Analisa Pengaruh Indeks Penutup Lahan Terhadap Suhu Permukaan Tanah (Land Surface Temperature) Di Kota Surabaya

Wibowo, Caesaryo Arif (2023) Analisa Pengaruh Indeks Penutup Lahan Terhadap Suhu Permukaan Tanah (Land Surface Temperature) Di Kota Surabaya. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Urbanisasi yang meningkat di perkotaan menyebabkan perubahan penutup lahan yang menimbulkan berbagai efek negatif, salah satunya ialah meningkatnya suhu permukaan tanah di daerah perkotaan, yang dapat berdampak terhadap iklim ekstrem, bencana alam, keanekaragaman hayati, dan pengaruhnya pada sektor-sektor di suatu daerah. Kota Surabaya merupakan kota yang terus mengalami peningkatan penduduk, urbanisasi yang pesat, dan dinamika perubahan penutup lahan, di mana juga diidentifikasi terdapat kenaikan suhu di Kota Surabaya. Penelitian ini bertujuan untuk mengetahui pengaruh dari perubahan penutup lahan dengan menggunakan pendekatan indeks penutup lahan terhadap suhu permukaan tanah di Kota Surabaya, dengan variabel indeks penutup lahan yang terdiri dari indeks kekosongan, vegetasi, air, dan lahan terbangun, yang meliputi NDBaI, BI, NDVI, SAVI, NDWI, MNDWI, NDBI, NBI, BUc, EBBI, UI, dan IBI. Penelitian ini menggunakan metode Exploratory Regression dan Geographically Weighted Regression untuk mengetahui kombinasi variabel-variabel indeks penutup lahan dan pengaruhnya terhadap suhu permukaan tanah, yang meninjau juga pengaruhnya dengan mempertimbangkan bobot spasial. Hasil penelitian menunjukkan bahwa suhu permukaan tanah di Kota Surabaya mengalami penurunan rata-rata sebesar 12,74 oC dari tahun 2018 menuju tahun 2022. Indeks penutup lahan menunjukkan adanya dinamika perubahan tingkat vegetasi dan air yang semakin meningkat, serta penurunan tingkat indeks lahan terbangun dan kekosongan di Kota Surabaya dari tahun 2018 hingga tahun 2022. Hasil analisis Exploratory Regression dan Geographically Weighted Regression menunjukkan bahwa kombinasi variabel indeks penutup lahan yang berpengaruh terdiri dari MNDWI secara negatif dan UI secara positif pada tahun 2018, 2019, 2020, dan 2022, dan variabel MNDWI dan SAVI secara negatif pada tahun 2021. Nilai Adjusted R2 dari hasil Geographically Regression memiliki rentang 0,9643 dan 0,9785, yang menunjukkan bahwa variabel indeks penutup lahan terkait telah merepresentasikan proporsi varians dari variabel dependen yang diperhitungkan oleh model regresi dengan sangat baik, serta memiliki ukuran kinerja model terbaik dengan parameter AICc pada tahun 2022.
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Increasing urbanization in cities causes changes in land cover that cause various negative effects, one of which is increasing land surface temperatures in urban areas, which can have an impact on extreme climate, natural disasters, biodiversity, and their effects on sectors in an area. Surabaya City is a city that continues to experience population increase, rapid urbanization, and dynamics of land cover change, where there is also an increase in temperature in the city of Surabaya. This study aims to determine the effect of land cover change using a land cover index approach on land surface temperature in Surabaya City, with variable land cover index consisting of vacancy, vegetation, water, and built-up land indices, which include NDBaI, BI, NDVI, SAVI, NDWI, MNDWI, NDBI, NBI, BUc, EBBI, UI, and IBI. This study uses the Exploratory Regression and Geographically Weighted Regression methods to determine the combination of land cover index variables and their effects on land surface temperature, which also reviews their effects by considering spatial weights. The results showed that the land surface temperature in Surabaya City decreased by an average of 12.74 oC from 2018 to 2022. The land cover index shows the dynamics of changes in vegetation and water levels that are increasing, as well as a decrease in the index level of built-up land and vacancy in Surabaya City from 2018 to 2022. The results of the Exploratory Regression and Geographically Weighted Regression analysis showed that the combination of influential land cover index variables consisted of MNDWI negatively and UI positively in 2018, 2019, 2020, and 2022, and MNDWI and SAVI variables negatively in 2021. The Adjusted R2 value of the Geographically Regression results has a range of 0.9643 and 0.9785, which shows that the related land cover index variable has represented the proportion of variance of the dependent variable calculated by the regression model very well, and has the best model performance measure with AICc parameters in 2022.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Suhu Permukaan Tanah, Indeks Penutup Lahan, Exploratory Regression, Geographically Weighted Regression, Land Surface Temperature, Land Cover Index, Exploratory Regression, Geographically Weighted Regression
Subjects:	G Geography. Anthropology. Recreation > G Geography (General) > G70.212 ArcGIS. Geographic information systems. G Geography. Anthropology. Recreation > G Geography (General) > G70.5.I4 Remote sensing H Social Sciences > HT Communities. Classes. Races > HT133 City and Towns. Land use,urban
Divisions:	Faculty of Architecture, Design, and Planning > Regional and Urban Planning > 35201-(S1) Undergraduate Thesis
Depositing User:	Caesaryo Arif Wibowo
Date Deposited:	01 Aug 2023 06:41
Last Modified:	01 Aug 2023 06:41
URI:	http://repository.its.ac.id/id/eprint/100135

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