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This study quantified spatial and temporal Land-Use/Land-Cover (LULC) changes within selected six classes of land cover type from 2002 to 2022 in a tropical rainforest reserve, Southwestern Nigeria. It also identified the most dominant plant diversity in the study area. Landsat 7, 8, and 9 imageries of the United States Geological Survey were used to identify and quantify the distribution and extent of selected six classes of land cover type used with the application of Geographical Information Systems and remote sensing techniques. Data on plant dominance were obtained from fieldwork conducted within the study area. The Results revealed that between 2002 and 2022, 15112 pixels in undisturbed forests were converted to disturbed forests, 16902 pixels in disturbed forests changed to built-up, 32233 pixels to built-up, and 60 pixels in disturbed forests were converted to agricultural land. There was a rise in agricultural land (8%) and built-up areas (0.3%) while decreases in forest (disturbed and undisturbed) (5%) and bare land (3%) were observed. Results also indicated there was an increase in water bodies from 2002 to 2014 (0.004%). Health of plant species decreased from the average NDVI (Normalized Difference Vegetation Index) value of 0.60 to 0.51. Results showed that among the plants, Albizia zygia, Celtis zenkeri, and Funtumia elastic were the dominant. observed rapid conversion of forest to agricultural land and built-up areas was found to be the cause of plant diversity loss in the forest. The Findings from this study have implications for life on land and climate action.
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Tom
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art. no. e57, 2024
Opis fizyczny
Bibliogr. 77 poz., rys., tab., wykr.
Twórcy
autor
- Obafemi Awolowo University, Osun, Nigeria
autor
- Obafemi Awolowo University, Osun, Nigeria
autor
- Obafemi Awolowo University, Osun, Nigeria
Bibliografia
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Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-d1a0caf3-1a79-4dc4-937e-f06488d00381
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