Integrating Satellite Imagery and Multicriteria Decision Analysis for High-Resolution Flood Vulnerability Mapping: A Case Study of Jakarta, Indonesia

Jakarta, Indonesia, ranks among the most flood-prone megacities in the world, with hydrometeorological factors placing up to 98% of its area at flood risk. Its population density—approximately 15,900 individuals per square kilometer—compounds the impacts of flooding through intensified exposure and socio-economic vulnerability. This study presents a novel, data-driven methodology for flood vulnerability assessment in the Jakarta Special Capital Region (DKI Jakarta), integrating satellite remote sensing and geospatial analysis with a Multicriteria Decision Analysis (MCDA) framework. Employing the Analytical Hierarchy Process (AHP) to systematically weight environmental and socio-economic criteria, a Flood Vulnerability Index (FVI) was developed and spatially modeled at a 500-meter grid resolution. The resulting FVI map categorizes vulnerability into five levels: very low, low, moderate, high, and very high. Findings indicate an index range between 0.36 and 0.70, highlighting predominantly moderate to high vulnerability zones across the region. This high-resolution assessment provides actionable insights for disaster risk reduction, urban resilience planning, and targeted policy interventions to mitigate flood-related hazards in Jakarta.

Authors

Institutions

Publication Details

Journal
International Journal of Advances in Data and Information Systems
Published
2025-07-12
DOI
https://doi.org/10.59395/ijadis.v6i2.1388
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Integrating Satellite Imagery and Multicriteria Decision Analysis for High-Resolution Flood Vulnerability Mapping: A Case Study of Jakarta, Indonesia

Arie Wahyu Wijayanto, Atut Pindarwati, Perani Rosyani, Meilinda Fitriani Nur Maghfiroh
International Journal of Advances in Data and Information Systems
Flood Risk Assessment and Management
article

Integrating Satellite Imagery and Multicriteria Decision Analysis for High-Resolution Flood Vulnerability Mapping: A Case Study of Jakarta, Indonesia

Arie Wahyu Wijayanto, Atut Pindarwati, Perani Rosyani, Meilinda Fitriani Nur Maghfiroh
article en

Abstract

Jakarta, Indonesia, ranks among the most flood-prone megacities in the world, with hydrometeorological factors placing up to 98% of its area at flood risk. Its population density—approximately 15,900 individuals per square kilometer—compounds the impacts of flooding through intensified exposure and socio-economic vulnerability. This study presents a novel, data-driven methodology for flood vulnerability assessment in the Jakarta Special Capital Region (DKI Jakarta), integrating satellite remote sensing and geospatial analysis with a Multicriteria Decision Analysis (MCDA) framework. Employing the Analytical Hierarchy Process (AHP) to systematically weight environmental and socio-economic criteria, a Flood Vulnerability Index (FVI) was developed and spatially modeled at a 500-meter grid resolution. The resulting FVI map categorizes vulnerability into five levels: very low, low, moderate, high, and very high. Findings indicate an index range between 0.36 and 0.70, highlighting predominantly moderate to high vulnerability zones across the region. This high-resolution assessment provides actionable insights for disaster risk reduction, urban resilience planning, and targeted policy interventions to mitigate flood-related hazards in Jakarta.

International Journal of Advances in Data and Information SystemsVol. 6(2)
Muscat College (OM), Universitas Pamulang (ID)
Openalex Percentile: Top 84%
Flood Risk Assessment and Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.