Abstract:
Land use/ land cover change has become a central component in current strategies for managing
natural resources and monitoring environmental changes. Hence, information about it is essential
for the selection, planning and implementation of land use schemes. This project examines the use
of GIS and Remote Sensing in mapping Land Use/Land Cover in Soro District between 1987 and
2017 so as to detect and analyze the changes that has taken place in their status between these
periods. In order to achieve these, satellite data of Landsat MSS for 1987, TM for 2002 and ETM
for 2017 have been obtained and preprocessed using ERDAS Imagine. 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 show that cultivated land decreased in the first period but increased in
the second and the entire study periods. Grassland increased in the first period and decreased in
the second period. Wetland is the most converted cover type during the entire study period and
forest increased in first study period and decreased in second study period. The impact of this
LULC change is more significant on the socioeconomic condition and status of the study area.
