School of Geosciences, University of Aberdeen, King's College, Aberdeen, AB24 3UE, UK.
J Environ Manage. 2024 Jul;364:121477. doi: 10.1016/j.jenvman.2024.121477. Epub 2024 Jun 14.
The rapid expansion of cities in developing countries has led to many environmental problems, and the mechanism of urban expansion (UE), as a more complex human-land coupled system, has always been a difficult issue to research. This paper introduces a new approach by establishing an analytical framework for spatiotemporal pattern mining, exemplified by studying the urban growth of Changsha City from 1990 to 2019. Initially, an emerging hotspot analysis model (EHA) is employed to examine the spatiotemporal changes of urban growth on a macro scale. Mathematical models are subsequently utilized to quantify the correlations between urban expansion and selected infrastructural and topographical factors. Building on these findings, the paper constructs mathematical models to further quantify the spatiotemporal evolution of various urban sprawl patterns across different regions, aiming to elucidate and quantify the significant variations in UE over time and space. The study reveals that, as an emerging city, Changsha's hotspots of urban expansion prior to 2003 were primarily concentrated in the city centre, subsequently spreading to the periphery. The radial influence of metro stations on UE is notably less than that of railway stations-approximately 3 km versus 8 km-and the impact diminishes rapidly before gradually tapering off. Moreover, UE in Changsha predominantly occurs on slopes with gradients ranging from 1.1° to 7.5°, and significant development capacity is observed at elevations between 36.1 m and 78.3 m above sea level, with a tendency for urban sprawl to migrate to lower elevations. The paper also identifies three distinct patterns of urban expansion across different regions: an initial slow-growth phase, followed by a rapid escalation to a peak, and subsequently a swift decline to near stagnation. Additionally, it highlights a significant correlation between the proportion of built-up areas at the micro-regional scale and the stages of UE. This correlation was quantitatively analysed by constructing a logistic function, which demonstrated a robust fit that effectively captures spatiotemporal heterogeneity in the dynamics of UE. These insights enhance the selection of drivers in urban simulation models and deepen the understanding of the complex dynamics that influence urban development.
发展中国家城市的快速扩张导致了许多环境问题，而城市扩展（UE）机制作为一个更加复杂的人地耦合系统，一直是一个难以研究的问题。本文通过建立时空模式挖掘分析框架，以研究 1990 年至 2019 年长沙市的城市增长为例，引入了一种新的方法。首先，采用新兴热点分析模型（EHA）来考察城市增长的时空变化。然后，利用数学模型量化城市扩展与选定基础设施和地形因素之间的相关性。在此基础上，构建数学模型进一步量化不同区域不同城市扩展模式的时空演变，旨在阐明和量化 UE 随时间和空间的显著变化。研究表明，作为一个新兴城市，长沙的城市扩展热点在 2003 年之前主要集中在市中心，随后扩展到外围。地铁站对 UE 的径向影响明显小于火车站-约 3 公里对 8 公里-而且影响在迅速减弱之前迅速减弱。此外，长沙的 UE 主要发生在坡度为 1.1°至 7.5°的斜坡上，在海拔 36.1 米至 78.3 米之间的高程上观察到显著的发展能力，城市扩展有向低海拔迁移的趋势。该论文还在不同区域确定了三种不同的城市扩展模式：初始缓慢增长阶段，随后迅速上升到峰值，然后迅速下降到接近停滞状态。此外，还发现微观区域尺度上建成区的比例与 UE 的阶段之间存在显著的相关性。通过构建逻辑函数对这种相关性进行了定量分析，该函数拟合效果良好，有效地捕捉了 UE 动态中的时空异质性。这些见解增强了城市模拟模型中驱动因素的选择，并加深了对影响城市发展的复杂动态的理解。
