Assessing urban land use change and MRT impact: A case study of Cheras, Kuala Lumpur

Nuriah Abd Majid, Nurzahidah Mohd Zaki

Abstract


Understanding the spatial variability in the relationship between land use patterns and the impact of MRT infrastructure is essential for selecting effective strategies to manage and sustain urban development. Urbanization significantly influences land use configurations and environmental sustainability. This study applies Geographically Weighted Regression (GWR) to examine urban land use changes within Cheras, Kuala Lumpur, emphasizing spatial variation in the factors driving these changes. By utilizing spatially explicit datasets and GWR modelling, the research identifies localized determinants of land use dynamics and explores their implications for environmentally sustainable urban planning. The analysis was conducted using GWR 4.0 software, while ArcGIS 10.8 was employed for spatial mapping and further analysis. GWR, a local statistical technique, is capable of capturing the spatial variation of non-stationary variables and their corresponding regression coefficients, thereby modelling spatially differentiated relationships. The model’s performance was assessed using various goodness-of-fit indicators. The corrected Akaike Information Criterion (AICc) improved significantly, decreasing from 1990.12 to -1602.32, while the Bayesian Information Criterion (BIC) rose from 2006.89 to 6036.47. Furthermore, the R-squared value increased from 0.01 to 0.86 and the adjusted R-squared rose from 0.009 to 1.22. These improvements indicate that GWR provides a superior local fit compared to global models. The analysis of local parameter estimates revealed that proximity to MRT stations significantly influences land use changes in the study area. These findings highlight the necessity for localized and spatially sensitive planning approaches to effectively address the diverse challenges of urbanization and to foster sustainable urban growth.

 

Keywords: Geographical Weighted Regression (GWR), land use change, land use patterns, Mass Rapid Transit (MRT), urban, urban planning


Keywords


Geographical Weighted Regression (GWR), land use change, land use patterns, Mass Rapid Transit (MRT), urban, urban planning

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