Andenet Ashagrie (PhD)Muhammed Belale2024-10-282024-10-282024-06https://etd.aau.edu.et/handle/123456789/3508Urbanization poses significant challenges to the sustainability of agricultural land, which plays a crucial role in food security and local economies in rapidly urbanizing areas. The study assesses the impact of urbanization on agricultural land in Motta town using Geographic Information System (GIS) and remote sensing techniques. Land use and land cover (LULC) changes from 1992 to 2023 were analysed using Landsat satellite images from the United States Geological Survey (USGS). Both Supervised and unsupervised classification methods of classification were used to classify four land use classes namely built-up area, vegetation, bare land, and agricultural land. The study compared classification algorithms including Support Vector Machine (SVM), Maximum Likelihood Classification (MLC), and unsupervised classification based on their results and accuracy. Additionally, urbanization indices such as New Built-up Index (NBI), Urbanization intensity Index (UII), and Normalized Difference Built-up Index (NDBI) were employed to assess urbanization dynamics. Results indicate a consistent trend of agricultural land loss and built-up area increase. SVM classification shows built-up areas increasing from 323 hectares in 1992 to 607 hectares in 2023, with agricultural land decreasing from 944 hectares to 510 hectares. MLC classification similarly reveals an increase in built-up areas from 534 hectares to 757 hectares and a decrease in agricultural land from 791 hectares to 352 hectares by 2023. Unsupervised classification identifies an increase in built-up areas from 510 hectares to 910 hectares and a decrease in agricultural land from 695 hectares to 346 hectares over the studied period. Accuracy assessments confirm SVM as the most accurate method. The study concludes that urban expansion significantly diminishes agricultural land in Motta town and suggests implementing sustainable land use policies and employing satellite remote sensing for effective monitoring of urban sprawl to mitigate further agricultural land lossen-USUrbanizationAgricultural landRemote SensingMotta town.Thesis