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Item
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Application of Digital Image Processing Integration with Satellite Remote Sensing and GIS in Land Use Land Cover Change and Soil Erosion
http://hdl.handle.net/20.500.12678/0000005231
http://hdl.handle.net/20.500.12678/000000523179796a6c-8733-402a-8eeb-f7fda94b3ee5
fb3a0318-ed50-4293-a0e1-44ac43a9cf4e
Name / File | License | Actions |
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Publication type | ||||||
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Conference paper | ||||||
Upload type | ||||||
Publication | ||||||
Title | ||||||
Title | Application of Digital Image Processing Integration with Satellite Remote Sensing and GIS in Land Use Land Cover Change and Soil Erosion | |||||
Language | en | |||||
Publication date | 2008-05-05 | |||||
Authors | ||||||
Kyaw Zaya Htun | ||||||
Dr. Lal Samarakoon | ||||||
Description | ||||||
The relationship between land use land cover changes and soil erosion is investigated using digital image processing integrated with Remote Sensing (RS) and Geographic Information System (GIS) in Tonle Sap Watershed, Cambodia. The Universal Soil Loss Equation (USLE –Wischmeier and Smith, 1978) was applied to build a model to estimate the annual soil loss from the watershed in 1976 and 2002. The analysis process on land use land cover change is based on geo-processing of GIS utilizing the raster and vector analysis. The analysis result of land use land cover change between 1976 and 2002 show that the agriculture land was expanded and the forest area was decreased in the study area. A grid based and polygon based GIS were used to comparatively calculated soil loss map. The result shows that grid based method also enables the meaningful use of pixel based remotely sensed land cover information for modeling soil erosion. The result also shows that increasde soil erosion in the agriculture land and suggests that mitigation measure should be taken for prevention of further degradation. High resolution satellite images are very effective tool for not only monitoring the land use land cover change but also estimating soil erosion in the watershed. Similarly, GIS is also an effective tool in analyzing by overlaying various vector maps related to factors affecting in soil erosion. C++ programs were also developed for digital image processing such as solving LS factor and converting raw Digital Number (DN) value to reflectance valves. The main data used in this study are Landsat ETM satellite images. | ||||||
Conference papers | ||||||
JCSSE | ||||||
May 2008 | ||||||
The 5th International Joint Conference on Computer Science and Software Engineering | ||||||
Department of Computing, Faculty of Science, Silpakorn University, Thailand |