城市景观格局演变驱动因子及其特征研究综述
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国家重点研发计划项目(2022YFF1301101);国家自然科学基金项目(42330707)


A review on the driving factors and their characteristics in urban landscape pattern changes
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National Key Research and Development Program, No. 2022YFF1301101; the National Natural Science Foundation of China (42330707)

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    摘要:

    识别城市景观格局演变的驱动因子,是更好地理解城市景观动态格局、过程及其影响的关键,对于城市景观格局优化与预测、城市空间规划和政策制定等均至关重要。系统梳理了城市景观格局演变的驱动因子;归纳了城市景观格局变化驱动因子定量分析模型,包括基于经验的统计模型和基于过程的动态模型;阐明了全球、国家、城市群和城市等不同尺度下城市景观格局演变驱动因子的时空和尺度异质性特征,以及不同驱动因子的直接和间接效应。提出了城市景观格局演变驱动因子的未来研究方向。

    Abstract:

    Identifying the driving factors of urban landscape pattern changes is key to better understanding the dynamic patterns, processes and influences of urban landscapes, which is crucial for optimizing and predicting of urban landscape patterns and for formulation of urban spatial planning and policies. We systematically reviewed the drivers of changes in urban landscape patterns, generally divided into human activities and natural factors. Human activities, especially population change, economic development, and policies, are the primary driving forces of urban landscape pattern changes, particularly over shorter time scales. Natural factors, such as topography, climate, and water resources, provide the material foundation and environmental conditions shaping urban landscape patterns, primarily determining the spatial pattern of cities over long periods. In addition, we summarized the quantitative analysis models of the drivers of urban landscape pattern changes, including empirically based statistical models and process-based dynamic models. Statistical models dominate in the quantitative analysis of driving factors of urban landscape changes and are classified according to their correlation relationships into linear, non-linear relationship, spatial relationship and causality models. Process-based dynamic models, including the system dynamics model, cellular automata model, and multi-agent system model, effectively simulate the operation of systems by deeply understanding various driving forces and analyzing interactions among the internal components of the system. Furthermore, we clarified the spatio-temporal and scaling heterogeneity patterns of driving factors of urban landscape pattern changes at different scales, including global, national, agglomeration and city levels, as well as the direct and indirect effects of different driving factors. The degree and direction of influence of drivers of urban landscape pattern changes vary regularly over time, differ between regions, and change with the spatial scale of the study unit. Moreover, these drivers are not isolated from each other, and there are complex interactions between them. Changes in these drivers can directly affect the spatial configuration of urban landscapes, and the interactions between different factors can also have indirect effects. Finally, we identified future research directions for the study of driving factors of urban landscape pattern changes, including temporal attribution analysis of urban landscape pattern changes, spatial effects and feedback mechanisms of urban social-ecological landscape patterns and their driving factors, and cross-scale interaction analysis of driving factors influencing urban landscape pattern changes.

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杨筠慧,史文娇,周伟奇,王江浩,钱雨果,王伟民.城市景观格局演变驱动因子及其特征研究综述.生态学报,2024,44(22):10486~10498

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