第34回日本情報地質学会講演会 講演要旨集 007-008頁 2023年

Integration of a satellite image with geologic and topographic information
for delineating geothermal potential areas in East Java Island(Indonesia)
Tedi Atmapradhana*, Heru Berian Pratama* and Katsuaki Koike**Department of Urban Management, Graduate School of Engineering, Kyoto University, Katsura C1-2,
Kyoto 615-8540, Japan.
E-mail: tedi.atmapradhana.83a@st.kyoto-u.ac.jp

Key words: Land cover, Digital Elevation Model, Geothermal, Landsat-8 image

1. Introduction

Indonesia's unique location at the convergence ofmultiple tectonic plates has made it a prime candidatefor geothermal energy utilization, with a total
geothermal potential estimated at 28,910 mW, drawn
from 312 fields across several islands (Pambudi, 2018).
Surface manifestations such as hot springs, mud pools,
hydrothermal alteration, fumaroles, and sinter silica
indicate potential geothermal energy sources. These
manifestations reveal higher temperatures than theirsurrounding environments, making them easily
identified as anomalies. The main objective of thisresearch project is to identify the thermal anomalies andutilize the Landsat 8 OLI/TIRS imagery to identify areas
with geothermal manifestations as indicators ofgeothermal activity in East Java Indonesia. Combining
TIR (Thermal Infrared) remote sensing with geologicalanalysis and understanding geothermal mechanisms isan accurate and efficient approach to geothermal area
detection (Qin et al., 2011). The main reason for thisstudy is to assist and support the Indonesian
government's efforts to optimize the utilization ofgeothermal energy, especially for electricity generation of
7,242 mW by 2025.

2. Study Area and Methodology

2.1. Study area and data
This research focuses on the province of East Java as
its study area. It is geographically located between 111°0'- 114°4' East Longitude and 7°12' - 8°48' South Latitudeand has an area of approximately 48,040 Km2 (Figure 1).
In general, East Java can be divided into two main parts,
namely mainland East Java with a larger proportion ofalmost 90% of the entire area of East Java Province, andthe Madura Islands area which is only about 10%. The
province has the largest installed power generation
capacity in Indonesia with a total of 10,572 mW or 14.5%of the power generation in Indonesia (Sidik andHarmoko, 2022). The datasets used in this method are
multisensor image data from Landsat 8 Operational
Land Imager (OLI) and Thermal Infrared Sensor (TIRS),
geological data, and digital elevation model (DEM) data.

Figure 1. Landsat-8 image covering the study area

2.2. Methodology
The analysis of the study area's land cover, vegetation
density, and land surface temperature (LST) relied ondata obtained from the Landsat 8 satellite. The land
cover was determined by subjecting the satellite imageto a classification process, which utilized a supervised
method employing a support vector machine module. To
assess vegetation density, the NDVI (NormalizedDifference Vegetation Index) algorithm was applied. Thisalgorithm calculates the index by comparing thenear-infrared and red bands of the satellite image,enabling the quantification of vegetation density basedon the variation between these spectral bands.
Furthermore, the land surface temperature map wasgenerated using specific algorithms, namely the LST
algorithm and the LSE (Land Surface Emissivity)algorithm, the researchers were able to detect
temperature anomalies that may indicate the presence ofgeothermal energy. These algorithms utilized thethermal information extracted from band 10 and band 11of the satellite image, however, not all of these anomalies
are indicators of geothermal energy. The above researchflow is summarized in Figure 2.

8geothermal manifestations in the southwestern part of
East Java Province. The similarities in fault formations
between this region and the northwest area, as well asaround Mt Arjuno-Welirang, further support theprospects of significant geothermal resources in theseareas. These findings provide valuable guidance for
future geothermal exploration efforts, highlighting
specific regions within East Java Province that holdpromising prospects for future geothermal energy
development.

4.

Figure 2. Research flowchart to investigate thegeothermal potential area.

3.

Results and Discussion

The collected data were processed into thematic maps
with the projection system Universal Transverse
Mercator (UTM) zone 49S. Geothermal potential zone
maps were delineated by employing a combination of key
factors and data overlays. These factors include land useand land cover (LULC), land elevation, normalized
difference vegetation index (NDVI), and land surface
temperature (LST). By integrating these datasets, alongwith the combination of fault line data, lineamentdensity, and geothermal manifestation locations,comprehensive geothermal potential zone maps weregenerated as shown in Figure 3.
Based on generated geothermal potential zone map
reveals a distinct pattern of geothermal manifestations
predominantly clustered in mountainous regions.
Notable locations exhibiting geothermal activity include
Mt Lawu, Mt Arjuno, Mt Pandan, Mt Argopuro, and Mt
Wilis. These mountainous areas emerge as hotspots ofgeothermal potential, suggesting favorable conditions forgeothermal resources exploration and development.
Furthermore, a closer examination of the density patternof fault lines indicates a high likelihood of encountering

Figure 3. Potential geothermal zone map.

Summary

Even though TIR remote sensing is undoubtedly avaluable tool, it does possess certain limitations when it
comes to geothermal resource exploration andmonitoring. Consequently, relying exclusively on TIRremote sensing would prove inadequate for effectively
assessing and monitoring geothermal resources. It
becomes imperative, therefore, to integrate additional
techniques and methodologies that can complement andaugment the capabilities of TIR remote sensing. By
doing so, a more comprehensive and precise assessmentof geothermal reservoirs can be achieved. Incorporating
diverse approaches will contribute to a more holistic
approach to geothermal exploration and monitoring,leading to improved decision-making and resource
management in this study.

References

Pambudi, N. A. (2018) Geothermal power generation inIndonesia, a country within the ring of fire: Current status,
future development and policy. Renewable and Sustainable
Energy Reviews, 81, pp. 2893–2901.
https://doi.org/10.1016/j.rser.2017.06.096.
Qin, Q., Zhang, N., Nan, P., and Chai, L. (2011) Geothermalarea detection using Landsat ETM+ thermal infrared dataand its mechanistic analysis—A case study in Tengchong,China. International Journal of Applied Earth Observation
and Geoinformation, 13(4), pp. 552–559.
https://doi.org/10.1016/j.jag.2011.02.005
Sidik, M. and Harmoko, U. (2022) Potensi Energi Panas Bumi
di Jawa Timur Sebagai Energi Alternatif Pengganti Energi
Fossil. Jurnal Energi Baru dan Terbarukan, 3(1), pp. 49–60.
https://doi.org/10.14710/jebt.2022.13395.