Geothermal Estimation In Pantar, Nusa Tenggara Timur Based On Land Surface Temperature
Keywords:
Estimation, Geothermal, Land Surface Temperature, Magnetotelluric, PantarAbstract
Pantar Island in East Nusa Tenggara is one of the regions located on the Pacific Ring of Fire and is part of the active volcanic zone of Mount Sirung. This condition gives Pantar great geothermal potential, marked by surface manifestations in the form of hot springs and hot soil. However, the utilisation of geothermal energy in this region is still not optimal due to limited research specifically identifying prospective areas, coupled with high investment and exploration costs. This study aims to estimate geothermal areas on Pantar Island through analysis of surface temperature anomalies (Land Surface Temperature/LST) using a remote sensing approach. The data used are Landsat 9 images with Thermal Infrared Sensor (TIRS) bands. Anomalies were determined using the classify method, which groups temperature values into fewer categories, and the quantile method, which divides the data range into equal numbers of data. In general, temperatures above 37.8 °C are considered LST anomalies. The analysis results show four areas of surface temperature anomalies, with indications of geothermal areas in the northeast of Mount Sirung, covering several manifestations. These findings are expected to provide preliminary information on the geothermal potential of Pantar Island, which can serve as a basis for recommendations for further research and planning for the utilisation of geothermal energy that is economically viable, clean, and sustainable.
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Alhamri, R. Z., & Suryani, E. (2016). Kajian Potensi Energi Panas Bumi Sebagai Alternatif Pembangkit Energi Listrik Terbarukan: Sebuah Framework Sistem Dinamik. In Sisfo (Vol. 05, Issue 05, pp. 542–554). https://doi.org/10.24089/j.sisfo.2016.03.006
Andini, D., Lepong, P., & Natalisanto, A. I. (2020). Identifikasi Kawasan Zona Panas Bumi (Geothermal) Di Daerah X Menggunakan Metode Magnetotellurik 1*. Jurnal Geosains Kutai Basin, 3(1), 1–8.
Arafat, R. (2019). Model Konseptual Sistem Panasbumi Non-Vulkanik Di Lapangan “Tersier”, Sulawesi Barat, Menggunakan Metode Magnetotellurik. July 2019. http://eprints.upnyk.ac.id/19716/%0Ahttp://eprints.upnyk.ac.id/19716/4/5. DAFTAR ISI.pdf
Augusty, D. G., Bagaskara, M. F., & Oktaviani, A. D. (2023). Analisis Potensi Panas Bumi Pada Daerah G. Karang, Banten, Menggunakan Metode Penginderaan Jauh. JURNAL TEKNIK GEOLOGI : Jurnal Ilmu Pengetahuan Dan Teknologi, 5(2), 15. https://doi.org/10.30872/jtgeo.v5i2.5455
Bunga Fathya, A., Nugraha, H., Gusti Ranti, A., & Wahyuningsih, R. (2023). Analisis Anomali Land Surface Temperature Menggunakan Citra Satelit Landsat 8 Untuk Identifikasi Prospek Panas Bumi Gunung Sirung Di Kabupaten Alor, Provinsi Nusa Tenggara Timur. Buletin Sumber Daya Geologi, 18(1), 37–54. https://doi.org/10.47599/bsdg.v18i1.367
Clarissa, G. D., Bujung, C. A. N., & Silangen, P. M. (2020). Identifikasi Daerah Prospek Panas Bumi Berdasarkan Sebaran Temperatur Dan Stress Vegetasi Menggunakan Citra Landsat 8 Di Daerah Gunung Tampusu. Jurnal FisTa : Fisika Dan Terapannya, 1(2), 88–96. https://doi.org/10.53682/fista.v1i2.96
Cumming, W., & Mackie, R. (2010). Resistivity Imaging of Geothermal Resources Using 1D , 2D and 3D MT Inversion and TDEM Static Shift Correction Illustrated by a Glass Mountain Case History. Proceedings World Geothermal Congress 2010, April, 1–10.
ESDM, K. E. dan S. D. M. (2025). Kementrian Energi dan Sumber Daya Mineral. https://www.esdm.go.id/
Faridah, N. S. A., & Krisbiantoro, A. (2014). Analisis distribusi temperatur permukaan tanah wilayah potensi panas bumi menggunakan teknik penginderaan jauh di Gunung Lamongan, Tiris- Probolinggo, Jawa Timur. Berkala Fisika, 17(2), 67–72.
Fildzah Hakim, A., Krismadiana, Sholihah, F., & Artikel, I. (2022). Indonesian Journal of Conservation. Indonesian Journal of Conservation, 2(11), 71–77. https://doi.org/10.15294/ijc.v11i2.40599
Gemitzi, A., Dalampakis, P., & Falalakis, G. (2021). Detecting geothermal anomalies using Landsat 8 thermal infrared remotely sensed data. International Journal of Applied Earth Observation and Geoinformation, 96, 102283. https://doi.org/https://doi.org/10.1016/j.jag.2020.102283
Gorr, W. L., & Kurland, K. S. (2020). GIS tutorial For ArcGIS Desktop 10.8. ESRI Press.
