规划实施评估和重点区域调控是国土空间规划进入实施管理阶段后的重要需求。现有土地利用变化模拟多侧重单一路径下的格局预测，难以在统一条件下辨析历史惯性与规划目标导向的差异。为此，提出一种融合历史变化基线与规划目标导向的双路径土地利用变化模拟方法。基于 2019—2024 年土地利用、空间驱动与约束及 2035 年国土空间规划数据，采用马尔可夫链模型与矢量元胞自动机模型构建历史趋势驱动路径；以现状与规划目标的差额为数量约束，构建规划目标牵引路径；进而对双路径结果进行数量结构、空间配置和规划偏离对比与叠置诊断。以常州市武进区中心城区为研究区，结果表明：模型回测中，数量预测的 L1 精度为 0.98，空间模拟的总体精度、Kappa 系数和优值因子分别为 0.92、0.90 和 0.26；双路径差异主要集中于农用地、城镇住宅用地、工业仓储用地和商业服务业用地，并在外围发展区、既有开发区及工业连续带边缘集聚；双路径协调区、历史惯性偏离区、规划实施难点区和规划调整不稳定区分别占研究区的 48.21%、18.90%、27.12%和 5.77%。
Urban economic forecasting is crucial for the formulation of a macroeconomic development strategy for a region toward harmonious socio-economic and ecological progress. Cellular Automata (CA) enables fine-grained urban economic modeling, but its conventional discrete-state structure performs poorly when handling continuous economic variables like GDP density, and furthermore often lacks the ability to integrate with general economic growth patterns. These shortcomings ultimately compromise the simulation accuracy of urban economic dynamics.
Title: Formal and informal settlements and corresponding demographic patterns in Gaza Strip: deep learning approach to urban sustainability
Title: Optimizing urban three-dimensional landscapes in potential development areas to mitigate urban heat island effect under shared socioeconomic pathways
Title: CoCA: Spatial cooperative simulation and future prediction of “land-population-economy” in urban agglomerations
Title: A Framework for Exploring “Transfer-Out” Land Parcels for Urban Development Under the Ecological Control Line (ECL) Policy in China
Title: Temporal-VCA: Simulating urban land use change using coupled temporal data and vector cellular automata
Urbanization-induced land cover changes significantly impact ecological environments and socioeconomic growth. Vector-based cellular automata
Fine-grained regional economic forecasting for a megacity using vector-based cellular automata
Spatial cooperative simulation of land use-population-economy in the Greater Bay Area, China
UrbanComp