Classification of Flood-Prone Areas in Padang City Using Landsat-9 Satellite Imagery

Flood-susceptibility mapping requires spatial information that captures the combined influence of hydrological conditions, topography, soils, and land cover. This study classified and mapped flood-prone areas in Padang City by integrating six parameters: rainfall, elevation, slope, distance from rivers, soil type, and land use/land cover. A quantitative spatial approach using Geographic Information Systems (GIS) was employed. Land cover was classified from Landsat-9 Collection 2 Level-2 imagery using the Classification and Regression Trees (CART) algorithm in Google Earth Engine. The six parameters were subsequently scored, weighted, and integrated through weighted-overlay analysis. The land-cover classification achieved an overall accuracy of 85.17%, while the overlay analysis delineated five flood-susceptibility classes. Moderate susceptibility occupied the largest area, covering 30,675.414 ha (45.79%), followed by high susceptibility at 17,631.140 ha (26.32%), low susceptibility at 17,226.524 ha (25.72%), very high susceptibility at 1,420.275 ha (2.12%), and very low susceptibility at 31.048 ha (0.05%). These findings reveal substantial spatial variation in flood susceptibility across Padang City, with moderate susceptibility predominating. The study provides an integrated spatial assessment to support disaster mitigation and environmentally responsive land-use planning.

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Publication Details

Journal
Journal of Multidisciplinary Science MIKAILALSYS
Published
2026-11-02
DOI
https://doi.org/10.58578/mikailalsys.v4i3.12469
Primary Topic
Flood Risk Assessment and Management
Type
article
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article

Classification of Flood-Prone Areas in Padang City Using Landsat-9 Satellite Imagery

Pakhrur Razi, Nofi Yendri Sudiar, Yohandri, Ramona Fitria
2 links
Journal of Multidisciplinary Science MIKAILALSYS
Flood Risk Assessment and Management
article

Classification of Flood-Prone Areas in Padang City Using Landsat-9 Satellite Imagery

Pakhrur Razi, Nofi Yendri Sudiar, Yohandri, Ramona Fitria
article en

Abstract

Flood-susceptibility mapping requires spatial information that captures the combined influence of hydrological conditions, topography, soils, and land cover. This study classified and mapped flood-prone areas in Padang City by integrating six parameters: rainfall, elevation, slope, distance from rivers, soil type, and land use/land cover. A quantitative spatial approach using Geographic Information Systems (GIS) was employed. Land cover was classified from Landsat-9 Collection 2 Level-2 imagery using the Classification and Regression Trees (CART) algorithm in Google Earth Engine. The six parameters were subsequently scored, weighted, and integrated through weighted-overlay analysis. The land-cover classification achieved an overall accuracy of 85.17%, while the overlay analysis delineated five flood-susceptibility classes. Moderate susceptibility occupied the largest area, covering 30,675.414 ha (45.79%), followed by high susceptibility at 17,631.140 ha (26.32%), low susceptibility at 17,226.524 ha (25.72%), very high susceptibility at 1,420.275 ha (2.12%), and very low susceptibility at 31.048 ha (0.05%). These findings reveal substantial spatial variation in flood susceptibility across Padang City, with moderate susceptibility predominating. The study provides an integrated spatial assessment to support disaster mitigation and environmentally responsive land-use planning.

Journal of Multidisciplinary Science MIKAILALSYSVol. 4(3)
State University of Padang (ID)
Sustainable cities and communities, Clean water and sanitation, Climate action, Life on land
Openalex Percentile: Top 20%
Flood Risk Assessment and Management
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