GIS and Remote Sensing based Land Use/Land Cover Change Detection: The Case of Kility Watershed

The land cover and land use changes are caused by both, natural and anthropogenic factors. This study was conducted in kility Watershed, Amhara Region, North western Ethiopia. The objective of this study was to detect and analyse LULC changes in the watershed. The study has used ArcGIS10.3 and ERDAS IMAGINE 15, Landsat images of 1986 and 2002; Sentinel 2 image for 2019 to analyse land cover and land use changes of Kility watershed. In addition, the survey was conducted to detect the land use class and their drivers of changes. The Maximum Likelihood Algorithm of Supervised Classification has been used to generate land use and land cover maps. For the accuracy of classified Land Use/Land Cover maps, a confusion matrix was used to derive overall accuracy and results were above the minimum and acceptable threshold level. Post classification comparison change detection method was employed to identify gains and losses between Land Use/Land Cover classes. The satellite image results showed that Bush land decreased in the first period but increased in the second and the entire study periods. Grassland increased in the first period and increased in the entire periods. Agricultural land is the most converted cover type during the second study period. In the 33 years, forest lands expanded by over 8.48 % of the original forest cover what was existed at the base year. Settlement area which was not found in the first two study years satellite image result have 1.46 % proportion in 2019 Land Use/Land Cover classification.