Assessment of Land Use Land Cover Dynamics and Soil Erosion Susceptible Modeling in Amhara Regional State: Case Study at Dessie Zuria Woreda Using Remote Sensing and Gis

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Addis Ababa Universty


Spatial data processing especially using GIS techniques has been playing an important role in different applications. Multiple source spatial and non-spatial data can be processed and integrated for the analysis of spatio-temporal dimension of a given area. In this study, land use/cover dynamics that occurred from 1973 to 2000 & potential area to soil erosion have been identified. The main objective of the study is to assess land use land cover dynamics for the last 27 years and to identify soil erosion susceptible area. To this end, remotely sensed data i.e. Landsat satellite images of 1973 MSS, 1986TM and 2000ETM+ have been used to produce land use land cover classes and to see the dynamics using Geographical Information System (GIS).The results in this research for the last 27 years are the following. From 1973 to 1986 agriculture and bare lands have been increased with 7348.8 ha and 3998.9 ha, respectively. The main factor of this is population growth in the area. While forest, bush and grass lands have been diminished by 2152.7, 2381.7, and 6386.5ha, respectively. From 1986 to 2000, only agricultural lands have been expanded by 2282.8 ha, while bare, forest, bush and grass lands have been decreased with 272.3, 4.1, 241.7 and 1765.2 ha, respectively. The dynamics have been detected and supported with NDVI statistics. It indicates that there has been increasing forest degradation in the Study area. Agricultural lands have been analyzed with slope and soil erosion susceptible areas. In both cases, such land class has been expanded. This is the best indicator of the scarcity of agricultural land in the area. As a result people have been forced to use marginal land. This is also the main factor to increase bare/degraded land. To sum up the conclusion; land use/cover dynamics have been detected and analyzed with the input data of landsat image using GIS to understand the trend in short period of time, least cost and in effective manner. However, for sound decision making process, other data such as socio-economic should be used and integrated in GIS. Key words: Land use/ cover Dynamics, Land Degradation (forest degradation),soil erosion Modeling, Remote Sensing and GIS



Land use/ cover Dynamics, Land Degradation (forest degradation), Soil erosion Modeling, Remote Sensing and GIS