首页|顾及存量更新与增量发展不均速率的城市空间增长模拟研究

顾及存量更新与增量发展不均速率的城市空间增长模拟研究

扫码查看
我国大多数城市正处于从增量规划向存量规划转型的过渡阶段,存量规划的实施仍需以增量规划为基础,二者之间相辅相成、协同发展.值此转型阶段,新的国土空间规划体系强调了规划的层级传导,从宏观到微观,渐近式地引导和约束着城市的发展方向.本文依据存量更新与增量发展的时空增减更替变化规律,分别进行参数控制以实现二者指标的调整和面积分配,将其纳入到多层次矢量元胞自动机(Vector Cellular Automata,VCA)模型中,以此实现顾及"存量更新-增量发展"的城市空间增长多层次矢量CA模拟,并将其应用于存量规划背景下的江阴市2027年多情景用地增长预测与分析.研究结论如下:①多层次VCA通过不同层次间驱动力自上而下差异性分解与自下而上协同性传递的方式,既完成了上层管控的指标落实,又实现了用地模拟的精细化控制;②多层次VCA给予不同片区差异化的速度参数,充分顾及到了驱动因子与用地分布的空间异质性,其整体FoM达到了24.6%,精度相比单层次VCA高2.5%;局部细节特征上,多层次VCA对不同用地类型的错分情况以及对水域等禁建区的侵占情况要比单层次的模拟结果少,且对条状地块的模拟效果更好;③在"底线管控-分层管控-指标管控"层次约束下,随着存量更新速度的提高,不同情景下预测的新增建设用地的扩张情况均保持在规划控制的范围之内,且集中在澄西、澄南和澄东南3个片区,这与规划划定的增长边界和用地布局结构相吻合;④不同情景下存量用地更新方向以工业用地为主导,乡村建设用地次之,情景二中(d)和(e)的模拟结果中,工业更新趋于饱和,整体实现均衡增长,可作为未来江阴市用地格局发展的主要参考.
Study on Urban Spatial Growth Simulation Considering Uneven Rates of Stock Renewal and Incremental Development
In China,the majority of cities are currently transitioning from incremental planning to inventory planning. The implementation of inventory planning still relies on incremental planning as its foundation,with the two approaches complementing each other and developing in coordination. During this transition,the new national spatial planning system emphasizes the hierarchical transmission of planning,guiding and constraining urban development progressively from macro to micro levels. This study is based on a multi-level Vector Cellular Automata (VCA) model. We use land use data from Jiangyin City in 2012 as the foundation to simulate and analyze land use changes in 2017,and then verify the accuracy of the VCA model. Subsequently,adhering to the spatiotemporal patterns of stock renewal and incremental development,parameters are adjusted and area allocations are made separately to integrate these two indicators. They are then incorporated into the multi-level VCA model. This approach allows for a multi-level simulation of urban spatial growth,considering both stock renewal and incremental development. Then,this approach is applied to predict and analyze multiple scenarios of land use growth in Jiangyin City in 2027 within the context of stock planning. The conclusions of the study are as follows:① The multi-level VCA decomposes differential driving forces from top to bottom and transmits them collaboratively from bottom to top,achieving both the implementation of upper-level control indicators and fine-grained control of land use simulation. ② The multi-level VCA assigns differentiated speed parameters to different regions,fully considering the spatial heterogeneity of driving factors and land distribution. The overall Figure of Merit (FoM) reaches 24.6%,which is 2.5% higher than that of the single-level VCA. At the local detail level,the multi-level VCA exhibits fewer misclassifications of different land use types and less encroachment on prohibited areas such as water bodies compared to single-level simulations,with better simulation results for linear land parcels. ③ Under the constraints of "baseline control-layered control-indicator control," with the increase in stock renewal speed,the expansion of newly predicted construction land in different scenarios remains within the range of planned control. The scale of expansion for newly predicted construction land is reduced,and it is concentrated in the West,South,and Southeast of Jiangyin city. This transition aligns with the growth boundaries and land layout structure designated in the master planning outline. In different scenarios,stock land renewal is dominated by industrial land,followed by rural construction land. ④ In scenarios (d) and (e),industrial renewal tends toward saturation,achieving overall balanced growth,serving as a key reference for future land use pattern development in Jiangyin City.

stock planningland allocationmulti-level vector cellular automatonurban spatial growth simulationmulti-scenario prediction

朱杰、朱梦瑶、宋书颖、丁远、陈丽、朱学明、孙毅中

展开 >

南京林业大学土木工程学院,南京 210037

南京师范大学虚拟地理环境教育部重点实验室,南京 210023

江苏省地理信息资源开发与利用协同创新中心,南京 210023

河海大学地理与遥感学院,南京 210098

常州市新北自然资源和规划技术保障中心,常州 213022

展开 >

存量规划 用地分配 多层次矢量CA模型 城市空间增长模拟 多情景预测

自然资源部国土卫星遥感应用重点实验室开放基金项目自然资源部国土卫星遥感应用重点实验室开放基金项目国家自然科学基金项目国家自然科学基金项目江苏省海洋科技创新项目江苏省自然资源科技项目江苏省自然资源科技项目

KLSMNR-K202210KLSMNR-G2023114237140842101430JSZRHYKJ20230220220292023005

2024

地球信息科学学报
中国科学院地理科学与资源研究所

地球信息科学学报

CSTPCD北大核心
影响因子:1.004
ISSN:1560-8999
年,卷(期):2024.26(8)