基于遥感图像的建筑群绿地空间布局优化仿真

Optimization Simulation of Green Space Layout in Building Clusters Based on Remote Sensing Images

在城市建筑群绿地空间开展布局优化时,由于提取的城市建筑群遥感信息数据质量较差,导致对绿地空间布局优化效果降低,因此提出改进遗传算法下城市建筑群绿地空间布局优化方法。采用图像增强方法,将采集的城市建筑群遥感数字图像增强处理,提升遥感图像信息数据质量;通过对图像的边缘展开检测,获取目标建筑群空间特征分布,并制定空间绿地布局优化目标函数,构建用于建筑群绿地空间布局优化目标模型;通过改进遗传算法对模型求解,确定城市建筑群绿地空间布局优化最佳优化系数,完成绿地空间布局优化。实验结果表明,所提方法对城市建筑群绿地空间布局优化时,优化效果好。

When optimizing the layout of green space in urban building clusters,due to the poor quality of extrac-ted remote sensing information data,the optimization effect of green space layout is reduced.Therefore,an improved genetic algorithm based optimization method for green space layout in urban building clusters is proposed.Firstly,we used the enhancement methods to enhance the collected remote sensing digital images of urban buildings,thus impro-ving the quality of information data.After detecting the edge of image,we obtained the spatial feature distribution of the target buildings,thus setting up corresponding objective functions for optimizing the spatial green space layout.Moreover,we constructed a model for optimizing the green space layout of buildings.Furthermore,we used the im-proved genetic algorithm to solve the model,thus determining the optimal coefficient.Finally,we achieved the green space layout optimization.Experimental results show that the proposed method has a good optimization effect on the spatial layout of green space in urban buildings.