College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China; College of Surveying & Geo-Informatics and the State Key Laboratory of Disaster Reduction in Civil Engineering, Tongji University, Shanghai 200092, China.
College of Surveying & Geo-Informatics and the State Key Laboratory of Disaster Reduction in Civil Engineering, Tongji University, Shanghai 200092, China; College of Architecture & Urban Planning, Tongji University, Shanghai 200092, China.
Sci Total Environ. 2020 Apr 10;712:136509. doi: 10.1016/j.scitotenv.2020.136509. Epub 2020 Jan 7.
Driven by increasing urban demand, spatially-varying urban expansion has led to significant ecosystem degradation in China and elsewhere. Spatial nonstationarity affects the relationship between urban expansion and ecosystem service value (ESV) loss, but its significance has been under-emphasized. To study the spatially-heterogeneous ESV loss, we integrated cellular automata (CA) with geographically weighted regression (GWR) in a model that considers the relationships between urban expansion and its driving factors. We used ten GWR bandwidths to construct the CA models for reproducing rapid urban expansion at Chongqing from 2005 to 2010. We then used the CA model with the best bandwidth to predict future urban scenarios out to 2030. Our modeling shows that CA is strongly sensitive to bandwidth, and that the overall accuracy and Figure-of-Merit are maximized with a ~2 km bandwidth (about 150 samples). We examined ESV losses in eleven ecosystem classes and found that climate regulation and water flow regulation are the dominant drivers of ESV loss. From 2010 to 2030, Chongqing's urban area will increase by about 87%, resulting in substantial encroachment on agricultural land, dryland and shrubs, causing significant ESV losses of about 38%. Our results constitute an early warning of ecosystem degradation caused by massive urban development. This study improves our understanding of spatially-varying urban expansion and related ESV losses in rapidly developing areas and should help improve urban planning regulation and regional policy for sustainable development to maintain environmentally-friendly cities.
受城市需求增长的推动，空间异质的城市扩展导致了中国和其他地区生态系统的严重退化。空间非平稳性影响了城市扩展与生态系统服务价值（ESV）损失之间的关系，但这种影响的重要性被低估了。为了研究空间异质的 ESV 损失，我们将元胞自动机（CA）与地理加权回归（GWR）集成在一个模型中，该模型考虑了城市扩展及其驱动因素之间的关系。我们使用了十个 GWR 带宽来构建考虑重庆 2005 年至 2010 年快速城市扩展的 CA 模型。然后，我们使用具有最佳带宽的 CA 模型来预测 2030 年之前的未来城市情景。我们的建模表明，CA 对带宽非常敏感，并且在带宽约为 2km（约 150 个样本）时，整体准确性和测度值达到最大值。我们检查了十一种生态系统类别的 ESV 损失，发现气候调节和水流调节是 ESV 损失的主要驱动因素。从 2010 年到 2030 年，重庆市的城区面积将增加约 87%，这将大量侵占农业用地、旱地和灌木林，导致约 38%的 ESV 损失。我们的研究结果构成了对大规模城市发展导致的生态系统退化的早期预警。这项研究提高了我们对快速发展地区空间异质城市扩展及相关 ESV 损失的认识，应该有助于改善城市规划法规和区域可持续发展政策，以维持环境友好型城市。
