MODELING INFLUENCE OF URBAN SPRAWL ON URBAN HEAT ISLAND (UHI) ACTIVITY IN KOLAKA REGENCY
Authors
Satriawan Nadhrotal Atsidiqi , Eko Hadi Sujiono , Husain HusainDOI:
10.29303/ipr.v8i1.385Published:
2024-12-13Issue:
Vol. 8 No. 1 (2025)Keywords:
Urban Sprawl, UHI, WRF, BIG, VerficationArticles
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Abstract
The expansion of urban areas into rural regions, known as Urban Sprawl, contributes to the Urban Heat Island (UHI) phenomenon, where urban areas exhibit higher temperatures than their rural counterparts. Kolaka Regency is an area with significant potential for Urban Sprawl and subsequent UHI activity. Therefore, it is essential to investigate the impact of Urban Sprawl on UHI in the Kolaka region. This study simulates these changes using the Weather Research and Forecasting (WRF) model, incorporating land cover data from the Geospatial Information Agency (BIG) with four urban schemes: SLUCM, BEM, and the default non-UCM/land cover. The simulation also includes the Kolaka 2042 development map for Urban Sprawl projections. Simulations were conducted over 48 non-rainfall events across 12 months. The results indicated that the WRF BIG-BEM model demonstrated the highest verification accuracy and the lowest errors, with a MAPE of 4.70%, CRMSE of 1.06°C, and a correlation coefficient of 87.62%. Including BIG land cover and the BEM urban scheme enhanced the model's performance, with a MAPE of 17.92%, CRMSE of 10.11%, and a correlation improvement of 3.18%. The UHI effect predominantly ranged from -2.0 to 2.5°C, with the highest values observed in the Pomalaa mining area and central Kolaka Regency. The UHI effect was most pronounced from evening to morning, peaking during the night and early morning hours, with increased intensity during the dry season from July to September. Regression analysis revealed a trend of increasing UHI following Urban Sprawl activity, with a trend rate of 0.91°C. The R-squared value of 96.69% indicates that Urban Sprawl activity accounted for 96.69% of the UHI intensity in Kolaka, while other unexamined variables influenced 3.31%.References
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