Analisis Perubahan Suhu Permukaan Daratan di Kecamatan Ternate Tengah Menggunakan Google Earth Engine Berbasis Cloud Computing
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Keywords:
Cloud Computing, Google Earth Engine, Suhu Permukaan Daratan, Ternate Tengah
Abstract
Suhu permukaan daratan di Kecamatan Ternate Tengah mengalami peningkatan dari tahun 2013-2023, 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 berbasis cloud computing. Hasil penelitian menunjukan bahwa nilai suhu permukaan daratan tertinggi di tahun 2013 yaitu 24,41ᵒ C dan mengalami peningkatan di tahun 2023 menjadi 28,63ᵒ C. Hasil peneltian diharapkan dapat memberikan manfaat yang besar bagi Pemerintah setempat dalam merencanakan dan mengambil keputusan dalam berbagai sector diantaranya pengembangan sektor pertanian, pengelolaan
References
[1] M. F. U. Moazzam, Y. H. Doh, and B. G. Lee, “Impact of urbanization on land surface temperature and surface urban heat Island using optical remote sensing data: A case study of Jeju Island, Republic of Korea,” Build. Environ., vol. 222, p. 109368, Aug. 2022, doi: 10.1016/j.buildenv.2022.109368.
[2] C. B. Caballero, A. Ruhoff, and T. Biggs, “Land use and land cover changes and their impacts on surface-atmosphere interactions in Brazil: A systematic review,” Sci. Total Environ., vol. 808, p. 152134, 2022, doi: https://doi.org/10.1016/j.scitotenv.2021.152134.
[3] 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.
[4] R. C. Zulkarnain, “Pengaruh Perubahan Tutupan Lahan Terhadap Perubahan Suhu Permukaan di Kota Surabaya,” Skripsi Inst. Teknol. Sepuluh Nop., pp. 1–306, 2016.
[5] N. Wachid and W. P. Tyas, “Analisis Transformasi NDVI dan kaitannya dengan LST Menggunakan Platform Berbasis Cloud: Google Earth Engine,” J. Planol., vol. 19, no. 1, p. 60, Apr. 2022, doi: 10.30659/jpsa.v19i1.20199.
[6] 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.
[7] H. Latue, P. C., & Rakuasa, “Analysis of Land Cover Change Due to Urban Growth in Central Ternate District, Ternate City using Cellular Automata-Markov Chain,” J. Appl. Geospatial Inf., vol. 7, no. 1, pp. 722–728, 2023, doi: https://doi.org/10.30871/jagi.v7i1.4653.
[8] Y. Rakuasa, H., & Pakniany, “Spatial Dynamics of Land Cover Change in Ternate Tengah District, Ternate City, Indonesia,” Forum Geogr., vol. 36, no. 2, pp. 126–135, 2022, doi: DOI: 10.23917/forgeo.v36i2.19978.
[9] H. Salakory, M., Rakuasa, “Modeling of Cellular Automata Markov Chain for predicting the carrying capacity of Ambon City,” J. Pengelolaan Sumberd. Alam dan Lingkung., vol. 12, no. 2, pp. 372–387, 2022, doi: https://doi.org/10.29244/jpsl.12.2.372-387.
[10] H. Pertuack, S., Latue, P.C., & Rakuasa, “Analisis Spasial Daya Dukung Lahan Permukiman Kota Ternate,” ULIL ALBAB J. Ilm. Multidisiplin, vol. 2, no. 6, pp. 2084–2090, 2023, doi: https://doi.org/10.56799/jim.v2i6.1574.
[11] 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.
[12] 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.
[13] L. K. Onisimo Muntaga, “Google Earth Engine Applications,” remotesensing, pp. 11–14, 2019, doi: 10.3390/rs11050591.
[14] 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.
[15] 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.
[16] 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/
[17] 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.
[18] C. Maffei, S. Alfieri, and M. Menenti, “Relating Spatiotemporal Patterns of Forest Fires Burned Area and Duration to Diurnal Land Surface Temperature Anomalies,” Remote Sens., vol. 10, no. 11, p. 1777, Nov. 2018, doi: 10.3390/rs10111777.
[19] A. Latue, P. C., Rakuasa, H., Somae, G., & Muin, “Analisis Perubahan Suhu Permukaan Daratan di Kabupaten Seram Bagian Barat Menggunakan Platform Berbasis Cloud Google Earth Engine,” Sudo J. Tek. Inform., vol. 2, no. 2, pp. 45–51., 2023, doi: https://doi.org/10.56211/sudo.v2i2.261.
