Spatial prioritization of urban green open space development using weighted overlay analysis
DOI:
https://doi.org/10.61511/srsd.v2i1.2025.1707Keywords:
green open space, weighted overlay analysis, NDVI, THIAbstract
Background: Urban areas are ecosystems where plants, animals, humans, and infrastructure interact. Green open spaces (GOS) like parks are vital in cities for facilitating this interaction. However, rapid urbanization and limited land often lead to the conversion of green spaces into built-up areas, which increases urban temperatures, disrupts ecosystems, and lowers the quality of life for city dwellers. The allocation of GOS development is often not aligned with the community's actual needs. This study aims to determine the priority locations for GOS development in Mataram City using the Weighted Overlay method in the ArcGIS application. Method: This study employs a qualitative approach using spatial analysis through the Weighted Overlay method in ArcGIS. Three key variables are considered: the comfort index (THI), vegetation density (NDVI), and population density. The data from these variables are combined to assess and prioritize areas in Mataram City for GOS development. Findings: The analysis shows that the sub-districts of Mataram and Cakranegara have the highest priority for GOS development, based on the combined analysis of comfort index, vegetation density, and population density. These areas require more green space to improve environmental quality and meet the community’s needs. Conclusion: The study highlights the importance of prioritizing GOS development in Mataram and Cakranegara sub-districts. It suggests that urban planning policies in Mataram City should focus on these areas to enhance urban living conditions and mitigate environmental degradation caused by limited green spaces. Novelty/Originality of this article: This research is unique in applying the Weighted Overlay method in ArcGIS to evaluate and prioritize GOS locations based on multiple urban variables. It provides valuable insights for urban planners, offering a data-driven approach to address the challenges of green space distribution in urban environments.
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