Russian Journal of Earth Sciences Russian Journal of Earth Sciences Russian Journal of Earth Sciences 1681-1208 79402 10.2205/2024ES000921 hscgrg ОРИГИНАЛЬНЫЕ СТАТЬИ ORIGINAL ARTICLES ОРИГИНАЛЬНЫЕ СТАТЬИ The Use of Landsat 8 in Detecting Potential Mineral Zones in West Nusa Tenggara, Indonesia The Use of Landsat 8 in Detecting Potential Mineral Zones in West Nusa Tenggara, Indonesia https://orcid.org/0009-0000-1440-0740 Said Umar Abdulrahim Said Umar Abdulrahim usaid@stu.kau.edu.sa https://orcid.org/0000-0002-0226-0418 Bantan Rashad A. Bantan Rashad A. https://orcid.org/0000-0002-1857-4171 Mannaa Ammar A. Mannaa Ammar A. Taufiq Yasser Taufiq Yasser Department of Marine Geology, Faculty of Marine Sciences, King AbdulAziz University Саудовская Аравия Department of Marine Geology, Faculty of Marine Sciences, King AbdulAziz University Saudi Arabia Department of Marine Geology, Faculty of Marine Sciences, King AbdulAziz University Саудовская Аравия Department of Marine Geology, Faculty of Marine Sciences, King AbdulAziz University Saudi Arabia Department of Marine Geology, Faculty of Marine Sciences, King AbdulAziz University Саудовская Аравия Department of Marine Geology, Faculty of Marine Sciences, King AbdulAziz University Saudi Arabia PT. Sumbawa Timur Mining Индонезия PT. Sumbawa Timur Mining Indonesia 24 12 2024 24 12 2024 24 5 1 10 21 03 2024 29 07 2024 https://rjes.ru/en/nauka/article/79402/view

The remote sensing analysis within the Hu'u District area is known to face a challenge with dense vegetation. The problem affects the accurate reading of spectral reflectance from satellites, influencing the differentiation between potential mineral zones and vegetation. Therefore, this study aims to carry out a remote sensing analysis of densely vegetated areas to differentiate minerals from vegetation and obtain potential mineral zones. The combination band ratios and principal component analysis (PCA) methods are used to acquire potential mineral zones. Furthermore, Landsat 8 images freely available on Google Earth Engine are adopted and the validation is carried out using a drill hole from previous study. The results show that band ratios method cannot distinguish mineral zones from vegetation. However, PCA method can recognize potential mineral zones. This is the result from PCA method with band combination of bands 1, 2, 3, 4, 5, and 6 as the first group and band 2, 4, 5, and 6 as the second group.

The remote sensing analysis within the Hu'u District area is known to face a challenge with dense vegetation. The problem affects the accurate reading of spectral reflectance from satellites, influencing the differentiation between potential mineral zones and vegetation. Therefore, this study aims to carry out a remote sensing analysis of densely vegetated areas to differentiate minerals from vegetation and obtain potential mineral zones. The combination band ratios and principal component analysis (PCA) methods are used to acquire potential mineral zones. Furthermore, Landsat 8 images freely available on Google Earth Engine are adopted and the validation is carried out using a drill hole from previous study. The results show that band ratios method cannot distinguish mineral zones from vegetation. However, PCA method can recognize potential mineral zones. This is the result from PCA method with band combination of bands 1, 2, 3, 4, 5, and 6 as the first group and band 2, 4, 5, and 6 as the second group.

 Landsat 8 Band Ratio Principal Component Analysis Mineral Densely Vegetated Areas Landsat 8 Band Ratio Principal Component Analysis Mineral Densely Vegetated Areas No. No.

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