Identification of Land Surface Temperature (LST) using Multitemporal Sentinel 3 Images from 2019-2023 Case Study: Padang City Area, West Sumatra
DOI:
https://doi.org/10.30631/sdgs.v4i1.2585Keywords:
Land Surface Temperature (LST), Sentinel 3, Multitemporal, NDVIAbstract
Land Surface Temperature (LST) is widely utilized in current studies, particularly as an initial survey tool to assess geothermal activity in locations suspected to have geothermal sources. The research method involves geometric correction of Sentinel-3 imagery and conversion of temperature units from Fahrenheit (F) to Celsius (C) to ensure accuracy in temperature measurement. Image data processing from Sentinel-3, including thermal band analysis, is carried out to generate land surface temperature values. The field-measured temperatures are then compared to the land surface temperature data obtained through processing. The temperatures in the location, ranging from 23°C to 35°C, fall within the minimum geothermal temperature range, indicating potential geothermal activity. However, the LST values from the image data exhibit some differences compared to the on-site measurements. These discrepancies are categorized into classes I (23.7 – 24°C), II (24 – 24.3°C), and III (24.3 – 24.8°C), marked by red areas in the LST values. These discrepancies are attributed to various factors during image recording and processing, such as atmospheric interference and sensor calibration.
References
ESA Sentinel Online. (2020). Land Surface Temperature. May 8 2023, retrieved from https://sentinel.esa.int/web/sentinel/user-guides/sentinel-3-slstr/overview/geophysical-measurements/land-surface-temperature
Fajrin & Dwi Marsiska Driptufany (2019). Identifikasi Urban Heat Island Kota Padang Menggunakan Teknik Penginderaan Jauh dan Sistem Informasi Geografis. Jurnal Teknik Sipil Intitut Teknologi Padang. 6 (1), 1-7 doi: https://doi.org/10.21063/jts.2019.V601.01-7 DOI: https://doi.org/10.21063/JTS.2019.V601.01
Johnson, J. C., Urcuyo, J., Moen, C., & Stevens, D. R. (2019). Urban heat island conditions experienced by the Western black widow spider (Latrodectus hesperus): Extreme heat slows development but results in behavioral accommodations. PLOS ONE, 14(9), e0220153. doi:10.1371/journal.pone.0220153 DOI: https://doi.org/10.1371/journal.pone.0220153
Kurniadin, Yani,M,.Nurgiantoro, dkk. 2022. Deteksi Perubahan Suhu Permukaan Tanah dan Hubungannya dengan Pengaruh Albedo dan NDVI Menggunakan Data Satelit Landsat 8 Multitemporal di Kota Palu Tahun 2013- 2020. Journal of Geodasy and Geometics. Vol 18. No.1 DOI: http://dx.doi.org/10.12962/j24423998.v18i1.13157 DOI: https://doi.org/10.12962/j24423998.v18i1.13157
Mirnayani, Rapang,S.R, Nursuasri, dkk. 2021. Pemanfaatan Data Citra Sentinel -3 Sea and Land Surface Temperature Radiometer (SLSTR) Pagi dan Malam Hari Untuk Analisis Intesitas Fenomena Pulau Bahang Permukaan (Studi kasus: Kota Bandung). Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital 18 (1),15-25 DOI: https://doi.org/10.30536/inderaja.v18i1.3362
Min, M., Zhao, H., Miao, C. (2018). Spatio-Temporal Evolution Analysis of the Urban Heat Island: A Case Study of Zhengzhou City, China. Sustainability, 10 (6), 1-23 doi: http://dx.doi.org/10.3390/su10061992 DOI: https://doi.org/10.3390/su10061992
Murni, Lorensia Yatimas dkk. 2023. 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), 1-9. DOI: https://doi.org/10.24843/BF.2023.v24.i01.p01
Nurgiantoro, Aris, A. (2019). Analisis Land Surface Emissivity menggunakan Data NDVI Landsat 8 dan Pengaruhnya terhadap Formasi Land Surface Temperature di Wilayah Kota Kendari. Jurnal Penginderaan Jauh Indonesia, 1 (2), 39-44. Retrieved from https://journal.its.ac.id/index.php/jpji DOI: https://doi.org/10.12962/jpji.v1i2.257
Pramudiyasari, Mangapul, Tambunan, Rudi, Masita, Manessa. 2021. Analisis LST NDVI Menggunakan Satelit Landsat 8 Serta Trend Suhu Udara di Kabupaten Majelengka. Jurnal Geosaintek. Vol 7, No 3 (2021). DOI:10.12962/j25023659.v7i3.9043 DOI: https://doi.org/10.12962/j25023659.v7i3.9043
Ramdhan M,Satryo.I.F, Cerlandita.P.K. 2021. Analisis Perubahan Land Surface Temperature Menggunakan Citra Multitemporal (Studi Kasus : Kota Banjarmasin). Jurnal Pendidikan dan Ilmu Geografi.Vol.6, No.1. Hal. 15-20 DOI: https://doi.org/10.21067/jpig.v6i1.5202
Smith et al., 2018, 'Impact of Vegetation on Urban Microclimate in Arid Climates: A Remote Sensing Approach
Suhadha, Argo Galih. 2019. Satelit Multimasi Sentinel-3 dan Pemanfaatnya dalam Pemantuan Sumberdaya Pesisir dan Laut. Pemanfaatan Data Penginderaan Jauh 10 (12), 41-49.USGS. 2023. Land Surface Temperature. Diakses pada 29 Maret 2023, melalui (https://www.usgs.gov/landresources/nli/)
Tran, H., Uchihama D., Ochi, S., and Yasuoka, Y (2006). Assessment With Satellite Data Of The Urban Heat Island Effects In Asian Mega Cities. International Journal of Applied Earth Observation and Geoinformation. 8 (1) 34-48 doi: https://doi.org/10.1016/j.jag.2005.05.003 DOI: https://doi.org/10.1016/j.jag.2005.05.003
USGS. (2023). Land Surface Temperature. May 8, 2023, retrieved from https://www.usgs.gov/landresources/nli/
Voogt, J.A., Oke, T.R. (2003). Thermal remote sensing of urban climates. Remote Sens, Environ, 86, (page. 370–384). London, England: Cambridge University Press DOI: https://doi.org/10.1016/S0034-4257(03)00079-8
Wiguna, Dede Prabowo. 2017. Identifikasi Suhu Permukaan Tanah dengan Metode Konversi Digital Number Menggunakan Teknik Penginderaan Jauh dan Sistem Informasi Geografi. Jurnal Teknologi Informasi. Vol. 1. No.2








