Gao Yuan, Zhang Chuanrong, He Qingsong, Liu Yaolin
School of Resource and Environmental Science, Wuhan University, 129 Luoyu Road, Wuhan 430079, China.
Department of Geography and Center for Environmental Sciences and Engineering, University of Connecticut, Storrs, CT 06269-4148, USA.
Int J Environ Res Public Health. 2017 Jun 15;14(6):643. doi: 10.3390/ijerph14060643.
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.
生态安全是一个重要的研究课题，尤其是城市生态安全。作为人口密集的生态系统，城市的生态环境往往更为脆弱。然而，文献中关于城市生态安全的大多数研究都集中在评估生态环境的当前或过去状况。很少有文献对未来生态安全进行模拟或预测。此外，探索精细尺度下城市生态环境的文献更是少之又少。为了填补这一文献空白，在本研究中，我们使用改进的细胞自动机（CA）方法在精细尺度（区级）上模拟和预测了城市生态安全。首先，我们基于网格尺度数据，采用压力-状态-响应（PSR）方法评估城市生态安全。然后，根据评估结果，我们将地理加权回归（GWR）概念引入CA模型，以模拟和预测城市生态安全。我们将改进的CA方法应用于一个案例研究——模拟和预测中国中部武汉市的城市生态安全。通过将使用改进的CA模型模拟的2010年生态安全值与2010年的实际生态安全值进行比较，我们得到了相对较高的卡帕系数值，这表明该CA模型能够较好地模拟或预测武汉市生态安全的未来发展。基于2020年的预测结果，我们为武汉市的每个区提出了一些政策建议。
