Abstract
How to estimate vulnerability of eco-environment quickly and accurately is an important research to predict the trend of environmental change in the future. Based on the analysis of the previous methods of eco-environment assessment, we tried to build a quantitative assessment model of eco-environment vulnerability by multi-source remote sensing data. The model focuses on extracting the change information of vegetation and land cover types from remote sensing (RS) data, and reveals the law of eco-environment vulnerability change. In the process of building the model, the correlation between normalized difference vegetation index (NDVI) and topographic data was analysed. The nonlinear regression method was used to estimating vegetation coverage taken as one of the main parameters of the model. And then, the model was applied to a specific study area. The quantitative assessment used Multi temporal data obtained to calculate the vulnerability values. It described the spatial distribution and variation characteristics of eco-environmental vulnerability in this region. We also estimate the accuracy and stability of the model. The calculation results show that we can quickly evaluate regional eco-environmental vulnerability and improve the efficiency of ecological environment monitoring through our proposed model.
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