Land Use Analysis using GIS, Radar and Thematic Mapper in Ethiopia

DMG ’10: Proceedings of the 1st ACM SIGSPATIAL International Workshop on Data Mining for Geoinformatics, 2010

Haile K. Tadesse

“Land degradation, and poverty issues are very common in our world, especially in developing countries in Africa. There are fewer adaptation strategies for climate change in these countries. Ethiopia is a tropical country found in the horn of Africa. The majority of the population live in rural areas and agriculture is the main economic sector. Extensive agriculture has resulted in an unexpected over-exploitation and land degradation. The project locations are Southwestern and Northwestern Ethiopia. The main objectives are to analyze the accuracy of land use classification of each sensors, classification algorithms and analyze land use change. Thematic Mapper (TM) and Radar data will be used to classify and monitor land use change. Two consecutive satellite images will be used to see the land use change in the study area (1998, 2008). ERDAS Imagine will be used to resample and spatially register the Radar and TM data. The image classification for this research study is supervised signature extraction. The Maximum likelihood decision rule and C4.5 algorithm will be applied to classify the images. TM and Radar data will be fused by layer staking. The accuracy of the digital classification will be calculated using error matrix. Land change modeler will be used for analyzing and predicting land cover change. The impact of roads, urban and population density on land use change will be analyzed using GIS.”