Lamya Nurul Adzkia
Department of Social Sciences Education, Syarif Hidayatullah State Islamic University Jakarta, Jl. Ir. H. Juanda No. 95, Ciputat, Ciputat Timur, South Tangerang City, Banten 15412

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GIS-Based Flood Hazard Mapping Using Weighted Overlay in Bekasi City Lamya Nurul Adzkia; Hermawan Setiawan; Andri Noor Ardiansyah
Jambura Geoscience Review Vol 8, No 2 (2026): Jambura Geoscience Review (JGEOSREV)
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jgeosrev.v8i2.37870

Abstract

Flooding remains a recurrent urban hazard in Bekasi City owing to the interaction of lowland topography, downstream hydrological position, rapid urban development, and reduced surface infiltration. This study aims to map flood hazard levels in Bekasi City using a geographically weighted overlay (GIS)-based method and to examine the spatial agreement between the modeled hazard zones and observed flood occurrences. Seven parameters were integrated into the analysis: land use/land cover, rainfall, slope, soil type, Topographic Wetness Index, distance to rivers, and distance to roads. Each parameter was standardized, scored, and weighted based on relevant literature before being combined to produce a composite flood hazard index. The resulting map classified the study area into very low, low, moderate, high, and very high hazard classes. The results show that more than 80% of Bekasi City is located within moderate to very high flood hazard classes, with higher hazard zones concentrated mainly in the central and eastern parts of the city. These areas are characterized by flat terrain, high wetness potential, proximity to river networks, and a dominant built-up land cover. A preliminary spatial validation using 12 observed flood occurrence points indicates that approximately 83% of the points are located within moderate to very high hazard zones. These findings suggest that the GIS-based weighted overlay method can support preliminary flood hazard identification in data-limited urban areas. However, the results remain sensitive to parameter selection, weighting schemes, and limited validation data.