SPECTRAL REFLECTANCE AND GEOCHEMISTRY ANALYSIS AT COAL MINING SUMP USING SENTINEL-2 IMAGERY

• Main Author: Maghfira, Syiaudi
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/71190
• Institution: Institut Teknologi Bandung

Remote sensing has been used widely to map and assess natural waterbodies quality like river and lake, but mining sump physicochemical characteristics have rarely been studied. This study aims to analyze the relationships between the spectral reflectance and the physic and geochemist properties of water from mining sump. Remote sensing data are mostly in multispectral format, which divide spectral response into discrete bandwidths on different wavelengths, which are limiting the analysis of spectral response only to these bands. Meanwhile, to get continuous information, hyperspectral data is a better choice. To accommodate both, this study used multispectral data from Sentinel-2 imagery and hyperspectral data obtained from reflectance measurements in the laboratory. The research was conducted at the Asam-Asam coal mine in Tanah Laut District, South Kalimantan. Ten water samples were collected from various locations within the mine sumps over two periods representing the rainy and dry season. These samples were analyzed chemical parameters by measuring dissolved ion and metal content, while the physics parameters such as pH and electrical conductivity were measured in the field. Hyperspectral reflectance data were measured from nine samples using a reflectance spectroradiometer under laboratory conditions. The other data used is several precipitate minerals such as ferrihydrite, jarosite, goethite and hematite from the USGS Spectral Library. Hyperspectral data from water samples and Sentinel-2 images, both were preprocessed to improve data quality. The analyzes are based on the spectral response and reflectance value and then are strengthened by simple mathematical analysis. The results show that the water samples are classified as acid mine drainage, which has a low pH and a high electrical conductivity value. The band depth analysis’s spectral signatures revealed several key wavelengths associated with iron oxides with sulfate, alumina, and manganese ions within the visible-near infrared range. Simple mathematical modeling also showed a strong correlation between the physicochemical properties of the water and its spectral reflectance. Furthermore, the distribution of precipitate minerals is mapped using multispectral Sentinel-2 imagery and several types of precipitate minerals have been identified and meticulously mapped. Despite the encouraging results, it is essential to note that the cloud cover, small size of mine sumps and high suspended sediment can pose a challenge in using satellite imagery