Identification of representative samples from existing samples for digital soil mapping

doi:10.1016/j.geoderma.2017.03.014

	Identification of representative samples from existing samples for digital soil mapping
	An Yiming 1,2; Yang Lin 1,3; Zhu A-Xing 1,4,5,6; Qin Chengzhi 1; Shi JingJing 1,2
刊名	GEODERMA
	2018-02-01
卷号	311 页码:109-119
关键词	Digital soil mapping Similarity based method under soil-landscape inference model (SoLIM) Representative samples
ISSN号	0016-7061
DOI	10.1016/j.geoderma.2017.03.014
通讯作者	Yang Lin(yanglin@lreis.ac.cn)
英文摘要	Existing sample data are important for digital soil mapping. Different sample points possess different representativeness. The representativeness of samples influences the soil mapping result greatly. However, few study focus on assessing the representativeness of single sample. In this paper, we proposed a method to identify representative samples from existing samples collected from multiple resources. The basic idea of the method was to use clusters of environmental covariates to approximate types of soil variations, and check the occupancy of the existing samples in centroids of environmental clusters. Those samples locating in typical locations or centroids of environmental clusters were considered as representative samples. In this paper, the proposed method was used to discern representative samples in 282 soil samples in Anhui Province, China. SOM content was mapped using a similarity based mapping method. Two cases with different training samples (representative samples, non -representative samples, and training samples including representative and non-representative samples) and validation samples were set to compare the mapping results and accuracies. The results showed that the SOM content maps predicted using representative training samples had generally higher accuracy than the results produced using non -representative samples, and comparative accuracies with the results produced using full training samples. To discern representative samples is helpful for understanding the soil-landscape relationships in an area and the proposed method can be used to design supplementary samples for a better soil mapping result. Mapping results and accuracies showed that different training and validation sample sets impacted the mapping results and accuracies greatly, which indicates that researchers should be cautious when using randomization to obtain training and validation subsets for soil mapping. (C) 2017 Elsevier B.V. All rights reserved.
资助项目	National Natural Science Foundation of China[41471178] ; National Natural Science Foundation of China[41530749] ; National Natural Science Foundation of China[41431177] ; National Key Technology Innovation Project for Water Pollution Control and Remediation[2013ZX07103006] ; Featured Institute Construction Services Program[TSYJS03] ; National Basic Research Program of China[2015CB954102] ; Natural Science Research Program of Jiangsu[14KJA170001] ; University of Wisconsin-Madison ; One-Thousand Talents Program of China
WOS关键词	ALGORITHM
WOS研究方向	Agriculture
语种	英语
出版者	ELSEVIER SCIENCE BV
WOS记录号	WOS:000415771300012
资助机构	National Natural Science Foundation of China ; National Key Technology Innovation Project for Water Pollution Control and Remediation ; Featured Institute Construction Services Program ; National Basic Research Program of China ; Natural Science Research Program of Jiangsu ; University of Wisconsin-Madison ; One-Thousand Talents Program of China
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/56742]
专题	中国科学院地理科学与资源研究所
通讯作者	Yang Lin
作者单位	1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Nanjing Univ, Sch Geog & Oceanog Sci, Nanjing, Jiangsu, Peoples R China 4.Nanjing Normal Univ, Key Lab Virtual Geog Environm, Minist Educ, Nanjing 210023, Jiangsu, Peoples R China 5.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Jiangsu, Peoples R China 6.Univ Wisconsin, Dept Geog, Madison, WI 53706 USA
推荐引用方式 GB/T 7714	An Yiming,Yang Lin,Zhu A-Xing,et al. Identification of representative samples from existing samples for digital soil mapping[J]. GEODERMA,2018,311:109-119.
APA	An Yiming,Yang Lin,Zhu A-Xing,Qin Chengzhi,&Shi JingJing.(2018).Identification of representative samples from existing samples for digital soil mapping.GEODERMA,311,109-119.
MLA	An Yiming,et al."Identification of representative samples from existing samples for digital soil mapping".GEODERMA 311(2018):109-119.