International Journal of Disaster Risk Management (IJDRM)

International Journal of Disaster Risk Management (IJDRM)

Unveiling An Efficient Framework for Predicting Flood Risk Areas, Using Earth Observatory Data, Google Earth Engine, and Multicriteria Decision Making-Analytical Hierarchy Process

First page of “Unveiling An Efficient Framework for Predicting Flood Risk Areas, Using Earth Observatory Data, Google Earth Engine, and Multicriteria Decision Making-Analytical Hierarchy Process”, published in IJDRM, Vol. 8, No. 1 (2026).

Authors

Ishaku Bashir Yakubu
Sheikh D. Abubakar
Solomon Ndace Jiya
Yakubu Muhammad
Aisha Yakubu Aliyu

Abstract

The flood risk in the Niger-East region of Niger State is increasingly becoming an annual event. Climatic shifts, land-surface modifications, and human socioeconomic factors are among the conditions that trigger floods. This study explores geospatial technology and multicriteria decision analysis-analytical hierarchy process (MCDA-AHP) to develop a flood risk prediction system that leverages Google Earth Engine to process remote sensing data directly influencing flood risk. Elevation, slope, drainage density, rainfall, soil, proximity to drainage, proximity to road, population density, flow accumulation, and land use land cover (LULC). The weightage assignment was performed using the MCDA-AHP technique. Flood risk classes predicted as very low, 13.82 km2 (9.29%), low, 18.77 km2 (12.61%), low – moderate, 111.97 km2 (75.24%), high, 3.32 km2 (2.23%), and very high, 0.93 km2 (0.63%) of the study area, respectively. This research presents a flood emergency response system that highlights the impact of different prioritization criteria across multiple conditions. Therefore, integrating GEE to generate different flood-conditioning risk indicators, prioritized and ranked using MCDA-AHP, is crucial for developing an efficient methodological framework for flood risk prediction across a wide region, achieving 88% precision. Thus, effective for evidence-based decision-making by authorities, policy makers, and emergency response agencies.

Keywords: Google Earth Engine; MCDA-AHP; GIS; remote sensing; flood prediction; Niger East

Publication details

International Journal of Disaster Risk Management (IJDRM), Vol. 8, No. 1 (2026), pp. 201-228.

DOI: https://doi.org/10.66050/xfxaaq83

Read the full open-access article:
https://internationaljournalofdisasterriskmanagement.com/index.php/Vol1/article/view/201

Download PDF:
https://internationaljournalofdisasterriskmanagement.com/index.php/Vol1/article/view/201/210

Suggested citation

Yakubu, I. B., Abubakar, S. D., Jiya, S. N., Muhammad, Y., & Aliyu, A. Y. (2026). Unveiling An Efficient Framework for Predicting Flood Risk Areas, Using Earth Observatory Data, Google Earth Engine, and Multicriteria Decision Making-Analytical Hierarchy Process. International Journal of Disaster Risk Management, 8(1), 201-228. https://doi.org/10.66050/xfxaaq83

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