11 July 2009 A study on eco-environmental vulnerability of mining cities: a case study of Panzhihua city of Sichuan province in China
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Proceedings Volume 7491, PIAGENG 2009: Remote Sensing and Geoscience for Agricultural Engineering; 74910Y (2009); doi: 10.1117/12.836929
Event: International Conference on Photonics and Image in Agriculture Engineering (PIAGENG 2009), 2009, Zhangjiajie, China
Abstract
The large-scale and super-strength development of mineral resources in mining cities in long term has made great contributions to China's economic construction and development, but it has caused serious damage to the ecological environment even ecological imbalance at the same time because the neglect of the environmental impact even to the expense of the environment to some extent. In this study, according to the characteristics of mining cities, the scientific and practical eco-environmental vulnerability evaluation index system of mining cities had been established. Taking Panzhihua city of Sichuan province as an example, using remote sensing and GIS technology, applying various types of remote sensing image (TM, SPOT5, IKONOS) and Statistical data, the ecological environment evaluation data of mining cities was extracted effectively. For the non-linear relationship between the evaluation indexes and the degree of eco-environmental vulnerability in mining cities, this study innovative took the evaluation of eco-environmental vulnerability of the study area by using artificial neural network whose training used SCE-UA algorithm that well overcome the slow learning and difficult convergence of traditional neural network algorithm. The results of ecoenvironmental vulnerability evaluation of the study area were objective, reasonable and the credibility was high. The results showed that the area distribution of five eco-environmental vulnerability grade types was basically normal, and the overall ecological environment situation of Panzhihua city was in the middle level, the degree of eco-environmental vulnerability in the south was higher than the north, and mining activities were dominant factors to cause ecoenvironmental damage and eco-environmental Vulnerability. In this study, a comprehensive theory and technology system of regional eco-environmental vulnerability evaluation which included the establishment of eco-environmental vulnerability evaluation index system, processing of evaluation data and establishing of evaluation model. New ideas and methods had provided for eco-environmental vulnerability of mining cities.
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Huaiyong Shao, Wei Xian, Wunian Yang, "A study on eco-environmental vulnerability of mining cities: a case study of Panzhihua city of Sichuan province in China", Proc. SPIE 7491, PIAGENG 2009: Remote Sensing and Geoscience for Agricultural Engineering, 74910Y (11 July 2009); doi: 10.1117/12.836929; https://doi.org/10.1117/12.836929
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KEYWORDS
Mining

Remote sensing

Minerals

Artificial neural networks

Neural networks

Environmental sensing

Evolutionary algorithms

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