中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Identification of representative samples from existing samples for digital soil mapping

文献类型:期刊论文

作者An Yiming3,4; Yang Lin3,5; Zhu A-Xing1,2,3,6; Qin Chengzhi3; Shi JingJing3,4
刊名GEODERMA
出版日期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
DOI10.1016/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.
WOS关键词ALGORITHM
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研究方向Agriculture
语种英语
WOS记录号WOS:000415771300012
出版者ELSEVIER SCIENCE BV
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
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.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Jiangsu, Peoples R China
2.Univ Wisconsin, Dept Geog, Madison, WI 53706 USA
3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
5.Nanjing Univ, Sch Geog & Oceanog Sci, Nanjing, Jiangsu, Peoples R China
6.Nanjing Normal Univ, Key Lab Virtual Geog Environm, Minist Educ, Nanjing 210023, Jiangsu, Peoples R China
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.

入库方式: OAI收割

来源:地理科学与资源研究所

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