GEOGRAPHICALLY WEIGHTED REGRESSION MODELING IN ANALYZING FACTORS INFLUENCING THE URBAN HEAT ISLAND PHENOMENON IN MAKASSAR CITY: SUSTAINABLE MITIGATION EFFORTS

Abstract

Background:Urban Heat Island (UHI) is a phenomenon of urban microclimate change that has become a significant issue and challenge in environmentally sustainable regional development planning. This study aims to comprehensively analyze the intensity of UHI growth across each district in Makassar City. In addition, the study highlights the importance of identifying the most influential factors contributing to the growth of the UHI phenomenon, with the ultimate goal of generating sustainable mitigation efforts.

Method: The analytical method in this study employs a spatial statistical approach using spatial analysis and Geographically Weighted Regression (GWR) modeling to examine the growth of UHI and the key influencing factors. The GWR analysis includes a Multicollinearity Test of Independent Variables, a Spatial Heterogeneity Test (using the Breusch-Pagan method), Euclidean Distance Calculation, Spatial Weighting with three types of kernels, selection of the best model for GWR analysis, significance testing of variables in each region, and ultimately results in grouping regions based on their influencing variables.

Results: The results of the study show that anthropogenic activities significantly impact environmental temperatures. Consequently, the environmental factors affecting surface temperature vary across districts in Makassar City, with NDVI, elevation, green area, and NDBI identified as significant variables that contribute to either the increase or decrease in temperature as a response to ongoing anthropogenic activities.

Conclusion: These findings form the basis for recommendations to mitigate the Urban Heat Island effect through increased vegetation, population density management, and adaptive spatial planning design based on the spatial characteristics of each region.