ANALISIS PENGARUH KEPADATAN BANGUNAN TERHADAP PERUBAHAN SUHU PERMUKAAN LAHAN DI KOTA CIMAHI MENGGUNAKAN CITRA LANDSAT 8 MULTITEMPORAL - Aqilla Tsabita Putri; Lili Somantri; Shafira Himayah (Universitas Negeri Padang, 2023)
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