摘要
由于耕地空间布局不仅需要考虑土地质量和生产潜力,还需要综合考虑环境保护、水文特征等因素影响,增加了空间布局规划的复杂性。为此,提出一种时空数据随机性影响下耕地空间布局规划方法。根据栅格空间数据和线性加权方法构建耕地布局规划模型,通过耕地质量自相关性计算耕地各指标数值,结合最优组合赋权法确定评价体系权重,利用增量自相关分析,归一化处理耕地指标数值,基于物元矩阵计算耕地地质环境的经典域与节域,获取耕地地质环境评价的综合关联程度,实现耕地空间布局规划。实验结果表明,所提方法时空数据随机性特征识别能力更强,耕地分类精度为94%,耕地空间布局规划效果好,空间集约性高,较小的耕地区域占地面积的NNI指数高达0.634。
Due to the fact that the spatial layout of cultivated land not only needs to consider land quality and production potential,but also needs to comprehensively consider factors such as environmental protection and hydrological characteristics,it increases the complexity of spatial layout planning.As a result,this paper proposed a method for planning the spatial layout of cultivated land under the influence of randomicity of spatiotemporal data.Firstly,we constructed a layout planning model by using raster spatial data and linear weighting method.Then,we calculated the values of various indicators of cultivated land through the autocorrelation of cultivated land quality,and determined the weight of the evaluation system by combining the optimal combination weighting approach.Next,we used incremental autocorrelation analysis to normalize the cultivated land indicators.Based on the matter element matrix,we calculated the classical domain and segment domain of the geological environment of cultivated land,thus obtaining the comprehensive correlation degree of the geological environment evaluation.Finally,we completed the spatial layout planning of cultivated land.The experimental results show that the proposed method has stronger identification ability for the randomness characteristics of spatiotemporal data,as well as 94%classification accuracy of cultivated land.In addition,the effect of spatial layout planning is good,and the spatial intensive nature is high.The NNI index of smaller cultivated land area is as high as 0.634.
作者
杨锋
王秀丽
周雨石
高松峰
YANG Feng;WANG Xiu-li;ZHOU Yu-shi;GAO Song-feng(School of Surveying and Urban Spatial Information,Henan University of Urban Construction,Pingdingshan Henan 467036,China;College of Resources and Environment,Henan Agricultural University,Zhengzhou Henan 450002,China)
出处
《计算机仿真》
2024年第5期325-328,371,共5页
Computer Simulation
关键词
时空数据模型
线性加权方式
自相关性分析法
物元矩阵
综合关联程度
Spatiotemporal data model
Linear weighting method
Autocorrelation analysis
Matter element matrix
Comprehensive correlation degree
