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ANALISIS SUHU PERMUKAAN LAUT SAWU TAHUN 2021 MENGGUNAKAN CITRA SENTINEL-3 Handoko, Eko Yuli; Syariz, Muhammad Aldila; Wicaksono, Krisna Wahyu
J SIG (Jurnal Sains Informasi Geografi) Vol 6, No 2 (2023): Edisi November
Publisher : Universitas Muhammadiyah Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31314/jsig.v6i2.2403

Abstract

The eastern part of Indonesian Seas has a very unique characteristic as it is traversed by the Indonesian Through Flow (ITF). The ITF is a movement of water masses from the Pacific Ocean to the Indian Ocean, driven by the pressure differences between these two oceans. The movement of water masses and currents, along with the existence of monsoon winds that blow across the region throughout the year, impact the Sea Surface Temperature (SST) in Indonesia. The SST can be derived from satellite imagery such as MODIS and SeaWIFs images. This study utilized Sentinel-3 Sea and Land Surface Temperature data, with better spatial and temporal resolution than the two aforementioned images, to process the Sea Surface Temperature values. The research also investigated sea surface temperature values correlation with the movement and speed of winds occurring in Indonesia. The research results presented the monthly time-series distribution of sea surface temperature values in the Savu Sea for the year 2021. The analysis revealed that the lowest sea surface temperature values occurred in July, while the highest were recorded in December. The sea surface temperature values per month demonstrated an increase during the westerly monsoon from October to April, which corresponds to the rainy season in Indonesia. Conversely, during the easterly monsoon, the sea surface temperature values tended to be lower, resulting in the dry season due to decreased ocean evaporation. Furthermore, the study found a negative correlation between sea surface temperature values and wind speed, with a strong correlation coefficient of -0.5709.
the Comparative Analysis Of Landsat 8 And Landsat 9 Satellite Image Data In Surface Temperature Estimation, NDVI and NDBI Using Goggle Earth Engine Purwoko, Dana; Handoko, Eko Yuli; Syariz, Muhammad Aldila; Sopaheluwakan, Ardhasena
GEOID Vol. 20 No. 2 (2025)
Publisher : Departemen Teknik Geomatika ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The rapid urbanization in major cities like Jakarta significantly alters land cover, which in turn impacts environmental thermal conditions and ecological quality. This research aims to analyze the spatial and temporal dynamics of Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Built-up Index (NDBI) in DKI Jakarta during the 2023–2024 period using combined data from the Landsat 8 and 9 satellites. Cross-validation analysis shows a very high level of consistency between the sensors, validating the use of combined data for multi-temporal studies. Analysis methods include land cover classification, linear regression analysis, and temporal change analysis. The results indicate a clear Urban Heat Island (UHI) phenomenon, characterized by a strong positive correlation between LST and NDBI (R > 0.67) and a negative correlation between LST and NDVI (R ≈ -0.5). Temporal analysis indicates that thermal conditions in 2024 were generally lower than in 2023, and localized dynamics of land cover change were also identified. These findings affirm the fundamental relationship between land cover composition and the urban microclimate, and underscore the importance of vegetation in mitigating high temperatures in urban environment.