Spatiotemporal dynamics of land use/land cover changes and its drivers in Bilate watershed, central rift valley, Ethiopia
Land use/land cover (LULC) changes influence the ecological function, consequence on ecosystem services, which are tightly linked to human wellbeing. However, quantification of the LULC changes and identifying the underlying factors remain patchy particularly in developing nations, despite this information is crucial to propose a feasible restoration action. Therefore, this study investigates the land use/land cover changes and its drivers in central Rift Valley, Ethiopia. GIS and Remote sensors i.e. Landsat 5 (TM), and Landsat 8 (OLI/TIRs) imagery sensors acquired from USGS, and field observation were used. Using the supervised classification method and the support of ArcGIS 10.5 and ERDAS IMAGINE 2014, all images were classified into various land cover types. Focus group discussions, key informant interviews, and structured questionnaire surveys were used to investigate the drivers of LULC change. NDVI was used to detect the vegetation cover change. Woodland, grassland, and barren lands were the major LULC types identified in this study. After 28 years, the woodland cover increased from 20.6% to 40.2% whereas the barren land decreased from 43.4% to 22.6%. Grassland showed very slight increment, i.e. from 35.9% to 36.9%. This implies that area enclosure plays a significant role in the restoration of degraded lands. The highest NDVI values (0.6) were determined in the year 2022 at the end of the classification. Focus group discussants and key informants confirmed that human-induced factors were the major drivers of LULC changes in the study area. Our findings indicated that human interventions are the key determinants of land use/land cover dynamics, and as a result, enforcement of the law and public education campaigns to change human behavior in support of the area enclosure approach are essential to restoring degraded land for the benefit and wellbeing of humans and nature while also advancing the achievement of the global goals.
How to Cite
Area enclosure, Conservation, Landsat images, Restoration, Vegetation cover
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