摘要
目前城市布局优化方法没有分析交错带空间结构,以及功能与结构之间的关系,导致总体精度、Kappa系数和优化效率低。提出基于多源遥感数据的城市交错带约束布局优化方法,对采集的多源遥感数据进行几何校正、辐射定标处理,根据多源遥感数据选取并计算景观格局指数,分析交错带空间结构,以及功能与结构之间的关系。根据分析结果将用水目标、生态目标和经济目标作为优化方向,构建城市交错带约束布局优化模型,采用粒子群算法获得布局优化模型的最优解,实现城市交错带的布局优化。实验结果表明,所提方法的总体精度高、Kappa系数高、优化效率高。
Currently,urban layout optimization methods ignore the spatial structure of the crisscross zone and the relationship between function and structure,thus resulting in low overall accuracy,Kappa coefficient and optimization efficiency.Therefore,this paper puts forward a constrained layout optimization method of urban fringe based on multi-source remote sensing data.The collected multi-source remote sensing data were geometrically corrected and radiometrically calibrated.The landscape pattern index was selected and calculated by multi-source remote sensing data.The spatial structure of interlaced zone and the relationship between function and structure were analyzed.Based on the analysis results,water use objectives,ecological objectives and economic objectives were taken as optimization objects to construct the constrained layout optimization model of urban fringe.The optimal solution of the layout optimization model was obtained with the utilization of particle swarm optimization(PSO)algorithm,thus the layout optimization of urban fringe was achieved.The simulation results show that the method has high overall accuracy,kappa coefficient and optimization efficiency.
作者
陈莉
王晓燕
CHEN Li;WANG Xiao-yan(Ningxia University School of Civil And Hydraulic Engineering,Yinchuan Ningxia 750021,China)
出处
《计算机仿真》
北大核心
2021年第3期351-354,392,共5页
Computer Simulation
基金
宁夏高校科学研究项目(NGY2018043)
宁夏大学自然科学基金资助项目(ZR1118)。
关键词
多源遥感数据
景观格局指数
布局优化模型
粒子群算法
数据预处理
Multi-source remote sensing data
Landscape pattern index
Layout optimization model
Particle swarm algorithm
data preprocessing
