ANALISIS PENGARUH KEPADATAN BANGUNAN TERHADAP PERUBAHAN SUHU PERMUKAAN LAHAN DI KOTA CIMAHI MENGGUNAKAN CITRA LANDSAT 8 MULTITEMPORAL
Main Article Content
Abstract
The construction of settlements and the development of industrial estates are
continuously increasing, especially in urban areas. The city of Cimahi has a strategic position
and is quite close to the city of Bandung, so that an increase in building density will result in an
increase in atmospheric conditions around the area which will trigger land surface
temperatures in an area. The main objective of the research is to analyze the effect of building
density on land surface temperature in Cimahi City. To examine the effect between variables
using a simple linear regression test. Based on the results of NDBI processing in 2014, the
lowest value was -0.68 and the highest value was 0.51. In 2022, the NDBI processing results
will produce the lowest value of -0.447 and the highest value of 0.517. The results of building
density processing from 2014 to 2022 show an increase in building density. Based on the
processing results, the lowest land surface temperature in 2019 was 12ºC and the highest
temperature was 25ºC. The processing of land surface temperatures in 2022 will produce the
lowest temperature, which is 18ºC and the highest temperature, which is 27ºC. The results of
land surface temperature changes from 2014 to 2022 show a significant increase. The results of
a simple linear regression test in 2014 yielded values R square of 0.614 with a significant value
of 0.001. The results of the regression test in 2022 yield R square 0.505 with a significant value
of 0.001. From the results of the research, it is hoped that the government can assist decision
making as well as a policy reference in development planning and spatial planning. For future
researchers, it is hoped that they can provide updates on methods and the use of higher
resolution or updated satellite imagery.
Keywords: Building Density, Land Surface Temperature, Regression, Remote Sensing
Downloads
Article Details
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
References
Perumahan Dan Pemukiman Dengan Sistem Informasi Geografis Di Kabupaten Tanah
Datar. Jurnal Ilmiah Rekayasa Sipil, 17(1), 96-105.
Agustan, M. S. (2015). Analisis Kebutuhan Sistem Satelit Penginderaan Jauh Nasional
Indonesia. Jakarta: PTISDA-BPPT, Gedung, 2.
Baihaqi, H. F., Prasetyo, Y., & Bashit, N. (2019). Analisis Perkembangan Kawasan Industri
Kendal Terhadap Perubahan Suhu Permukaan (Studi Kasus: Kawasan Industri Kendal,
Kabupaten Kendal). Jurnal Geodesi Undip, 9(1), 176-186.
Danoedoro, P. (2012). Pengantar Penginderaan Jauh Digital. Yogyakarta: Penerbit ANDI.
Hamdani, D., & Saptanji, R. V. T. (2020, February). Perancangan Model Sistem Informasi
Geografis Untuk Monitoring Sebaran Jumlah Penduduk di Kota Cimahi. In Annual
Research Seminar (ARS) (Vol. 5, No. 1, pp. 227-230).
Handayani, M. N., Sasmito, B., & Wijaya, A. P. (2017). Analisis hubungan antara perubahan
suhu dengan indeks kawasan terbangun menggunakan citra Landsat (studi kasus: kota
Surakarta). Jurnal Geodesi Undip, 6(4), 208-2018.
Mas Putri I, Fikriyah N, Putri A. (2023). Kota Cimahi Dalam Angka 2023. BPS Kota Cimahi.
Diunduh pada 20 April 2023 dari
https://cimahikota.bps.go.id/publication/download.html?nrbvfeve=YjYxZjNhM2U1MTA
0YjhiZGYyNTM0Yjc1&xzmn=aHR0cHM6Ly9jaW1haGlrb3RhLmJwcy5nby5pZC9wd
WJsaWNhdGlvbi8yMDIzLzAyLzI4L2I2MWYzYTNlNTEwNGI4YmRmMjUzNGI3NS
9rb3RhLWNpbWFoaS1kYWxhbS1hbmdrYS0yMDIzLmh0bWw%3D&twoadfnoarfeauf
=MjAyMy0wNS0wMSAxODowOToxMw%3D%3D.
NINGRUM, E. S. (2010). Teknologi Penginderaan Jauh dan Sistem Informasi Geografis dalam
Pengelolaan Terumbu Karang.
Setyorini, Beti (2012) Analisis Kepadatan Penduduk Dan Proyeksi Kebutuhan Permukiman
Kecamatan Depok Sleman Tahun 2010 - 2015. Skripsi thesis, Universitas
Muhammadiyah Surakrta.
Wulandari, R., & HA Sudibyakto, H. A. (2017). Identifikasi urban heat island di kota
surakarta. Jurnal Bumi Indonesia, 6(1)