LANDUSE/LANDCOVER PREDICTION USING REMOTE SENSING DATA AND LAND CHANGE MODELER (LCM) IN BANIKOARA DISTRICT, BENIN

dc.contributor.authorOREKAN, Vincent O. A.
dc.contributor.authorADIMI, Olatondji S.C.
dc.date.accessioned2026-06-02T16:06:57Z
dc.date.available2026-06-02T16:06:57Z
dc.date.issued2018
dc.description.abstractThe landuse/landcoverchange has important role in environmental changes. This study aims to analyze the trend in landuse and landcover (LULC) changes and simulate these changes by the horizon 2025 and 2050.The methodology is based on Landsat ETM+ and Landsat OLI-TIRS image segmentation after color composite using PIR, Red and Green bands (543 for OLI-TIRS and 432 for ETM+) and supervised classification using IDRISI Selva. The module LCM of IDRISI Selva was also used for landuse and landcover prediction. The LCM is based on Markov chain. The result reveals that in 2000 and 2013, the savannah and light forest considerably decrease in profit of farm and fallow land and this tendency will continue to 2050. The dense and gallery forest decrease also between 2000 and 2013 but they will increase between 2013 and 2050. That is justified by the presence of protected area.
dc.identifier.otherBECDB-9783
dc.identifier.urihttps://dspace.uac.bj/handle/123456789/8716
dc.language.isofr
dc.relation.ispartofLagos Journal of Geo-Information Sciences (LJGIS)
dc.subjectLULC
dc.subjectLand Change Modeler
dc.subjectBanikoara
dc.titleLANDUSE/LANDCOVER PREDICTION USING REMOTE SENSING DATA AND LAND CHANGE MODELER (LCM) IN BANIKOARA DISTRICT, BENIN
dc.typeArticle

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