Analisis Spasial Perubahan Suhu Permukaan Daratan Kota Kupang Menggunakan Pendekatan Geospatial Artificial Intelligence (GeoAI)

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Authors

  • Sandy Liwan Belgorod State University, Belgorod
  • Philia Christi Latue Herzen University, Saint Petersburg

DOI:

https://doi.org/10.56211/buana.v1i1.343

Keywords:

Analsis Spasial; google earth engine; suhu permukaan daratan; kupang

Abstract

Suhu permukaan daratan di Kota Kupang mengalami peningkatan dari tahun 2018-2023, salah satu faktor penyebabnya yaitu terjadinya perkembangan lahan terbangun yang semakin meningkat setiap tahunnya. Penelitian ini menggunakan data citra Landsat 8 Collection 1 Tier 2 TOA Reflectance pada google earth engine. Untuk menganalisis suhu permukaan daratan (LST) pada citra Landsat 8 menggunakan pendekatan geospatial artificial intelligence (GeoAI) menggunakan pltafrom Google Earth Engine (GEE) berbasis cloud computing dengan menggunakan formula "Single Channel Algorithm" atau "Split-Window Algorithm". Hasil penelitian menunjukan bahwa nilai suhu permukaan daratan tertinggi di tahun 2018 berkisar 21,09ᵒ C – 30,79ᵒ C dan mengalami peningkatan di tahun 2023 menjadi 22,06ᵒ C – 34,99ᵒ C. Suhu permukaan pada kelas tinggi dan sangat tinggi terdistribusi di daerah pesisir yang megalami perkembangan lahan terbangun yang tinggi dan  yang juga merupakan daerah pusat Kota Kupang. Hasil peneltian diharapkan dapat memberikan manfaat yang besar bagi Pemerintah setempat dalam merencanakan dan mengambil keputusan dalam berbagai sector diantaranya pengembangan sektor pertanian, pengelolaan sumber daya air, dan penanggulangan bencana.

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References

Ahmed, M. Razu, Ebrahim Ghaderpour, Anil Gupta, Ashraf Dewan, and Quazi K. Hassan. 2023. “Opportunities and Challenges of Spaceborne Sensors in Delineating Land Surface Temperature Trends: A Review.” IEEE Sensors Journal 23(7):6460–72. doi: 10.1109/JSEN.2023.3246842.

Angin, Ignasius Suban, and Sunimbar Sunimbar. 2021. “Analisis Perubahan Penggunaan Lahan Kota Kupang Nusa Tenggara Timur Tahun 2010-2018.” Geoedusains: Jurnal Pendidikan Geografi 2(1):36–52. doi: 10.30872/geoedusains.v2i1.564.

Bhattacharjee, Rajarshi, Shishir Gaur, Nilendu Das, Shivam, Ashwani Kumar Agnihotri, and Anurag Ohri. 2022. “Analysing the Relationship between Human Modification and Land Surface Temperature Fluctuation in the Ramganga Basin, India.” Environmental Monitoring and Assessment 195(1):104. doi: 10.1007/s10661-022-10728-y.

Diksha, Maya Kumari, and Rina Kumari. 2023. “Spatiotemporal Characterization of Land Surface Temperature in Relation Landuse/Cover: A Spatial Autocorrelation Approach.” Journal of Landscape Ecology. doi: 10.2478/jlecol-2023-0001.

Döllner, Jürgen. 2020. “Geospatial Artificial Intelligence: Potentials of Machine Learning for 3D Point Clouds and Geospatial Digital Twins.” PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science 88(1):15–24. doi: 10.1007/s41064-020-00102-3.

Ermida, Sofia L., Patrícia Soares, Vasco Mantas, Frank-M. Göttsche, and Isabel F. Trigo. 2020. “Google Earth Engine Open-Source Code for Land Surface Temperature Estimation from the Landsat Series.” Remote Sensing 12(9):1471. doi: 10.3390/rs12091471.

Fonseka, H. P. U., Hongsheng Zhang, Ying Sun, Hua Su, Hui Lin, and Yinyi Lin. 2019. “Urbanization and Its Impacts on Land Surface Temperature in Colombo Metropolitan Area, Sri Lanka, from 1988 to 2016.” Remote Sensing 11(8):957. doi: 10.3390/rs11080957.

Gao, S. 2021. Geospatial Artificial Intelligence (GeoAI). New York: Oxford University Press.

Ghanbari, R., M. Heidarimozaffar, A. Soltani, and H. Arefi. 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. doi: 10.1007/s13762-022-04725-4.

Kanga, Shruti, Gowhar Meraj, Brian Alan Johnson, Suraj Kumar Singh, Muhammed Naseef PV, Majid Farooq, Pankaj Kumar, Asif Marazi, and Netrananda Sahu. 2022. “Understanding the Linkage between Urban Growth and Land Surface Temperature—A Case Study of Bangalore City, India.” Remote Sensing 14(17). doi: 10.3390/rs14174241.

