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平原与山地超大城市生态环境质量差异性演进OACHSSCD

Comparative evolution of ecological environment quality in plain and mountainous megacities:insights from the Chengdu-Chongqing urbanization process

中文摘要英文摘要

快速城市化显著改变了城市生态系统的结构与功能,揭示不同地貌类型超大城市生态环境质量的演变规律及驱动机制,对于优化城市空间治理具有重要意义.以典型山地城市重庆与平原城市成都为案例,基于 Landsat5/8、高程(DEM)、夜间灯光(NL)、交通网络(OSM)等多源时空数据,依托 GEE 云平台,综合运用遥感城市生态指数(RSUSEI)、景观格局指数(LM)、机器学习(ML)等方法,系统解析了双城生态环境质量的时空演变特征及其驱动机制.结果表明:(1)时序角度,源于复杂地形阻隔与生态建设,重庆总体表现出生境质量向好趋势,而成都源于地形的弱约束性及其派生的破碎化城市扩张模式,导致生境质量总体呈下降态势;(2)格局角度,重庆生态质量高值区由"条带状"向"片区状"扩展,生态质量整体提升趋势明显.成都生态质量高值区由"边缘带状"向"片区环状"演变且表现出萎缩态势,生态质量低值区则呈"放射楔状"扩张;(3)结构角度,重庆生境质量高值区的景观连通性与稳定性较强,而成都则表现出结构破碎、质量降低、生态廊道连续性下降态势;(4)机理角度,成都的驱动模式由自然-社会复合转向社会要素主导,重庆的自然因子则持续占优,表现出平原与山地城市生态驱动机制的明显分异.总体上,山地与平原城市在生态环境质量演变及驱动机制上表现出差异性规律,这为超大城市差异化生态修复与空间治理提供了重要理论与实践参考.

Rapid urbanization has profoundly altered the structure and function of urban ecosystems.Unveiling the evolutionary patterns and driving mechanisms of ecological environment quality in megacities with different geomorphic types is of great significance for optimizing urban spatial governance.This study selected Chongqing,a typical mountainous city,and Chengdu,a representative plain city,as case studies.Based on multi-source spatiotemporal data—including Landsat 5/8 imagery,Digital Elevation Model(DEM),Nighttime Light(NL),and OpenStreetMap(OSM)traffic networks—and leveraging the Google Earth Engine(GEE)cloud platform,we comprehensively applied the Remote Sensing Urban Ecological Index(RSUSEI),Landscape Pattern Index(LPI),and machine learning(ML)methods to systematically analyze the spatiotemporal evolution characteristics and driving mechanisms of ecological environmental quality in both cities.By integrating these datasets with robust computational approaches,the study provided a detailed,fine-scale,and multi-dimensional understanding of urban ecological dynamics.The results showed that:(1)From a temporal perspective,due to complex topographic barriers and ecological construction,Chongqing generally demonstrated an improving trend in habitat quality,while Chengdu,which is more weakly constrained by terrain and characterized by a rapidly expanding and fragmented urbanization model,exhibited an overall decline in habitat quality.(2)From a spatial pattern perspective,high-value ecological quality zones in Chongqing expanded from a"strip-like"to a"patch-like"distribution,indicating a gradual improvement and spatial stabilization of its overall ecological conditions.In contrast,Chengdu's high-value ecological zones evolved from"peripheral strip-like"to"ring-shaped patches,"yet showed a shrinking trend,while its low-value ecological zones expanded in a"radial wedge-shaped"pattern,suggesting an increasingly uneven spatial distribution of ecological quality.(3)From a structural perspective,high-value habitat areas in Chongqing maintained strong landscape connectivity and stability,whereas Chengdu exhibited increasing fragmentation,declining ecological quality,and weakened continuity of ecological corridors.(4)From a mechanistic perspective,Chengdu's driving mode shifted from a nature-society composite to one dominated by social factors,while natural factors continued to play the dominant role in Chongqing,reflecting the differing resilience and adaptability of their ecological systems.These findings reveal a distinct divergence in ecological driving mechanisms between plain and mountainous cities.In conclusion,significant differences were observed between mountainous and plain megacities in terms of ecological environmental quality evolution and driving mechanisms.This study provides an important reference for optimizing differentiated ecological patterns and formulating spatial governance strategies in megacities,offering deeper insights into sustainable urban development and contributing to the scientific basis for building resilient,ecologically harmonious,and livable urban environments.

张珂宁;汪洋;刘几淘;聂雪梅;夏雪;李培;李雨果;蔡骏

重庆师范大学地理与旅游学院,重庆 401331||重庆师范大学地理信息系统应用研究重庆市高校重点实验室,重庆 401331重庆师范大学地理与旅游学院,重庆 401331||重庆师范大学地理信息系统应用研究重庆市高校重点实验室,重庆 401331||重庆师范大学山区生态系统碳循环与碳调控重庆市重点实验室,重庆 401331重庆市璧山区土地整治储备中心,重庆 404100重庆师范大学地理与旅游学院,重庆 401331||重庆师范大学地理信息系统应用研究重庆市高校重点实验室,重庆 401331重庆师范大学地理与旅游学院,重庆 401331||重庆师范大学地理信息系统应用研究重庆市高校重点实验室,重庆 401331重庆师范大学地理与旅游学院,重庆 401331||重庆师范大学地理信息系统应用研究重庆市高校重点实验室,重庆 401331重庆师范大学地理与旅游学院,重庆 401331||重庆师范大学地理信息系统应用研究重庆市高校重点实验室,重庆 401331重庆师范大学地理与旅游学院,重庆 401331||重庆师范大学地理信息系统应用研究重庆市高校重点实验室,重庆 401331

城市生态环境质量山地与平原超大城市快速城市化成都与重庆机器学习

urban ecological qualitymountainous and plain megacitiesrapid urbanizationChengdu and Chongqingmachine leanring

《生态学报》 2026 (16)

8591-8608,18

重庆市自然科学基金(CSTB2023NSCQ-MSX0643,CSTB2022NSCQ-MSX1535)国家自然科学基金(52478042)

10.20103/j.stxb.202507081775

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