INTEGRATION OF SPATIAL PRINCIPAL COMPONENT ANALYSIS WITH REMOTE SENSING AND GIS TO DEVELOP ECO-ENVIRONMENTAL VULNERABILITY INDEX MODEL FOR MOUNTAINOUS REGIONB. Ganeshkumarl and R. Gobinath
Mountainous regions are fragile ecosystems that can easily subjected to vast degradation due to anthropo-genic activities. To asses the vulnerability of various mountain regions to the impact due to human kind many eco-environmental variables have to be calculated and analysed. Present work attempts to develop an eco-environmental vulnerability index model by integrating Spatial Principal Component Analysis (SPCA) with remote sensing and as for Kotagiri taluk, Nilgiris district which is characterized by complex distri-bution of hills and valleys. Seven eco-environmental vulnerability variables such as elevation, slope, land use, vegetation, soil, soil-water erosion and population density are considered in this study. Thematic layers indicating the vulnerability variables are included in this model to calculate eco-environmental vul-nerability index (FEW) and Eigen matrices are formed to find out EEVI values. With this model output, cluster principle is used for the gradation of vulnerability level. A five level standard vulnerability classi-fication data is used to compare the result. Results obtained shows that the eco-environmental vulnerabil-ity in the study area is at potential level. This model will provide a support to decision makers during the Unplementalion of eco-envinmmental protection policies in future
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