Spatial Analysis of Flood-Prone Areas in Padang Terap, Kedah: Integrating Spatial Autocorrelation and Optimized Hotspot Analysis
Flooding increasingly threatens socio-economic resilience in Malaysia, particularly in vulnerable districts such as Padang Terap, Kedah. Using a GIS-based framework integrating Spatial Autocorrelation (Moran’s I) and Optimized Hotspot Analysis (Getis-Ord Gi*), this study quantifies spatial clusterin...
Saved in:
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | en |
| Published: |
Muhammadiyah University Press
2026
|
| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/51302/1/%2819-43%29%2B10133.pdf http://ir.unimas.my/id/eprint/51302/ https://journals2.ums.ac.id/fg/article/view/10133 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Flooding increasingly threatens socio-economic resilience in Malaysia, particularly in vulnerable districts such as Padang Terap, Kedah. Using a GIS-based framework integrating Spatial Autocorrelation (Moran’s I) and Optimized Hotspot Analysis (Getis-Ord Gi*), this study quantifies spatial clustering of flood-prone areas across four inundation levels (0.3 m–3.7 m). Results reveal intensifying positive spatial autocorrelation with rising flood depths, reflecting hydrological connectivity and topographic controls. Hotspots are consistently concentrated in Belimbing Kanan, Belimbing Kiri, and Padang Temak, emphasizing severe spatial heterogeneity in flood risk distribution. These findings demonstrate that flood hazards are not randomly dispersed but spatially structured, necessitating geographically targeted risk mitigation strategies. Incorporating hotspot insights into planning can optimize resource allocation, strengthen adaptive capacity, and inform flood-resilient urban development. This research advocates for integrating fine-scale spatial analyses into national disaster frameworks to enhance Malaysia’s climate resilience agenda. Future work should embed socio-economic vulnerability metrics and spatiotemporal models to refine flood risk governance and promote equitable, anticipatory disaster management. |
|---|