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Geothermal energy that is renewable, reliable, and environmentally friendly is one of the most important energies. Based on Peraturan Pemerintah No. 79 tahun 2014 about the National Energy Policy, the use of geothermal energy must reach 23% by 2025. This regulation is in line with the goal of seven...

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Main Author: Candra Dewi, Wahyuni
Format: Final Project
Language:Indonesia
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Online Access:https://digilib.itb.ac.id/gdl/view/55877
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:55877
spelling id-itb.:558772021-06-19T20:04:37Z= Candra Dewi, Wahyuni Geometri Indonesia Final Project geothermal manifestation, surface roughness, vegetation stress INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/55877 Geothermal energy that is renewable, reliable, and environmentally friendly is one of the most important energies. Based on Peraturan Pemerintah No. 79 tahun 2014 about the National Energy Policy, the use of geothermal energy must reach 23% by 2025. This regulation is in line with the goal of seven of Sustainable Development Goals (SDGs) which ensure access to energy that is affordable, guaranteed, sustainable and renewable for everyone. In order to achieve the government's goals, a preliminary survey on a wide scale with a fast time. Remote sensing can be an alternative solution for preliminary surveys. The existence of geothermal energy can be characterized by surface manifestations or features associated with geothermal. Geothermal manifestations are hydrothermal fluids from within the earth that come out through fractures or pores in the rock towards the surface. The fluid filled with hot contents which affect the surrounding environment, for example, changes in rocks and vegetation anomalies occur. In this study, surface roughness and vegetation stress were used as parameters to detect indications of geothermal manifestations in Kamojang, West Java. The data used are ALOS-2 PALSAR-2 imagery to obtain surface roughness information and vegetation stress information obtained from vegetation index analysis using Sentinel-2 images, namely Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), Green Normalized Difference Vegetation Index (GNDVI), dan Renormalized Difference Vegetation Index (RDVI). The results of this study indicate that the surface roughness value in the manifestation area has a slightly higher value than the surrounding area while the vegetation index in the manifestation area has a lower value. The accuracy value obtained is 71.43% with an error prediction rate of 28.57%. text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
topic Geometri
spellingShingle Geometri
Candra Dewi, Wahyuni
=
description Geothermal energy that is renewable, reliable, and environmentally friendly is one of the most important energies. Based on Peraturan Pemerintah No. 79 tahun 2014 about the National Energy Policy, the use of geothermal energy must reach 23% by 2025. This regulation is in line with the goal of seven of Sustainable Development Goals (SDGs) which ensure access to energy that is affordable, guaranteed, sustainable and renewable for everyone. In order to achieve the government's goals, a preliminary survey on a wide scale with a fast time. Remote sensing can be an alternative solution for preliminary surveys. The existence of geothermal energy can be characterized by surface manifestations or features associated with geothermal. Geothermal manifestations are hydrothermal fluids from within the earth that come out through fractures or pores in the rock towards the surface. The fluid filled with hot contents which affect the surrounding environment, for example, changes in rocks and vegetation anomalies occur. In this study, surface roughness and vegetation stress were used as parameters to detect indications of geothermal manifestations in Kamojang, West Java. The data used are ALOS-2 PALSAR-2 imagery to obtain surface roughness information and vegetation stress information obtained from vegetation index analysis using Sentinel-2 images, namely Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), Green Normalized Difference Vegetation Index (GNDVI), dan Renormalized Difference Vegetation Index (RDVI). The results of this study indicate that the surface roughness value in the manifestation area has a slightly higher value than the surrounding area while the vegetation index in the manifestation area has a lower value. The accuracy value obtained is 71.43% with an error prediction rate of 28.57%.
format Final Project
author Candra Dewi, Wahyuni
author_facet Candra Dewi, Wahyuni
author_sort Candra Dewi, Wahyuni
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url https://digilib.itb.ac.id/gdl/view/55877
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