基于BRT模型的合肥中心城区蓝绿空间时空演变及驱动因素研究
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国家自然科学基金重点项目“低影响开发下的城市绿地规划理论与方法”(编号:51838003);东南大学“至善青年学者”支持计划资助项目“城市建成区蓝绿空间布局对碳汇效益的影响机制研究”(编号:2242023R40002)


Spatiotemporal Dynamics and Driving Factors of Urban Blue-Green Space in Central Hefei Based on BRT Model
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    摘要:

    蓝绿空间是城市用地重要组成部分,探究高速城市化进程下蓝绿空间的时空演变及驱动因素,有助于揭示其演化规律,为相关研究及政策制定提供基础。以合肥为例,基于面积变化强度、土地转移矩阵、多阶邻接指数研究中心城区蓝绿空间的时空变化;采用增强回归树模型探讨影响城市蓝绿空间扩张的驱动因子。结果表明:(1)2000?-?2020年,合肥中心城区蓝绿空间总体规模增长了14.8%,呈现稳步增加的阶段性特征。(2)研究时段内合肥中心城区蓝绿空间扩张模式均以边缘式为主、邻接式为辅;新增蓝绿斑块沿大型自然蓝绿斑块集聚,蓝绿空间扩张由城市边缘转向内部。(3)自然要素因子对蓝绿空间扩张的影响(80.8%)大于社会经济因子(19.2%),其中高程(32.1%)、坡度(26.9%)、坡向(21.8%)、人口密度(13%)、第三产业增加值(6.2%)是主要驱动因子。研究探明了近20年来合肥中心城区蓝绿空间的时空演变特征及驱动因子,可为未来城市蓝绿空间规划管理及可持续发展提供支撑。

    Abstract:

    The blue-green space in Chinese cities is important for urban land use. Exploring the spatiotemporal dynamics and driving factors of blue-green spaces under rapid urbanization processes contributes to unveiling the evolutionary patterns of urban blue-green spaces, which provides a fundamental basis for related research and policy formulation. In this study, remote sensing imagery was used to calculate the extent of blue-green spaces from 2000 to 2020, and we analyzed the evolution using the intensity of area change, a land transfer matrix, the multi-order adjacency index, and a boosted regression tree model. This study revealed the spatiotemporal dynamics and driving factors of blue-green spaces in the central area of Hefei from 2000 to 2020, particularly: (1) Between 2000 and 2020, there was a 14.8% net increase in the total area of blue-green spaces in Hefei’s central area. (2) Blue-green spaces primarily showed fringe-type expansion and proximity-type expansion. Spatially, new blue-green patches tended to cluster around large pre-existing natural blue-green patches. Furthermore, the expansion of blue-green spaces shifted from the urban periphery to the urban interior. (3) Natural factors exerted a greater influence (80.8%) on the expansion of blue-green spaces than did socioeconomic factors (19.2%). DEM (32.1%), slope (26.9%), aspect (21.8%), population density (PD) (13%), and value-added by the tertiary industry (VATI) (6.2%) were identified as the primary driving factors. The results contribute to understanding changes in urban blue-green spaces and the driving factors behind these changes, thereby providing support for future planning, protection, and sustainable development of urban blue-green spaces.

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  • 在线发布日期: 2024-01-15
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