Mapping Environmental Vulnerability from ETM + Data in the Yellow River Mouth Area
WANG Rui-yan1, 2, 3, YU Zhen-wen1*, XIA Yan-ling4, WANG Xiang-feng5, ZHAO Geng-xing2, JIANG Shu-qian2
1. College of Agronomy，Shandong Agricultural University，Tai’an 271018, China 2. College of Resources and Environment, Shandong Agricultural University, Tai’an 271018，China 3. National Engineering Laboratory for Efficient Utilization of Soil and Fertilizer Resources，Tai’an 271018，China 4. College of Geography and Planning，Ludong University，Yantai 264025，China 5. Bureau of Land and Resource of Kenli County，Kenli 257500，China
Abstract：The environmental vulnerability retrieval is important to support continuing data. The spatial distribution of regional environmental vulnerability was got through remote sensing retrieval. In view of soil and vegetation, the environmental vulnerability evaluation index system was built, and the environmental vulnerability of sampling points was calculated by the AHP-fuzzy method, then the correlation between the sampling points environmental vulnerability and ETM + spectral reflectance ratio including some kinds of conversion data was analyzed to determine the sensitive spectral parameters. Based on that, models of correlation analysis, traditional regression, BP neural network and support vector regression were taken to explain the quantitative relationship between the spectral reflectance and the environmental vulnerability. With this model, the environmental vulnerability distribution was retrieved in the Yellow River Mouth Area. The results showed that the correlation between the environmental vulnerability and the spring NDVI, the September NDVI and the spring brightness was better than others, so they were selected as the sensitive spectral parameters. The model precision result showed that in addition to the support vector model, the other model reached the significant level. While all the multi-variable regression was better than all one-variable regression, and the model accuracy of BP neural network was the best. This study will serve as a reliable theoretical reference for the large spatial scale environmental vulnerability estimation based on remote sensing data.
王瑞燕1, 2，3，于振文1*，夏艳玲4，王向锋5，赵庚星2，姜曙千2 . 黄河口地区环境脆弱性的遥感反演 [J]. 光谱学与光谱分析, 2013, 33(10): 2809-2814.
WANG Rui-yan1, 2, 3, YU Zhen-wen1*, XIA Yan-ling4, WANG Xiang-feng5, ZHAO Geng-xing2, JIANG Shu-qian2 . Mapping Environmental Vulnerability from ETM + Data in the Yellow River Mouth Area . SPECTROSCOPY AND SPECTRAL ANALYSIS, 2013, 33(10): 2809-2814.
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