LINEAMENT DENSITY INFORMATION EXTRACTION USING DEM SRTM DATA TO PREDICT THE MINERAL POTENTIAL ZONES

Utilization of remote sensing in geology is based on some identification of main parameters. They were the relief or morphology, flow patterns, and lineament. So it was necessary to study extraction method based on those parameters. This study aimed to obtain lineament density zone in the Geumpang area, Aceh, associated with mineral resource potential. Information of lineament density using remote sensing data was expected to help solve the problems that arised in the activities of early exploration, the difficulty of finding the prospect areas, so that the activities of pre-exploration always required a wide area and required a long time to determine the location of mineral prospect areas, it would have a direct impact on the financial of exploration activities. The used data was Landsat 8 and DEM SRTM of 30 m. The used method was processing of shaded relief on DEM data with the azimuth angle 0o, 45o, 90o, and 135o, then the result of hill shade process was done overlay, so DEM seen from all different azimuth angles. The results of the overlay were processed using the algorithm LINE with parameters such as the radius of the filter in pixels (RADI) 60, the threshold for edge gradient (GTHR) 120, the threshold for the curve length (LTHR) 100, the threshold for line fitting error (FTHR) 3, threshold for angular (ATHR) 30, and the threshold for linking distance (DTHR) 100. Vector lineament data from LINE algorithm process then performed density analysis to obtain lineament density zoning. Results from the study showed that the area has a high density lineament associated with mineral potency, so it was useful for exploration activities to minimize the survey area

Koreksi Radiometrik Data Citra Landsat Menggunakan Semi Automatic Classification Plugin Pada Software QGIS = Radiometric Corrections of Landsat Image Using Semi Automatic Classification Plugin on Software QGIS

Data Landsat-8 dikoreksi radiometrik menggunakan koreksiTop of Atmosphere (ToA) yang meliputi ToA reflektansi dan koreksi matahari. Koreksi ToA reflektansi dilakukan dengan mengkonversi nilai Digital Number ke nilai reflektansi. Koreksi ToA adalah koreksi pada citra yang dilakukan untuk menghilangkan distorsi radiometrik yangdisebabkan oleh posisi matahari. Posisi matahari terhadap bumi berubah bergantung pada waktu perekaman dan lokasi obyek yang direkam. Data citra satelit yang digunakan adalah citra satelit Landsat 8 tahun 2014 dan 2015, citra Landsat 7 tahun 2000, citra Landsat 5 tahun 2009, 2010 dan 2011 wilayah Aceh bagian selatan. Perangkat lunak yangdigunakan adalah QGIS 2.8.1 yang merupakan Free and Open Source Software.Reflectance correction is done by converting the value of Digital Number to the reflectance values. Top of Atmosphere (TOA)correction is a correction to the image radiometric to eliminate distortions caused by the position of the sun. The position of the sun to the earth is changed depending on the recording time and location of the object to berecorded. Satellite image data used is Landsat-8 satellite images in 2014 and 2015, Landsat 7 in 2000, Landsat 5 in 2009, 2010 and 2011 in South Aceh region. The software used is QGIS 2.8.1 is a Free and Open Source Software.hlm. 105-11

Lineament Density Information Extraction Using Dem Srtm Data To Predict The Mineral Potential Zones

Utilization of remote sensing in geology is based on some identification of main parameters. They were the relief or morphology, flow patterns, and lineament. So it was necessary to study extraction method based on those parameters. This study aimed to obtain lineament density zone in the Geumpang area, Aceh, associated with mineral resource potential. Information of lineament density using remote sensing data was expected to help solve the problems that arised in the activities of early exploration, the difficulty of finding the prospect areas, so that the activities of pre-exploration always required a wide area and required a long time to determine the location of mineral prospect areas, it would have a direct impact on the financial of exploration activities. The used data was Landsat 8 and DEM SRTM of 30 m. The used method was processing of shaded relief on DEM data with the azimuth angle 0o, 45o, 90o, and 135o, then the result of hill shade process was done overlay, so DEM seen from all different azimuth angles. The results of the overlay were processed using the algorithm LINE with parameters such as the radius of the filter in pixels (RADI) 60, the threshold for edge gradient (GTHR) 120, the threshold for the curve length (LTHR) 100, the threshold for line fitting error (FTHR) 3, threshold for angular (ATHR) 30, and the threshold for linking distance (DTHR) 100. Vector lineament data from LINE algorithm process then performed density analysis to obtain lineament density zoning. Results from the study showed that the area has a high density lineament associated with mineral potency, so it was useful for exploration activities to minimize the survey area.p.67-74 : ilus. ; 28 c

Indonesia ALOS pilot project : Kerjasama Internasional LAPAN dan JAXA (Jepang), untuk berbagai aplikasi inderaja

Hal.48-52: ilus.: 28 c

Analisa Profil Pertumbuhan Kelapa Sawit Dengan Menggunakan Data Landsat 8 (Studi Kasus : Tanah Laut, Kalimantan Selatan)

Hal.850-85

Kerjasama Airborne SAR PiSAR-L2 : potensi pemanfaatan data SAR untuk pemantauan wilayah Indonesia

Hal.54-58 : ilus. ; 28 c

Joint use of Sentinel-2 and Sentinel-1 data for rapid mapping of volcanic eruption deposits in Southeast Asia

Indonesia and Papua New Guinea (PNG) have 97 active volcanoes with high concentration of human life in the very close proximity to them. In case of a volcanic eruption, provision of detailed information on affected regions is very crucial to support rescue and humanitarian relief organizations. In this paper, we present a semi-automated unsupervised knowledge-based region growing procedure that utilizes Synthetic Aperture Radar (SAR) data, from Sentinel-1, and optical data, from Sentinel-2, for mapping land surface changes after volcanic eruptions. With initial seed points, being placed on active volcano vents and areas affected by thermal anomalies (derived from Sentinel-2), the region growing procedure considers interferometric coherence data in unvegetated sites, and radar brightness and polarimetric decomposition features at vegetated sites. We selected five eruptive events that occurred between 2018 and 2021 at the Indonesian volcanoes of Karangetang, Semeru, Sinabung and at Ulawun Volcano on PNG. The eruption patterns varied with respect to duration, spatial extent and ejected volcanic materials. The results indicated that usage of radar brightness features with interferometric coherence already gives good change delineation. However, in the Ulawun test case, where heavy ash and scoria fall occurred, the addition of polarimetric decomposition features substantially improved the output accuracy due to the improved detection of ash deposits. The presented change detection method is straight forward to implement, and will strongly improve rapid mapping activities during as well as after major volcano eruptions