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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/1749

Title: Landuse/ Landcover Dynamics and Erosion Susceptibility Analysis: a Case Study of Basso Werena Wereda
Authors: EPHREM, HAILE
Advisors: Dr. K.V. Suryabhagavan
Keywords: GIS
RS
landuse /cover
Susceptibility model
Copyright: Jul-2008
Date Added: 16-Dec-2008
Publisher: Addis Ababa University
Abstract: Landuse and Landcover changes between 1973 & 2000 and erosion susceptibility analysis were conducted in Basso werena wereda of North shewa zone; Amhara region, on an area of 1213 km2 using remote sensing and geographic information system (GIS) with field verifications. Information is extracted from various Satellite images of multidated Landsat images and different digital maps. In addition to these, different metrological and other data s are used for the study. Results from landcover change analysis show an increase in agriculture land from 28.96 % in 1973 to 49.98 % in 2000. The increase agriculture land was mainly at the expense of the wood land and natural forest. On the contrary, natural forest and wood land decreased from 12.19 % and 11.37 % in 1973 to 2.45 % and 0 % in 2000 respectively. Rate of landcover change and landcover conversion matrix clearly showed the dynamics of the different cover classes over the study periods. The result of erosion susceptibility analysis showed that around 35.61 % of the area is highly susceptible, 35.93 % susceptible, 16.35 % moderately susceptible, 7.31 % less susceptible and 4.80 % is very less susceptible to water erosion. The majority of the area falls on highly susceptible and susceptible to erosion (71.54%). The resultant erosion susceptibility map along with the landuse /landcover and structural dynamics can serve local planners and scientists as a primary source of information for natural resource management (NRM) of the study area.
Description: A THESIS SUBMITED TO THE SCHOOL OF GRADUATE STUDIES IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN GIS AND REMOTE SENSING
URI: http://hdl.handle.net/123456789/1750
Appears in:Thesis - Earth Sciences
Thesis - Earth Sciences

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