Linear Spectral Un-mixing
Applications In Land Degradation Assessment
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Land degradation is one of the most important limiting factors that hold back agricultural productivity. Overcoming this limitation requires planned action to take control measures. Land degradation assessment is an input for this planed action. Models play vital role making land degradation assessment easy. The USLE is commonly used model to predict annual soil loss. Slope and Slope length (LS), Erosovity (R) Soil Erodibilty (K) and Crop/cover (C) factors are parameters employed to predict potential annual soil loss. Several methods have been in use to determine the crop cover factor. With th...
Land degradation is one of the most important limiting factors that hold back agricultural productivity. Overcoming this limitation requires planned action to take control measures. Land degradation assessment is an input for this planed action. Models play vital role making land degradation assessment easy. The USLE is commonly used model to predict annual soil loss. Slope and Slope length (LS), Erosovity (R) Soil Erodibilty (K) and Crop/cover (C) factors are parameters employed to predict potential annual soil loss. Several methods have been in use to determine the crop cover factor. With the advent of technology, nowadays, satellite imagery is predominantly, used. This book covers how Linear Spectral Mixture Analysis and Change Vector Analysis (CVA) can be used to determine land cover of an area of interest and the changes that have taken place over a certain period of time, respectively. The technique can be used by professionals involving in natural resource management and conservation planning. It enhances efficiency while maximizing the accuracy of the model to represent the truth on the ground.
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