College of Marine Sciences, Shanghai Ocean University, Shanghai, 201306, China.
The Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources (Ministry of Education), Shanghai Ocean University, Shanghai, 201306, China.
Environ Monit Assess. 2016 Sep;188(9):540. doi: 10.1007/s10661-016-5558-y. Epub 2016 Aug 31.
The world's coastal regions are experiencing rapid urbanization coupled with increased risk of ecological damage and storm surge related to global climate and sea level rising. This urban development issue is particularly important in China, where many emerging coastal cities are being developed. Lingang New City, southeast of Shanghai, is an excellent example of a coastal city that is increasingly vulnerable to environmental change. Sustainable urban development requires planning that classifies and allocates coastal lands using objective procedures that incorporate changing environmental conditions. In this paper, we applied cellular automata (CA) modeling based on self-adaptive genetic algorithm (SAGA) to predict future scenarios and explore sustainable urban development options for Lingang. The CA model was calibrated using the 2005 initial status, 2015 final status, and a set of spatial variables. We implemented specific ecological and environmental conditions as spatial constraints for the model and predicted four 2030 scenarios: (a) an urban planning-oriented Plan Scenario; (b) an ecosystem protection-oriented Eco Scenario; (c) a storm surge-affected Storm Scenario; and (d) a scenario incorporating both ecosystem protection and the effects of storm surge, called the Ecostorm Scenario. The Plan Scenario has been taken as the baseline, with the Lingang urban area increasing from 45.8 km(2) in 2015 to 66.8 km(2) in 2030, accounting for 23.9 % of the entire study area. The simulated urban land size of the Plan Scenario in 2030 was taken as the target to accommodate the projected population increase in this city, which was then applied in the remaining three development scenarios. We used CA modeling to reallocate the urban cells to other unconstrained areas in response to changing spatial constraints. Our predictions should be helpful not only in assessing and adjusting the urban planning schemes for Lingang but also for evaluating urban planning in coastal cities elsewhere.
世界沿海地区正经历着快速的城市化进程,同时伴随着全球气候变化和海平面上升带来的生态破坏和风暴潮风险增加。这个城市发展问题在中国尤为重要,因为中国有许多新兴的沿海城市正在发展。上海东南的临港新城区就是一个受环境变化影响日益严重的沿海城市的典型例子。可持续城市发展需要规划,通过使用客观程序对沿海土地进行分类和分配,这些程序应纳入不断变化的环境条件。在本文中,我们应用基于自适应遗传算法 (SAGA) 的元胞自动机 (CA) 模型来预测未来情景,并探索临港的可持续城市发展选择。CA 模型使用 2005 年初始状态、2015 年最终状态和一组空间变量进行校准。我们将特定的生态和环境条件实施为模型的空间约束,并预测了 2030 年的四个情景:(a) 以城市规划为导向的规划情景;(b) 以生态系统保护为导向的生态情景;(c) 受风暴潮影响的风暴情景;以及 (d) 纳入生态系统保护和风暴潮影响的情景,称为生态风暴情景。规划情景被作为基准,临港城区面积从 2015 年的 45.8 平方公里增加到 2030 年的 66.8 平方公里,占整个研究区的 23.9%。规划情景 2030 年模拟的城市土地规模被用作容纳该城市预计人口增长的目标,然后将其应用于其余三个发展情景。我们使用 CA 模型来重新分配城市单元到其他不受约束的区域,以响应不断变化的空间约束。我们的预测不仅有助于评估和调整临港的城市规划方案,也有助于评估其他沿海城市的城市规划。