Khan, Rehan, Huan Li, Muhammad Basir, Yuan Lin Chen, Meer Muhammad Sajjad, Ihtisham Ul Haq, Barkat Ullah, Muhammad Arif, and Waqas Hassan. 2022. “Monitoring Land Use Land Cover Changes and Its Impacts on Land Surface Temperature over Mardan and Charsadda Districts, Khyber Pakhtunkhwa (KP), Pakistan.” Environmental Monitoring and Assessment 194(6):409. doi: 10.1007/s10661-022-10072-1.

Latue, P. C., Rakuasa, H., Somae, G., & Muin, A. 2023. “Analisis Perubahan Suhu Permukaan Daratan Di Kabupaten Seram Bagian Barat Menggunakan Platform Berbasis Cloud Google Earth Engine.” Sudo Jurnal Teknik Informatika 2(2):45–51. doi: https://doi.org/10.56211/sudo.v2i2.261.

Latue, P. C & Rakuasa, H. 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. doi: https://doi.org/10.35970/e-joint.v4i1.1901.

Maulana, J., and F. Bioresita. 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. doi: 10.1088/1755-1315/1127/1/012027.

Moisa, Mitiku Badasa, Bacha Temesgen Gabissa, Lachisa Busha Hinkosa, Indale Niguse Dejene, and Dessalegn Obsi Gemeda. 2022. “Analysis of Land Surface Temperature Using Geospatial Technologies in Gida Kiremu, Limu, and Amuru District, Western Ethiopia.” Artificial Intelligence in Agriculture 6:90–99. doi: 10.1016/j.aiia.2022.06.002.

Onisimo Muntaga, Lalit Kumar. 2019. “Google Earth Engine Applications.” Remotesensing 11–14. doi: 10.3390/rs11050591.

Philia, Christi Latue. 2023. “Analysis of Surface Temperature in Buru District Using Cloud Computing on Google Earth Engine.” Journal of Multidisciplinary Science 2(1):1–10.

Prayogo, L. M. (2021). 2023. “Platform Google Earth Engine Untuk Pemetaan Suhu Permukaan Daratan Dari Data Series Modis.” DoubleClick: Journal of Computer and Information Technology 5(1):25–31.

Purbahapsari, Alya Faryanti, and Irene B. Batoarung. 2022. “Geospatial Artificial Intelligence for Early Detection of Forest and Land Fires.” KnE Social Sciences. doi: 10.18502/kss.v7i9.10947.

Rakuasa, H., Sihasale , D. A., & Latue, P. C. 2023. “Spatial Pattern of Changes in Land Surface Temperature of Seram Island Based on Google Earth Engine Cloud Computing.” International Journal of Basic and Applied Science 12(1):1–9. doi: https://doi.org/10.35335/ijobas.v12i1.172.

Rakuasa, Heinrich. 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. doi: 10.35760/ik.2022.v27i3.7101.

Song, Yongze, Margaret Kalacska, Mateo Gašparović, Jing Yao, and Nasser Najibi. 2023. “Advances in Geocomputation and Geospatial Artificial Intelligence (GeoAI) for Mapping.” International Journal of Applied Earth Observation and Geoinformation 120:103300. doi: 10.1016/j.jag.2023.103300.

Tahooni, Amir, A. A. Kakroodi, and Majid Kiavarz. 2023. “Monitoring of Land Surface Albedo and Its Impact on Land Surface Temperature (LST) Using Time Series of Remote Sensing Data.” Ecological Informatics 75:102118. doi: 10.1016/j.ecoinf.2023.102118.

Ticman, K. V., S. G. Salmo III, K. E. Cabello, M. Q. Germentil, D. M. Burgos, and A. C. Blanco. 2021. “MONITORING POST-DISASTER MANGROVE FOREST RECOVERIES IN LAWAAN-BALANGIGA, EASTERN SAMAR USING TIME SERIES ANALYSIS OF MOISTURE AND VEGETATION INDICES.” The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVI-4/W6-:295–301. doi: 10.5194/isprs-archives-XLVI-4-W6-2021-295-2021.

Zhang, Maomao, Abdulla- Al Kafy, Pengnan Xiao, Siyu Han, Shangjun Zou, Milan Saha, Cheng Zhang, and Shukui Tan. 2023. “Impact of Urban Expansion on Land Surface Temperature and Carbon Emissions Using Machine Learning Algorithms in Wuhan, China.” Urban Climate 47:101347. doi: 10.1016/j.uclim.2022.101347.

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Article History

Submitted: 2023-07-27
Published: 2023-08-01
Pages: 14-20

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How to Cite

Liwan, S., & Latue, P. C. (2023). Analisis Spasial Perubahan Suhu Permukaan Daratan Kota Kupang Menggunakan Pendekatan Geospatial Artificial Intelligence (GeoAI). Buana Jurnal Geografi, Ekologi Dan Kebencanaan, 1(1), 14–20. https://doi.org/10.56211/buana.v1i1.343