The study assessed the effects of land use drivers on vegetation diversity, and projected the. To achieve these objectives, the study used remotely sensed image data and direct field observation. Landsat imageries of 1986, 2003 and 2022 were utilized for pre-processing of data, employing unsupervised classification. A total of 400 copies of questionnaire were used to determine the drivers of land use change; direct field study was used to examine the current vegetation status in the area. Multiple Linear Regression was used to determine the main drivers of land use land cover change in the study area.
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