Hadi, M. N., & Kusnadi, D. (2016). Survei Geologi dan Geokimia Daerah Panas Bumi Pulau Pantar, Kabupaten Alor, Nusa Tenggara Timur. 15(2), 1–23.
Hashim, M., Pour, A. B., Shehu, K., & Bahru, J. (2017). Review of Geothermal Mapping Techniques Using. Science World Journal, 12(4), 72–82. www.scienceworldjournal.org
Lestari, N. M. D. P., & Jusfarida. (2021). Pendugaan Manifestasi Panas Bumi Menggunakan Citra Landsat 8 Berdasarkan Analisis Kelurusan dan Suhu Permukaan Tanah (Studi Kasus: Arjuno-Welirang). In Jurnal Sumberdaya Bumi Berkelanjutan (Vol. 3, Issue 1, pp. 271–276).
Marry, R. T., Armawi, A., Hadna, A. H., & Pitoyo, A. J. (2017). Panas Bumi Sebagai Harta Karun Untuk Menuju Ketahanan Energi. Jurnal Ketahanan Nasional, 23(2), 217–237.
Muhammad, A. K., & Adhitia, I. (2021). Studi Potensi Panas Bumi Di Wilayah Kabupaten Bogor Ditinjau Dari Geologi Dan Geokimia. Jurnal Teknik | Majalah Ilmiah Fakultas Teknik UNPAK, 22(1), 27–37. https://doi.org/10.33751/teknik.v22i1.3733
NASA. (2013). Landsat 9. https://landsat.gsfc.nasa.gov/satellites/landsat-9/
Nurhadi, M., & Kusnadi, D. (2015). Survei Geologi Dan Geokimia Daerah Panas Bumi Pantar Kabupaten Alor, Provinsi Nusa Tenggara Timur. Prosiding Hasil Kegiatan Lapangan Pusat Sumber Daya Geologi Tahun Anggaran 2015.
Pearson, C. (2006). On the Relation between Relations. 86–94. https://doi.org/10.5840/cpsem20069
Permana, L. A., Nugraha, H. S., & Sukaesih. (2021). Analisis Citra Satelit Landsat 8 Dan Demnas Untuk Identifikasi Prospek Panas Bumi Di Kabupaten Aceh Tengah, Provinsi Aceh. Buletin Sumber Daya Geologi, 16(3), 166–184. https://doi.org/10.47599/bsdg.v16i3.322
Primastika, A. A., Fadrian, D. F., Zani, F. R., & Permana, N. R. (2023). Identification of Mount Sirung Geothermal Potential based on Land Surface Temperature and 3D Gravity Model. Jurnal Geocelebes, 7(2), 117–129. https://doi.org/10.20956/geocelebes.v7i2.23759
Qin, Q., Zhang, N., Nan, P., & Chai, L. (2011). Geothermal area detection using Landsat ETM+ thermal infrared data and its mechanistic analysis-A case study in Tengchong, China. International Journal of Applied Earth Observation and Geoinformation, 13(4), 552–559. https://doi.org/10.1016/j.jag.2011.02.005
Rahadinata, T., Takodama, I., & Zarkasyi, A. (2019). Penerapan Koreksi Topografi Pada Data Magnetotelurik Dan Analisis Data Gaya Berat Dalam Interpretasi Daerah Panas Bumi Pantar, Kabupaten Alor, Provinsi Nusa Tenggara Timur. Buletin Sumber Daya Geologi, 14(3), 156–168. https://doi.org/10.47599/bsdg.v14i3.290
Ramadhan, R. F., & Saputra, R. A. (2021). Identifikasi Area Prospek Panas Bumi Menggunakan Integrasi Citra Landsat 8 OLI/TIRS dan DEM : Studi Kasus Batu Bini, Kalimantan Selatan. Majalah Ilmiah Swara Patra, 11(2), 37–50. https://doi.org/10.37525/sp/2021-2/294
Sugiyono. (2014). Metode penelitian bisnis: pendekatan kuantitatif, kualitatif, kombinasi, dan R&D.
Syawalina, R. K., Ratihmanjari, F., & Saputra, R. A. (2022). Identification of The Relationship Between LST And NDVI On Geothermal Manifestations In A Preliminary Study Of Geothermal Exploration Using Landsat 8 OLI/TIRS Imagery Data Capabilities: Case Study Of Toro, Central Sulawesi. PROCEEDINGS, 47th Workshop on Geothermal Reservoir Engineering, 1–8.
Tian, B., Wang, L., Kashiwaya, K., & Koike, K. (2015). Combination of well-logging temperature and thermal remote sensing for characterization of geothermal resources in Hokkaido, northern Japan. Remote Sensing, 7(3), 2647–2667. https://doi.org/10.3390/rs70302647
USGS. (2025). Earth Explorer. https://earthexplorer.usgs.gov/
Yatimas Murni, L., Yuliara, I. M., & Windaryoto, W. (2021). Distribusi Land Surface Temperature (LST) Menggunakan Metode Spasial Berdasarkan Citra Landsat 8 di Kabupaten Manggarai Nusa Tenggara Timur Pada Periode Juni-Juli 2015-2019. Buletin Fisika, 24(1), 1. https://doi.org/10.24843/bf.2023.v24.i01.p01.
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Data Availability Statement
All relevant data supporting the findings of this study are available within the article
