The Effectiveness of Hydrothermal Alteration Mapping based on Hyperspectral Data in Tropical Region

5th ITB International Geothermal Workshop

Muhammad, R.R.D.^1 ; Saepuloh, A.^1,2

Geothermal Technology Study Program, Faculty of Mining and Petroleum Engineering, Institut Teknologi Bandung, Indonesia^1

Geology Engineering Study Program, Faculty of Earth Sciences and Technology, Institut Teknologi Bandung, Indonesia^2

关键词: High spectral resolution;    Hydrothermal alterations;    Hyperspectral remote sensing;    Multi-spectral data;    Multispectral sensors;    Reflectance spectrum;    Spectral angle mappers;    Surface manifestations;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/42/1/012005/pdf
DOI  :  10.1088/1755-1315/42/1/012005

来源: IOP

【 摘 要 】

Hyperspectral remote sensing could be used to characterize targets at earth's surface based on their spectra. This capability is useful for mapping and characterizing the distribution of host rocks, alteration assemblages, and minerals. Contrary to the multispectral sensors, the hyperspectral identifies targets with high spectral resolution. The Wayang Windu Geothermal field in West Java, Indonesia was selected as the study area due to the existence of surface manifestation and dense vegetation environment. Therefore, the effectiveness of hyperspectral remote sensing in tropical region was targeted as the study objective. The Spectral Angle Mapper (SAM) method was used to detect the occurrence of clay minerals spatially from Hyperion data. The SAM references of reflectance spectra were obtained from field observation at altered materials. To calculate the effectiveness of hyperspectral data, we used multispectral data from Landsat-8. The comparison method was conducted by comparing the SAM's rule images from Hyperion and Landsat-8, resulting that hyperspectral was more accurate than multispectral data. Hyperion SAM's rule images showed lower value compared to Landsat-8, the significant number derived from using Hyperion was about 24% better. This inferred that the hyperspectral remote sensing is preferable for mineral mapping even though vegetation covered study area.