Ecosystem Health Evaluation of Yima Coal-Mining Area based on Fuzzy Synthetic Evaluation Method

Xiaoyan Tao, Jiulong Zhu

Abstract

Evaluation of ecosystem health can help people realize the situation and developing trend of the ecological system of the area. An evaluation index system of ecosystem health of coal-mining area based on Pressure- Status-Response model was constructed. Then evaluation model based on fuzzy synthetic evaluation method was established. Finally ecosystem health condition of Yima Coal-Mining Area situated at Henan Province during 2005 and 2013 was evaluated. Results show that ecosystem of Yima Coal-Mining Area belongs to critically healthy grade in 2005, 2006, 2008 and 2009 and belongs to relatively unhealthy grade during other years. There is a tendency of gradual deterioration in ecosystem of Yima Coal-Mining Area with the exception of 2008 and 2009. The study can provide scientific guidance for the formulation of resource and environment management decisions and sustainable development strategies of the mining area.

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Paper Citation


in Harvard Style

Tao X. and Zhu J. (2015). Ecosystem Health Evaluation of Yima Coal-Mining Area based on Fuzzy Synthetic Evaluation Method . In Proceedings of the Information Science and Management Engineering III - Volume 1: ISME, ISBN 978-989-758-163-2, pages 486-491. DOI: 10.5220/0006029104860491


in EndNote Style

TY - CONF
JO - Proceedings of the Information Science and Management Engineering III - Volume 1: ISME,
TI - Ecosystem Health Evaluation of Yima Coal-Mining Area based on Fuzzy Synthetic Evaluation Method
SN - 978-989-758-163-2
AU - Tao X.
AU - Zhu J.
PY - 2015
SP - 486
EP - 491
DO - 10.5220/0006029104860491


in Bibtex Style

@conference{isme15,
author={Xiaoyan Tao and Jiulong Zhu},
title={Ecosystem Health Evaluation of Yima Coal-Mining Area based on Fuzzy Synthetic Evaluation Method},
booktitle={Proceedings of the Information Science and Management Engineering III - Volume 1: ISME,},
year={2015},
pages={486-491},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006029104860491},
isbn={978-989-758-163-2},
}