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Analysing the Relationship Between Built-Up Area and Land Surface Temperature Using NDBI Processing: A Comparative Study of Makassar City in 2014 and 2023
Ilyas Nur Setiawan, Jumadi Jumadi

Faculty of Geography, Universitas Muhammadiyah Surakarta


Abstract

The dynamic development of urban areas in Indonesia is intricately linked to population growth, economic expansion, and environmental dynamics. As of mid-2023, Indonesia^s population has surged to 273.8 million, ranking fourth globally in terms of population size. The unbridled urban growth has led to the restructuring of cities, transformation of agricultural lands, and a decline in green open spaces, resulting in deteriorating air quality, rising surface temperatures, and changes in land cover patterns. This phenomenon is notably evident in Makassar City, where insufficient green open spaces (less than 30%) and the conversion of land functions to buildings have escalated surface temperatures. This study aims to analyze the distribution of built-up land, land surface temperature (LST), and the relationship between changes in built-up land in Makassar City from 2014 to 2023, utilizing Landsat imagery. The analysis, employing Landsat imagery and the Normalized Difference Built-Up Index (NDBI) algorithm, reveals a significant growth in built-up land aligned with the development plans for Makassar City until 2026. Surface temperature classification indicates a substantial increase from 2014 to 2023, correlating with built-up land expansion. Simple linear regression results indicate a positive correlation between the extent of built-up land and surface temperature, with an R Square of 34.7% in 2014 and 38.9% in 2023. These findings underscore the impact of development on Land Surface Temperature (LST) and emphasize the urgency of built-up land management to mitigate heat-related urban impacts. The study highlights the need for strategic interventions and sustainable urban planning to curtail the adverse effects of rapid urbanization on environmental quality and public health.

Keywords: LST, remote sensing, urban study, NDBI, Makasar

Topic: Physical Sciences

Plain Format | Corresponding Author (Jumadi Jumadi)

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