Analisis Perubahan Suhu Permukaan Daratan di Kabupaten Seram Bagian Barat Menggunakan Platform Berbasis Cloud Google Earth Engine

Philia Christi Latue; Heinrich Rakuasa; Glendy Somae; Abdul Muin

doi:10.56211/sudo.v2i2.261

Authors

Philia Christi Latue Universitas Pattimura, Ambon
Heinrich Rakuasa Universitas Pattimura, Ambon
Glendy Somae Universitas Indonesia, Depok
Abdul Muin Universitas Negeri Jakarta, Jakarta

DOI:

https://doi.org/10.56211/sudo.v2i2.261

Keywords:

Google Earth Engine; Seram Bagian Barat; Suhu Permukaan Daratan

Abstract

Pemantauan suhu permukaan daratan dengan di Kabupaten Seram Bagian Barat menggunakan teknologi geospasial berbasis cloud computing Google Earth Engine dapat membantu dalam memahami perubahan iklim dan cuaca, serta memberikan informasi penting bagi para akademisi, masyarakat, pemerintah, dan organisasi non-pemerintah dalam mengambil keputusan terkait mitigasi perubahan iklim dan penanganan bencana alam. Penelitian ini menggunakan data citra Moderate Resolution Imaging Spectroradiometer (MODIS) Terra Land Surface Temperature and Emissivity 8-Day Global yang dianalisis di Google Earth Engine. Hasil penelitian menujukan bahwa nilai nilai suhu permukaan daratan di Kabupaten Seram Bagian Barat pada tahun 2012 yaitu 21,15ᵒ - 32,88 ᵒC dan mengalami kenaikan ditahun 2022 menjadi 12,73 ᵒ - 40,43ᵒC. Suhu permukaan daratan di Kabupaten Seram Bagian Barat mengalami peningkatan setiap tahunnya. Hasil penelitin ini sangat bermanfaat untuk pemantauan kualitas udara, pemantauan resiko kebakaran hutan, pada bidang pertanian dan lingkungan serta pada bidang kebencanan.

Downloads

Download data is not yet available.

References

H. P. U. Fonseka, H. Zhang, Y. Sun, H. Su, H. Lin, and Y. Lin, “Urbanization and Its Impacts on Land Surface Temperature in Colombo Metropolitan Area, Sri Lanka, from 1988 to 2016,” Remote Sens., vol. 11, no. 8, p. 957, Apr. 2019, doi: 10.3390/rs11080957.

K. Gadekar, C. B. Pande, J. Rajesh, S. D. Gorantiwar, and A. A. Atre, “Estimation of Land Surface Temperature and Urban Heat Island by Using Google Earth Engine and Remote Sensing Data,” 2023, pp. 367–389. doi: 10.1007/978-3-031-19059-9_14.

S. Kanga et al., “Understanding the Linkage between Urban Growth and Land Surface Temperature—A Case Study of Bangalore City, India,” Remote Sens., vol. 14, no. 17, 2022, doi: 10.3390/rs14174241.

R. Wang, M. Cai, C. Ren, B. Bechtel, Y. Xu, and E. Ng, “Detecting multi-temporal land cover change and land surface temperature in Pearl River Delta by adopting local climate zone,” Urban Clim., vol. 28, p. 100455, 2019, doi: https://doi.org/10.1016/j.uclim.2019.100455.

H. Rakuasa, “ANALISIS SPASIAL TEMPORAL SUHU PERMUKAAN DARATAN/ LAND SURFACE TEMPERATURE (LST) KOTA AMBON BERBASIS CLOUD COMPUTING: GOOGLE EARTH ENGINE,” J. Ilm. Inform. Komput., vol. 27, no. 3, pp. 194–205, Dec. 2022, doi: 10.35760/ik.2022.v27i3.7101.

A. R. Somae, G., Supriatna, S., Rakuasa, H., & Lubis, “PEMODELAN SPASIAL PERUBAHAN TUTUPAN LAHAN DAN PREDIKSI TUTUPAN LAHAN KECAMATAN TELUK AMBON BAGUALA MENGGUNAKAN CA-MARKOV,” J. Sains Inf. Geogr. (J SIG), vol. 6, no. 1, pp. 10–19, 2023, doi: http://dx.doi.org/10.31314/jsig.v6i1.1832.

Zhengming Wan, “MOD11A2 v061 MODIS/Terra Land Surface Temperature/Emissivity 8-Day L3 Global 1 km SIN Grid,” USGS website, 2020. https://lpdaac.usgs.gov/products/mod11a2v061/

D. How Jin Aik, M. H. Ismail, F. M. Muharam, and M. A. Alias, “Evaluating the impacts of land use/land cover changes across topography against land surface temperature in Cameron Highlands,” PLoS One, vol. 16, no. 5, p. e0252111, May 2021, doi: 10.1371/journal.pone.0252111.

J. Siqi, W. Yuhong, C. Ling, and B. Xiaowen, “A novel approach to estimating urban land surface temperature by the combination of geographically weighted regression and deep neural network models,” Urban Clim., vol. 47, p. 101390, Jan. 2023, doi: 10.1016/j.uclim.2022.101390.

S. L. Ermida, P. Soares, V. Mantas, F.-M. Göttsche, and I. F. Trigo, “Google Earth Engine Open-Source Code for Land Surface Temperature Estimation from the Landsat Series,” Remote Sens., vol. 12, no. 9, p. 1471, May 2020, doi: 10.3390/rs12091471.

L. K. Onisimo Muntaga, “Google Earth Engine Applications,” remotesensing, pp. 11–14, 2019, doi: 10.3390/rs11050591.

N. Gorelick, M. Hancher, M. Dixon, S. Ilyushchenko, D. Thau, and R. Moore, “Google Earth Engine: Planetary-scale geospatial analysis for everyone,” Remote Sens. Environ., vol. 202, pp. 18–27, 2017, doi: 10.1016/j.rse.2017.06.031.

B. Berhanu and E. Bisrat, “Identification of Surface Water Storing Sites Using Topographic Wetness Index (TWI) and Normalized Difference Vegetation Index (NDVI),” J. Nat. Resour. Dev., vol. 8, pp. 91–100, Sep. 2018, doi: 10.5027/jnrd.v8i0.09.

NASA, “Moderate Resolution Imaging Spectoradiometer (MODIS),” NASA, 2022. https://modis.gsfc.nasa.gov/

Diksha, M. Kumari, and R. Kumari, “Spatiotemporal Characterization of Land Surface Temperature in Relation Landuse/Cover: A Spatial Autocorrelation Approach,” J. Landsc. Ecol., Mar. 2023, doi: 10.2478/jlecol-2023-0001.

A. Sasky, P., Sobirin, S., & Wibowo, “Pengaruh Perubahan Penggunaan Tanah Terhadap Suhu Permukaan Daratan Metropolitan Bandung Raya Tahun 2000–2016.,” in Prosiding Industrial Research Workshop and National Seminar, 2017, pp. 354–361. doi: https://doi.org/10.35313/irwns.v8i3.767.

H. Latue, P. C., Septory, J. S. I., & Rakuasa, “Perubahan Tutupan Lahan Kota Ambon Tahun 2015, 2019 dan 2023,” JPG (Jurnal Pendidik. Geogr., vol. 10, no. 1, pp. 177–186, 2023, doi: http://dx.doi.org/10.20527/jpg.v10i1.15472.

F. Zhao et al., “Detection of geothermal potential based on land surface temperature derived from remotely sensed and in-situ data,” Geo-spatial Inf. Sci., pp. 1–17, Mar. 2023, doi: 10.1080/10095020.2023.2178335.