GIS-Based Analysis of Land Use and Land Cover Change Dynamics in Boricha Catchment, Central Main Rift Valley Lakes Basin of Ethiopia

Abstract

Land use and land cover (LULC) classification and its change detection is very important to understand the trend and to put strategies for managing land resources globally. Even if there are many techniques for LULC classification and change detection, using remote sensing data and Arc Map is an appropriate classifier and change detector. The major aim of this study is to classify and detect LULC change of Boricha Catchment, Central Main Rift Valley Lakes Basin of Ethiopia. In this research, supervised maximum likelihood classification techniques in GIS with Google earth pro is used. Landsat 7 image of 2003 and Landsat 8 image of 2013 and 2023 is used. Change detection is done by using simple excel formula from output of GIS LULC classification. Confusion matrix is also computed for accuracy assessment of the classification. From the study, six land use classes are identified: agriculture, barren land, forest, pasture, urban and water. The overall accuracy of LULC Classification for 2003, 2013 and 2023 is 91.2%, 91.5% and 92.9% respectively. The study also showed that a significant expansion of Agriculture, settlements barren land and a significant reduction of forest, pasture and water due to population increase and urbanization. This study helps in identifying the different LULC classes and their change which give a good understanding for decision maker to plan and manage land resources to meets the needs of the present, without compromising the ability of future generations to meet their own needs in the study area.