campus, Bogor, 16680, Indonesia)
Leopold Oscar Nelwan (Department of Mechanical and Biosystem Engineering, Faculty of Agricultural Technology, IPB University, IPB Darmaga Campus, Bogor, 16680, Indonesia)

Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management)
Vol 13 No 3 (2023): Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (JPSL)

This study intends to determine geothermal anomalies area using remote sensing data in the form of Landsat 8 and ASTER satellite imagery data which have Thermal Infrared Sensor (TIRS). Through pre-processing like georeferencing, radiometric calibration, and atmospheric correction, the Landsat 8 TIRS and ASTER data were wont to invert the land surface temperature of the study area during the daytime and night time using the inversion of planck function and emissivity separation algorithm. Result shows the land surface temperatures during daytime and night time of four natural land cover —water, vegetation, built up area, and bare soil—were classified and analyzed. According to the results, vegetation and bare soil show relatively thermal anomalies during the day and comparatively cold anomalies during the night. Otherwise water shows relatively cold anomalies during the day and relatively thermal anomalies during the night. Meanwhile built up area shows relatively thermal anomalies during the day and cold anomalies during the night. Superimposed and calculating mean of the night and day surface temperature can adequately eliminate the relatively cold/thermal anomalies of land cover caused by solar radiation, thus effectively highlighting geothermal anomalies. Thus, Nine geothermal anomalies areas were successfully extracted.