M. Yanis, N. Zaini, Isra Novari, Faisal Abdullah, B. G. Dewanto, M. Isa, Marwan Marwan, M. Zainal, Abdurrahman Abdurrahman
{"title":"Monitoring of Heat Flux Energy in the Northernmost Part of Sumatra Volcano Using Landsat 8 and Meteorological Data","authors":"M. Yanis, N. Zaini, Isra Novari, Faisal Abdullah, B. G. Dewanto, M. Isa, Marwan Marwan, M. Zainal, Abdurrahman Abdurrahman","doi":"10.14710/ijred.2023.47048","DOIUrl":null,"url":null,"abstract":"Geothermal energy, as a part of green and renewable energy, has been widely developed in the world to replace the current conventional fossil energy. Peut Sagoe is an active volcano in the northern part of Sumatra. The volcanic mountain has not been completely explored for geothermal and energy reserves study. This is due to the volcano locates in a high topography and surrounded by dense tropical forest, which makes it challenging to deploy geophysical instruments in the area. The Landsat 8 thermal infrared and meteorological data from 2013 – 2020 were used to estimate the energy resources by calculating the radiative heat flux (RHF) and measuring the energy lost annually through the heat discharge rate (HDR). We also used the normalized differential vegetation index (NDVI) for vegetation analysis, and estimation of its emissivity data. The mono-window algorithm was used to calculate the land surface temperature (LST). The Stefan–Boltzmann equation was utilized to analyze thermal infrared data for RHF, and ambient temperature and relative humidity data were acquired from the Indonesian Meteorological Agency (BMKG) database. The results showed that low vegetation values and high LST of 25°C–35°C were found in crater areas, which indicate the underground thermal activities of the mountain. It demonstrates that the maximum RHF values were 55 W/m2 in 2013 and 37 W/m2 in 2020. The HDR data were calculated by applying 15% of the RHF data, and the amounts of energy lost were 132.5 MWe and 64.5 MWe in 2013 and 2015 respectively. It increased to 186.4 MWe in 2017 and 89 MWe in 2020. Based on these predicted results, we conclude that the combination of thermal infrared imagery of Landsat 8 and meteorological data is an effective approach in estimating geothermal energy potential and energy loss of volcanoes situated in remote areas","PeriodicalId":44938,"journal":{"name":"International Journal of Renewable Energy Development-IJRED","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2022-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Renewable Energy Development-IJRED","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14710/ijred.2023.47048","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 5
Abstract
Geothermal energy, as a part of green and renewable energy, has been widely developed in the world to replace the current conventional fossil energy. Peut Sagoe is an active volcano in the northern part of Sumatra. The volcanic mountain has not been completely explored for geothermal and energy reserves study. This is due to the volcano locates in a high topography and surrounded by dense tropical forest, which makes it challenging to deploy geophysical instruments in the area. The Landsat 8 thermal infrared and meteorological data from 2013 – 2020 were used to estimate the energy resources by calculating the radiative heat flux (RHF) and measuring the energy lost annually through the heat discharge rate (HDR). We also used the normalized differential vegetation index (NDVI) for vegetation analysis, and estimation of its emissivity data. The mono-window algorithm was used to calculate the land surface temperature (LST). The Stefan–Boltzmann equation was utilized to analyze thermal infrared data for RHF, and ambient temperature and relative humidity data were acquired from the Indonesian Meteorological Agency (BMKG) database. The results showed that low vegetation values and high LST of 25°C–35°C were found in crater areas, which indicate the underground thermal activities of the mountain. It demonstrates that the maximum RHF values were 55 W/m2 in 2013 and 37 W/m2 in 2020. The HDR data were calculated by applying 15% of the RHF data, and the amounts of energy lost were 132.5 MWe and 64.5 MWe in 2013 and 2015 respectively. It increased to 186.4 MWe in 2017 and 89 MWe in 2020. Based on these predicted results, we conclude that the combination of thermal infrared imagery of Landsat 8 and meteorological data is an effective approach in estimating geothermal energy potential and energy loss of volcanoes situated in remote areas