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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/2377

Title: Multi-temporal Satellite Image Analysis for Assessing Land Degradation; A Case Study on South Wollo Zone, Doyach Watershed
Authors: Hudad, Barry
Advisors: Dr. Mohammed Umer
Keywords: NDVI
USLE
Landuse/landcover
Copyright: Jun-2010
Date Added: 3-May-2012
Publisher: AAU
Abstract: Land degradation in terms of soil erosion is a major environmental issue to maintain sustainable livelihood in Ethiopia. This study attempted to assess land degradation severity by integrating Lu/Lc and social parameters (population density) in spatial approach. Soil erosion and population density parameters were modeled in conjunction with Remote Sensing and GIS for resources monitoring, while household survey had been conducted for socioeconomic status assessment to identify cause and effect of the watershed degradation. The two landsat images (1986 and 2010) were classified into five major landuse/landcover classes based on supervised classification method in ArcGIS software. Post classification change detection among two classified images was conducted. Soil erosion susceptibility was estimated through Universal Soil Loss Equation (USLE). On the other hand, NDVI images analysis comparison also done to look into the vegetation/ landcover degradation or change between 1986 and 2010 images. From the classification result classes are classified as Agricultural land and degraded/barren lands were expanding in areal coverage at the expense of others. However, forest land and grazing lands of the study area became reduced in size in the time span of 1986 to 2010its result implies a decline in landcover taking the standard deviation variation in to account. The estimated annual soil loss for the study area ranges from 0.02 to 374.2 t/ha/yr. These values were classified in to five classes or degree of soil erosion depending on the calculated soil erosion amount. The estimated annual soil loss was evaluated against landuse/ landcovers classes. Knowing extent and severity of the land is important as a decision support system to policy makers, resource managers as well as local communities and farmers. The result of this assessment showed spatial distribution of different land degradation severity across the area in watershed basis.
URI: http://hdl.handle.net/123456789/2377
Appears in:Thesis - Earth Sciences

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