基于成土环境地理邻域分析的历史土壤图训练样本筛选  

Screening of Training Samples Based on Environmental Covariate Geospatial Neighborhood Analysis of Historical Soil Maps

作　　者：高鸿 朱娟 王良杰 赵玉国[1,2] 张甘霖 GAO Hong;ZHU Juan;WANG Liangjie;ZHAO Yuguo;ZHANG Ganlin(l State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China;University of Chinese Academy of Sciences, Beijing 100049, China;College of Territorial Resources and Tourism, Anhui Normal University, Wuhu, Ahhui 241002, China;Anhui Bureau of Surveying andMapping, Hefei 230031, China;College of Forest, Nanjing Forestry University, Nanjing 210037, China)

机构地区：[1]土壤与农业可持续发展国家重点实验室(中国科学院南京土壤研究所),南京210008 [2]中国科学院大学,北京100049 [3]安徽师范大学国土资源与旅游学院,安徽芜湖241002 [4]安徽省测绘局,合肥230031 [5]南京林业大学林学院,南京210037

出　　处：《土壤学报》2018年第3期585-594,共10页Acta Pedologica Sinica

基　　金：国家自然科学基金项目(41771251;41601209);国家重点研发计划项目(2017YFC0803807)资助~~

摘　　要：基于历史土壤图的知识挖掘和历史图更新对土壤资源调查、管理和利用有着重要的现实意义,而从历史土壤图中筛选代表性训练样本是进行知识挖掘和历史土壤图更新的关键步骤。以安徽省旌德县为研究区,提出一种新的土壤图训练样本筛选方法,包括样本数量确定和样本位置筛选。研究结果表明,面积分段线性缩放法确定的样本数量解决了已有研究未考虑同一类型多个图斑单元间样本数量分配的问题;采用邻域分析方法确定样本位置,当图斑位于地势平缓的区域时,基于高程因子和坡度因子确定的样本空间分布差异较小,而当图斑位于山区时,基于坡度因子确定的样本处于地形变化稳定的位置,全局代表性更高。通过与已有研究中环境因子直方图方法筛选样本进行对比,邻域分析方法确定的样本具有更高的差异比例和标准差,样本信息量更大。基于坡度因子采用邻域分析方法筛选出的图斑样本较高程因子样本拥有更高的全局空间代表性,邻域分析方法筛选的样本较相关研究中环境因子直方图方法筛选的样本拥有更高的信息量。【Objective】It is of great practical significance to investigate, manage and exploit soil resources based on knowledge mining and updating of historical soil maps, while screening of representative training samples out of the historical soil maps is a key step to accomplish the task. 【Method】Jingde County of Xuancheng City in Anhui Province was cited as the study area. In this paper, a new method for screening of training samples was developed, consisting of determining quantity of samples and specifying sample locations. The area segmented linear-scaling method, which builds a linear correspondence between the area and the number of samples in each area segment, was applied to determination of quantity of sample in each historical soil map polygon, and then after making geographical neighborhood analysis of elevation and slope, the two important environmental covariates, the stable cells in spatial variation of the environmental covariates were defined as sample locations. Geographical neighborhood analysis index indicates the degree of spatial variation of the environmental covariates in the neighborhood.【Result】Results show that the use of the area segmented linear-scaling method to determine quantity solved the problem that had never been pondered in past researches of how to distribute samples among units that were of the same type, but consisted of a number of polygons. When this method was used to define sample locations in polygons located in topographically flat areas, determination of spatial distribution of sample sites based on elevation or slope did not vary much, whereas in polygons located in mountainous areas, the sample sites defined based on slope were mostly located in places relatively stable in topography and more representative of the entire polygon. Compared with the environmental covariates histogram peak method used in most of the researches, this method is higher in odds ratio and standard deviation, and the samples defined with this method are bigger in volume of information.

关 键 词：历史土壤图 样本数量 邻域分析 样本位置 

分 类 号：P934[天文地球—自然地理学]