[20] J. Maulana and F. Bioresita, “Monitoring of Land Surface Temperature in Surabaya, Indonesia from 2013-2021 Using Landsat-8 Imagery and Google Earth Engine,” IOP Conf. Ser. Earth Environ. Sci., vol. 1127, no. 1, p. 012027, Jan. 2023, doi: 10.1088/1755-1315/1127/1/012027.
[21] C. L. Philia, “Analysis of Surface Temperature in Buru District Using Cloud Computing on Google Earth Engine,” J. Multidiscip. Sci., vol. 2, no. 3, 2023.
[2] C. B. Caballero, A. Ruhoff, and T. Biggs, “Land use and land cover changes and their impacts on surface-atmosphere interactions in Brazil: A systematic review,” Sci. Total Environ., vol. 808, p. 152134, 2022, doi: https://doi.org/10.1016/j.scitotenv.2021.152134.
[3] 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.
[4] R. C. Zulkarnain, “Pengaruh Perubahan Tutupan Lahan Terhadap Perubahan Suhu Permukaan di Kota Surabaya,” Skripsi Inst. Teknol. Sepuluh Nop., pp. 1–306, 2016.
[5] N. Wachid and W. P. Tyas, “Analisis Transformasi NDVI dan kaitannya dengan LST Menggunakan Platform Berbasis Cloud: Google Earth Engine,” J. Planol., vol. 19, no. 1, p. 60, Apr. 2022, doi: 10.30659/jpsa.v19i1.20199.
[6] 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.
[7] H. Latue, P. C., & Rakuasa, “Analysis of Land Cover Change Due to Urban Growth in Central Ternate District, Ternate City using Cellular Automata-Markov Chain,” J. Appl. Geospatial Inf., vol. 7, no. 1, pp. 722–728, 2023, doi: https://doi.org/10.30871/jagi.v7i1.4653.
[8] Y. Rakuasa, H., & Pakniany, “Spatial Dynamics of Land Cover Change in Ternate Tengah District, Ternate City, Indonesia,” Forum Geogr., vol. 36, no. 2, pp. 126–135, 2022, doi: DOI: 10.23917/forgeo.v36i2.19978.
[9] H. Salakory, M., Rakuasa, “Modeling of Cellular Automata Markov Chain for predicting the carrying capacity of Ambon City,” J. Pengelolaan Sumberd. Alam dan Lingkung., vol. 12, no. 2, pp. 372–387, 2022, doi: https://doi.org/10.29244/jpsl.12.2.372-387.
[10] H. Pertuack, S., Latue, P.C., & Rakuasa, “Analisis Spasial Daya Dukung Lahan Permukiman Kota Ternate,” ULIL ALBAB J. Ilm. Multidisiplin, vol. 2, no. 6, pp. 2084–2090, 2023, doi: https://doi.org/10.56799/jim.v2i6.1574.
[11] 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.
[12] 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.
[13] L. K. Onisimo Muntaga, “Google Earth Engine Applications,” remotesensing, pp. 11–14, 2019, doi: 10.3390/rs11050591.
[14] 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.
[15] 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.
[16] 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/
[17] 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.
[18] C. Maffei, S. Alfieri, and M. Menenti, “Relating Spatiotemporal Patterns of Forest Fires Burned Area and Duration to Diurnal Land Surface Temperature Anomalies,” Remote Sens., vol. 10, no. 11, p. 1777, Nov. 2018, doi: 10.3390/rs10111777.
[19] A. Latue, P. C., Rakuasa, H., Somae, G., & Muin, “Analisis Perubahan Suhu Permukaan Daratan di Kabupaten Seram Bagian Barat Menggunakan Platform Berbasis Cloud Google Earth Engine,” Sudo J. Tek. Inform., vol. 2, no. 2, pp. 45–51., 2023, doi: https://doi.org/10.56211/sudo.v2i2.261.
[20] J. Maulana and F. Bioresita, “Monitoring of Land Surface Temperature in Surabaya, Indonesia from 2013-2021 Using Landsat-8 Imagery and Google Earth Engine,” IOP Conf. Ser. Earth Environ. Sci., vol. 1127, no. 1, p. 012027, Jan. 2023, doi: 10.1088/1755-1315/1127/1/012027.
[21] C. L. Philia, “Analysis of Surface Temperature in Buru District Using Cloud Computing on Google Earth Engine,” J. Multidiscip. Sci., vol. 2, no. 3, 2023.
Published
2023-06-28
Section
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