Authors : Ntor Charles; Dorka Nwidag Daniel; Odiji Caleb; Clifford-Osawaru Wisdom Osamudiamen; Ubido Benjamin

Volume/Issue : Volume 11 - 2026, Issue 10 - October

Google Scholar : https://tinyurl.com/btrxky2e

DOI : https://doi.org/10.38124/ijisrt/26Oct1055

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

Abstract : Ogoniland, in Nigeria's Niger Delta, has experienced more than six decades of oil exploration, environmental pollution, and population pressure, yet its landscape change remains poorly quantified at the local scale. This study examined the spatio-temporal dynamics of land use and land cover (LULC) in Ogoniland between 1990 and 2025 using multi-temporal Landsat imagery acquired at five-year intervals. Images were classified into six classes (built-up, cropland, grassland, forest, mangrove, and water body) using the Random Forest algorithm, and vegetation condition was assessed with the Normalized Difference Vegetation Index (NDVI) in Google Earth Engine. Overall classification accuracy ranged from 84.2% to 88.6%, with Kappa coefficients of 0.825–0.868.

Keywords : Land Use/Land Cover Change; NDVI; Random Forest; Remote Sensing; Ogoniland; Niger Delta.

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