基于最小二乘支持向量机的农村土地利用空间优化配置方法及实例分析

A Method for Spatial Optimization Allocation of Rural Land Use Based on Least Squares Support Vector Machine and Its Case Study

因为农村各类用地数据具有样本小、非线性等特点,导致土地利用空间配置结果的适宜性较差,所以本文提出基于最小二乘支持向量机的农村土地利用空间优化配置方法。基于最小二乘支持向量机预测农村土地利用空间格局,得到各类用地面积数据,对各类用地进行满足经济效益与生态效益最大化的多目标函数的优化配置。实例结果表明,农村土地利用空间优化配置结果中各用地类型高度适宜区域的面积占比均超过75%,证实了设计方法的合理性。

Due to the small sample size and nonlinearity of various types of rural land use data,the suitability of land use spatial allocation results is poor.Therefore,a method for spatial optimization allocation of rural land use based on least squares support vector machine was proposed in this paper.Based on the least squares support vector machine to predict the spatial pattern of rural land use,we obtained data on various types of land use areas,and optimized the allocation of multi-objective functions that met the maximization of economic and ecological benefits for various types of lands.The results of case study indicated that the proportion of highly suitable areas for various types of lands exceeded 75%in spatial optimization allocation results of rural land use,which confirmed the rationality of the design method.