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Research Article Open access CC BY 4.0

Spatio-Temporal Classification and Prediction of Land Use and Land Cover Change in Finima Nature Park Bonny Island, Nigeria

R. E. Ubaekwe, U. D. Chima, F. S. Eguakun

Journal of Geography, Environment and Earth Science International · pp. 40–53 · Published 13 Sep 2022

10.9734/jgeesi/2022/v26i830367

Abstract

Land Use Land Cover (LULC) is naturally dynamic, thus change is inevitable. However, its changes have greatly increased to a frightening proportion as a result of high rate of anthropogenic and natural processes. Consequently, land use and land cover classes of Finima Nature Park were classified and changes were observed within the last 33 years (1987 - 2021) and predicted for the next 33 years (2021 – 2054). Remote sensing and Geographic Information System (GIS) were used to achieve the goal. Coordinate points were collected from the various land use and land cover classes as a reference data for accuracy assessment of the classification. Landsat imageries of 1987, 1999, 2010 and 2021 were acquired from The United States Geological Survey (USGS). The imageries were pre-processed, processed and classified into various LULC classes using Maximum Likelihood Classification in Idrisi and ArcGis10.5. Confusion matrix and Cellular Automata (CA) Markov Chain algorithm were used for accuracy assessment and prediction of LULC respectively. Results showed that dense vegetation, sparse vegetation, bare land, and water body were the main LULC class in 1987 and 1999, while dense vegetation, sparse vegetation, bare land, water body and built up were observed in the years 2010, 2021 and 2054. The Kappa Coefficient values were 93%, 81%, 83% and 90% for 1987, 1999, 2010 and 2021 respectively; an indication of strong accuracy of the classification. Generally, there were changes in land use and land cover within the study periods. However, changes were mostly observed in the areas of water body and bare lands closer to the sea coast. Hence, the sea was implicated as the major driver of land use and land cover change in the park. The slight decrease in dense vegetation and sparse vegetation from 1999 to 2021, and 2021 to 2054 underscores the importance and benefit of conservation.

Land use land cover change detection mapping modelling remote sensing GIS

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