Remote Sensing Satellite Imagery and In-Situ Data for Identifying Geothermal Potential Sites: Jaboi, Indonesia

*Muhammad Isa scopus  -  Physics Department, Universitas Syiah Kuala, Indonesia
Dwiky Pobri Cesarian  -  School of Physics, Universiti Sains Malaysia 11800, Pulau Penang, Malaysia, Malaysia
Ismail Ahmad Abir  -  School of Physics, Universiti Sains Malaysia 11800, Pulau Penang, Malaysia, Malaysia
Elin Yusibani  -  Department of Physics, Universitas Syiah Kuala 23111, Banda Aceh, Indonesia, Indonesia
Muhammad Syukri Surbakti  -  Department of Physics, Universitas Syiah Kuala 23111, Banda Aceh, Indonesia, Indonesia
Muksin Umar  -  Department of Physics, Universitas Syiah Kuala 23111, Banda Aceh, Indonesia, Indonesia
Received: 28 Jan 2020; Revised: 15 Feb 2020; Accepted: 19 Feb 2020; Published: 15 Jul 2020; Available online: 5 May 2020.
Open Access Copyright (c) 2020 International Journal of Renewable Energy Development
License URL: http://creativecommons.org/licenses/by-sa/4.0

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Article Info
Section: Original Research Article
Language: EN
In Vol 9, No 2 (2020): July 2020
Statistics: 420 209
Abstract

Remote sensing makes it possible to map potential geothermal site for a large area effectively using thermal infrared. The purpose of the present research is to overlay ground temperature, resistivity and satellite retrieved temperature in identifying geothermal potential site in Jaboi, Sabang-Indonesia. The data of acquisition of the DEM imagery was January 3rd, 2009 and the Landsat 8 imagery is July 18th, 2017. The satellite data were applied to extract the land surface temperature and land classification across. Two supporting data in situ were used to validate the results from remote sensing. First dataset was ground temperature measurements with total 114 points and second dataset was vertical electrical sounding (VES) with total of 51 points. Satellite, VES and ground temperature data were processed and analysed using the Envi 5.3, PCI Geomatica 2016 and ArcMap 10.4. The results from each data were integrated to produce a map shows geothermal potential. Its integration produced four areas which were considered to have high geothermal potential. However, these areas vary in term of the clustering of the features of interest, for example lineament and drainage density of the area, high temperature in the surface area, fault existence and low resistivity subsurface. All the features must take into consideration to rank potential area which has higher potential. Finally, a map of geothermal potential across were successfully created as an insight for future reference. ©2020. CBIORE-IJRED. All rights reserved

Keywords: Geothermal; energy; temperature; satellite data; electricity.

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