Authors : Sultan Kamal Abdulazeez; Matthew O. Adepoju; Godstime K. James; Salami Victor Taiwo; Ernest Afogbon; Belinda Odia O.; Odeh Augustine Abah; Mohammed Ismail

Volume/Issue : Volume 11 - 2026, Issue 8 - August

Google Scholar : https://tinyurl.com/4ddztwry

DOI : https://doi.org/10.38124/ijisrt/26aug921

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Riverine flooding along the River Niger is a recurrent hazard with substantial implications for settlements, agriculture, infrastructure and disaster management in Nigeria. This study assessed and monitored flood inundation along a 5 km corridor of the River Niger for the period 2015–2023 using Sentinel-1 Synthetic Aperture Radar (SAR), Google Earth Engine (GEE) and complementary geospatial datasets. Annual flood footprints were derived from pre-flood and floodperiod Sentinel-1 observations using a backscatter-change workflow, speckle filtering, threshold classification, terrain and permanent-water masks, and connected-pixel refinement. The mapped flood extents were intersected with population, cropland and settlement datasets to estimate exposure and to construct an annual settlement-inundation matrix. Internal consistency checks were applied to the annual statistics and the full 817-settlement matrix. The largest mapped event occurred in 2018, when 1,000,009 ha were inundated, an estimated 394,951 people were exposed and 18,467 ha of cropland intersected the flood footprint. Other high-exposure years included 2015, 2020 and 2022. Analysis of the settlement matrix identified 310 of 817 settlement records as recurrent hotspots, defined as inundation in at least four of the nine years, while 14 settlement records were inundated in all nine years. The results reveal marked interannual variability but also persistent spatial recurrence in both upstream and downstream sections of the corridor. The study demonstrates the operational value of open Sentinel-1 data and cloud computing for repeatable flood surveillance and provides a spatial evidence base for early warning, anticipatory action, floodplain planning, agricultural preparedness and targeted resilience investments along the River Niger.

Keywords : River Niger; Flood Inundation; Sentinel-1 SAR; Google Earth Engine; Population Exposure; Cropland Exposure; Inundation Frequency; Nigeria.

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