标题：Urban Ecological Security Simulation and Prediction Using an Improved Cellular Automata (CA) Approach-A Case Study for the City of Wuhan in China

作者：Gao, Y (Gao, Yuan); Zhang, CR (Zhang, Chuanrong); He, QS (He, Qingsong); Liu, YL (Liu, Yaolin)

来源出版物：INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 卷：14期：6文献编号：643 DOI：10.3390/ijerph14060643 出版年：JUN 2017

摘要：Ecological security is an important research topic, especially urban ecological security. As highly populated eco-systems, cities always have more fragile ecological environments. However, most of the research on urban ecological security in literature has focused on evaluating current or past status of the ecological environment. Very little literature has carried out simulation or prediction of future ecological security. In addition, there is even less literature exploring the urban ecological environment at a fine scale. To fill-in the literature gap, in this study we simulated and predicted urban ecological security at a fine scale (district level) using an improved Cellular Automata (CA) approach. First we used the pressure-state-response (PSR) method based on grid-scale data to evaluate urban ecological security. Then, based on the evaluation results, we imported the geographically weighted regression (GWR) concept into the CA model to simulate and predict urban ecological security. We applied the improved CA approach in a case study-simulating and predicting urban ecological security for the city of Wuhan in Central China. By comparing the simulated ecological security values from 2010 using the improved CA model to the actual ecological security values of 2010, we got a relatively high value of the kappa coefficient, which indicates that this CA model can simulate or predict well future development of ecological security in Wuhan. Based on the prediction results for 2020, we made some policy recommendations for each district in Wuhan.

入藏号：WOS:000404107600091

文献类型：Article

语种：English

作者关键词： urban ecological security; simulation and prediction; pressure-state-response (PSR); cellular automata (CA); geographically weighted regression (GWA)

扩展关键词： GEOGRAPHICALLY WEIGHTED REGRESSION; SOIL ORGANIC-MATTER; GROWTH PATTERNS; SPATIAL-DISTRIBUTION; ACCURACY ASSESSMENT; CITIES; REGION; FRAMEWORK; DYNAMICS; FUZZY

通讯作者地址：He, QS; Liu, YL (reprint author), Wuhan Univ, Sch Resource & Environm Sci, 129 Luoyu Rd, Wuhan 430079, Peoples R China.

Liu, YL (reprint author), Wuhan Univ, Key Lab Geog Informat Syst, Minist Educ, 129 Luoyu Rd, Wuhan 430079, Peoples R China.

Liu, YL (reprint author), Collaborat Innovat Ctr Geospatial Informat Techno, Wuhan 430079, Peoples R China.

电子邮件地址：2015102050045@whu.edu.cn; cindy.zhang@uconn.edu; baihualin2013@163.com; liuyaolin1999@126.com

地址：

[Gao, Yuan; He, Qingsong; Liu, Yaolin] Wuhan Univ, Sch Resource & Environm Sci, 129 Luoyu Rd, Wuhan 430079, Peoples R China.

[Zhang, Chuanrong] Univ Connecticut, Dept Geog, Storrs, CT 06269 USA.

[Zhang, Chuanrong] Univ Connecticut, Ctr Environm Sci & Engn, Storrs, CT 06269 USA.

[Liu, Yaolin] Wuhan Univ, Key Lab Geog Informat Syst, Minist Educ, 129 Luoyu Rd, Wuhan 430079, Peoples R China.

[Liu, Yaolin] Collaborat Innovat Ctr Geospatial Informat Techno, Wuhan 430079, Peoples R China.

研究方向：Environmental Sciences & Ecology; Public, Environmental & Occupational Health

ISSN：1660-4601

影响因子：2.101