Chinese Journal of Applied Ecology
Previous Articles Next Articles
PENG Jian, TAO Jing-xian, LIU Yan-xu
Online:
Published:
Abstract: Because the ability of selected indicators in assessing ecological risk at different temporal scales is not the same, it is necessary to clear the definite comparability of such indicators at temporal scale to explore a new method for dynamic assessing the ecological risk. In this case, five mining cities in Liaoning Province were selected as the study area, with the application of learning vector quantization (LVQ) neural network, the significance of the indicators for the ecological risk assessment was quantitatively analyzed to clarify their characteristics at temporal scale. The expression with twodimension (long-term and shortterm) of temporal scale was put forward as a new method to assess the ecological risk for mining cities. The results showed that the amount of industrial SO2 removed per output value, the amount of industrial dust removed per output value, coverage rate of urban green space, precipitation, coordination degree among subsystems, percentage of mining practitioners, and current year investment on pollution abatement projects were effective at long-term temporal scale, while the other indicators acted at shortterm temporal scale. With the combination of long-term and shortterm temporal scales, the dynamic assessment of ecological risk for mining cities could be expressed on twodimension of temporal scale. It was found that Fuxin City got the highest ecological risk in current status, with the risk increasing most in Fushun City at the shortterm temporal scale as well as in Chaoyang City at the long-term temporal scale. The method adopted in this study might act as a significant guidance in dynamic controlling and integrative management of ecological risk for mining cities.
PENG Jian, TAO Jing-xian, LIU Yan-xu. Temporal characteristics of ecological risk assessment indicators in coal-mining city with the application of LVQ method.[J]. Chinese Journal of Applied Ecology.
/ Recommend
Add to citation manager EndNote|Ris|BibTeX
URL: https://www.cjae.net/EN/abstract/abstract11574.shtml
https://www.cjae.net/EN/Y2015/V26/I3/867