Volume 6, Issue 6, December 2018, Page: 152-166
Modeling the Implication of Land Use Land Cover Change on Soil Erosion by Using Remote Sensing Data and GIS Based MCE Techniques in the Highlands of Ethiopia
Asirat Teshome Tolosa, Department of Hydraulic and Water Resources Engineering, Debre Tabor University, Debre Tabor, Ethiopia
Received: Nov. 30, 2018;       Accepted: Dec. 11, 2018;       Published: Jan. 2, 2019
DOI: 10.11648/j.ijema.20180606.12      View  325      Downloads  115
Abstract
Soil erosion is one of the natural resources which can be influenced by Land use land cover change (LCC). The main influencing factor for land use land cover change is the increase of population, which in turn resulted in land degradation. This study aimed at modeling and analyzing LCC and its effect on soil erosion. The study was conducted in the highlands of, Blue Nile Basin, Ethiopia. Three Landsat images (1986, 2000 and 2016) were used to analyze the LCC. Supervised classification using maximum likelihood algorism was used to analyze the LCC. Four land cover types (LCTs) cropland, forest, and grassland and shrubland were defined. Multi-criteria decision analysis (MCE) using the Analytic Hierarchy Process (AHP) was used to prioritize the most influencing factor for soil erosion. Five major factors; land use, slope, soil types, Topographic Wetness Index (TWI) and altitude were considered to analyze the erosion hotspot area. The result showed that cropland and grassland increased from 41.6% and 15.4% in 1986 to 58.8% and 28.3% in 2016, respectively. However, shrub-land and forest decline from 32.3% and 10.6% in 1986 to 5.6% and 7.3% in 2016, respectively. The AHP analysis showed that LCT is the most contributors for erosion. It is observed that free grazing in the area is the common practice which is the main contributor to erosion. Hence, 50% of the gully erosion is influenced by LCT. The resultant erosion risk map shows that 1.12% of the area lies under the low-risk zone, whereas 19.02%, 72.67% and 7.2% of the total area fall in medium, high and very high-risk categories respectively. The results verified by field data collected and the judgment of the experts.
Keywords
GIS, Landsat, Remote Sensing, Analytic Hierarchy Process, MCE, Supervised Classification
To cite this article
Asirat Teshome Tolosa, Modeling the Implication of Land Use Land Cover Change on Soil Erosion by Using Remote Sensing Data and GIS Based MCE Techniques in the Highlands of Ethiopia, International Journal of Environmental Monitoring and Analysis. Vol. 6, No. 6, 2018, pp. 152-166. doi: 10.11648/j.ijema.20180606.12
Copyright
Copyright © 2018 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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