Analysis of Average Land Surface Temperature of Java Island, Indonesia in 2024 using reduceRegions in Google Earth Engine
Abstract
This study presents a comprehensive analysis of the average Land Surface Temperature (LST) of Java Island, Indonesia, for the year 2024, utilizing the reduceRegions function in Google Earth Engine (GEE). Rapid urbanization and environmental changes on Java Island have significant implications for its climate and thermal conditions, necessitating effective monitoring and analysis of LST. The research employs satellite-based remote sensing techniques to assess the relationship between vegetation cover and surface temperatures, revealing that areas with higher vegetation density tend to exhibit lower surface temperatures. This finding aligns with previous studies, underscoring the importance of green spaces in urban environments. The analysis not only contributes to a deeper understanding of Java Island's environmental dynamics but also provides critical insights for policymakers and urban planners. The results can inform strategies for climate adaptation and sustainable development, addressing ongoing environmental challenges. Limitations of the study are acknowledged, and recommendations for future research are proposed, emphasizing the need for continued exploration of LST variations in relation to urbanization and climate change. Overall, this research serves as a valuable resource for enhancing environmental management practices on Java Island and similar regions facing rapid development.
Full text article
References
Diksha, Kumari, M., & Kumari, R. (2023). Spatiotemporal Characterization of Land Surface Temperature in Relation Landuse/Cover: A Spatial Autocorrelation Approach. Journal of Landscape Ecology. https://doi.org/10.2478/jlecol-2023-0001
Ermida, S. L., Soares, P., Mantas, V., Göttsche, F.-M., & Trigo, I. F. (2020). Google Earth Engine Open-Source Code for Land Surface Temperature Estimation from the Landsat Series. Remote Sensing, 12(9), 1471. https://doi.org/10.3390/rs12091471
Gadekar, K., Pande, C. B., Rajesh, J., Gorantiwar, S. D., & Atre, A. A. (2023). Estimation of Land Surface Temperature and Urban Heat Island by Using Google Earth Engine and Remote Sensing Data (pp. 367–389). https://doi.org/10.1007/978-3-031-19059-9_14
Ghanbari, R., Heidarimozaffar, M., Soltani, A., & Arefi, H. (2023). Land surface temperature analysis in densely populated zones from the perspective of spectral indices and urban morphology. International Journal of Environmental Science and Technology, 20(3), 2883–2902. https://doi.org/10.1007/s13762-022-04725-4
Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., & Moore, R. (2017). Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment, 202, 18–27. https://doi.org/10.1016/j.rse.2017.06.031
Heinrich Rakuasa, Nadhi Sugandhi, Zainudin, Wulan Abdul Wahab, K. (2023). Aplikasi GAI Dan UAVs Untuk Analisis Korelasi Kepadatan Permukiman Dan LST Di Pulau Panggang DKI Jakarta. Larisa Penelitian Multidisiplin, 1(1), 31–35.
Jaelani, L., & Handayani, C. (2022). Spatio-temporal Analysis of Land Surface Temperature Changes in Java Island from Aqua and Terra MODIS Satellite Imageries Using Google Earth Engine. International Journal of Geoinformatics, 18(5), 1–12. https://doi.org/10.52939/ijg.v18i5.2365
Maulana, J., & Bioresita, F. (2023). Monitoring of Land Surface Temperature in Surabaya, Indonesia from 2013-2021 Using Landsat-8 Imagery and Google Earth Engine. IOP Conference Series: Earth and Environmental Science, 1127(1), 012027. https://doi.org/10.1088/1755-1315/1127/1/012027
Munawar, M., Prasetya, T. A. E., Marzuki, M., Taufik, M. R., & Fadla, T. (2024). Java and Bali Land Surface Temperature Decrease Variation. SSRN, 1–12. https://doi.org/https://dx.doi.org/10.2139/ssrn.4848577
Munawar, M., Prasetya, T. A. E., McNeil, R., Jani, R., & Buya, S. (2023). Spatio and Temporal Analysis of Indonesia Land Surface Temperature Variation During 2001–2020. Journal of the Indian Society of Remote Sensing, 51(7), 1393–1407. https://doi.org/10.1007/s12524-023-01713-0
Onisimo Muntaga, L. K. (2019). Google Earth Engine Applications. Remotesensing, 11–14. https://doi.org/10.3390/rs11050591
Philia Christi Latue, H. R. (2023). Analisis Perubahan Suhu Permukaan Daratan di Kecamatan Ternate Tengah Menggunakan Google Earth Engine Berbasis Cloud Computing. E- JOINT ( Electronica and Electrical Journal of Innovation Technology), 4(1), 16–20. https://doi.org/https://doi.org/10.35970/e-joint.v4i1.1901
Rakuasa, H., Huy-Hoang, D., Nasution, R. A. R., Turi, F., & Hidayatullah, M. (2024). Analysis of Land Surface Temperature Changes in Sorong City, Indonesia Using Landsat 8 Satellite Image Data Based on Cloud Computing. Journal of International Multidisciplinary Research, 2(7), 246–252. https://doi.org/https://doi.org/10.62504/jimr784
Rakuasa, H. (2022). ANALISIS SPASIAL TEMPORAL SUHU PERMUKAAN DARATAN/ LAND SURFACE TEMPERATURE (LST) KOTA AMBON BERBASIS CLOUD COMPUTING: GOOGLE EARTH ENGINE. Jurnal Ilmiah Informatika Komputer, 27(3), 194–205. https://doi.org/10.35760/ik.2022.v27i3.7101
Rakuasa, H. (2024). Spatial Temporal Analysis of Land Surface Temperature Changes in Ambon Island from Landsat 8 Image Data Using Geogle Earth Engine. Journal of Applied Research In Computer Science and Information Systems, 2(1), 107–113. https://doi.org/https://doi.org/10.61098/jarcis.v2i1.123
Rakuasa, H., & Lasaiba, M. A. (2024). FUTURE POPULATION PREDICTION 2050 OF BANTEN PROVINCE, JAKARTA, JAWA BARAT, JAWA TENGAH, DAERAH ISTIMEWA YOGJAKARTA, JAWA TIMUR, USING WORLDPOP DATA WITH GOOGLE EARTH ENGINE. Journal of Data Analytics, Information, and Computer Science, 1(2), 79–86. https://doi.org/10.59407/jdaics.v1i2.712
Rakuasa, H., & Pertuack, S. (2023). Pola Perubahan Suhu Permukaan Daratan di Kecamatan Ternate Tengah, Kota Ternate Tahun 2013 dan 2023 Menggunakan Google Earth Engine. Sudo Jurnal Teknik Informatika, 2(2), 78–85. https://doi.org/10.56211/sudo.v2i2.271
Zhang, M., Kafy, A.- Al, Xiao, P., Han, S., Zou, S., Saha, M., Zhang, C., & Tan, S. (2023). Impact of urban expansion on land surface temperature and carbon emissions using machine learning algorithms in Wuhan, China. Urban Climate, 47, 101347. https://doi.org/10.1016/j.uclim.2022.101347
Zhengming Wan. (2020). MOD11A2 v061 MODIS/Terra Land Surface Temperature/Emissivity 8-Day L3 Global 1 km SIN Grid. USGS Website. https://lpdaac.usgs.gov/products/mod11a2v061/
Authors
Copyright (c) 2024 Rafly Aulya Rizky Nasution, Heinrich Rakuasa, Fadlan Turi, Muh Hidayatullah, Philia Christi Latue

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.