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A representativeness heuristic for mitigating spatial bias in existing soil samples for digital soil mapping
Zhang, Guiming1; Zhu, A-Xing2,3,4,5
2019-10-01
Source PublicationGEODERMA
ISSN0016-7061
Volume351Pages:130-143
Corresponding AuthorZhang, Guiming(guiming.zhang@du.edu)
AbstractDigital soil mapping (DSM) often relies on existing soil samples obtained from various sources. However, the spatial distribution of such soil samples can be biased, for example, towards areas of better accessibility. Such biased coverage over the geographic space (i.e., spatial bias) often leads to biased coverage of the soil samples over the environmental covariate space. As a result, spatial bias degrades the correlation or statistical relationship between samples and covariates in the study area and impedes DSM accuracy. This paper presents a representativeness heuristic for mitigating spatial bias in existing soil samples for improving DSM accuracy. The key idea of the heuristic was to define and quantify sample representativeness as the goodness-of-coverage of the soil samples over the environmental covariate space. Spatial bias was then mitigated by weighting the samples towards maximizing their representativeness. Determination of the sample weights was conceived as an optimization problem and accordingly the optimal weights were determined using a genetic algorithm. To evaluate the effectiveness of the representativeness heuristic, a case study of mapping soil organic matter (SOM) content using existing soil samples was conducted in Heshan study area, northeastern China. Results showed that weighting soil samples using the optimal weights determined from the representativeness heuristic improved SOM content mapping accuracy. Moreover, a positive relationship between sample representativeness and mapping accuracy was observed, suggesting sample representativeness is an effective indicator of mapping accuracy. Additionally, the determined optimal weights were informative of individual sample importance and thus can be used as guidance to filter existing soil samples to improve DSM accuracy.
KeywordSample representativeness Existing soil samples Spatial bias Digital soil mapping (DSM)
DOI10.1015/j.geoderma.2019.05.024
WOS KeywordPOINT PATTERN-ANALYSIS ; ORGANIC-MATTER ; INFORMATION ; IMPROVE ; REDUCE
Indexed BySCI
Language英语
Funding ProjectUniversity of Denver ; Department of Geography, University of Wisconsin-Madison ; National Natural Science Foundation of China[41431177] ; National Natural Science Foundation of China[41871300] ; National Basic Research Program of China[2015CB954102] ; PAPD ; Outstanding Innovation Team in Colleges and Universities in Jiangsu Province ; University of Wisconsin-Madison
Funding OrganizationUniversity of Denver ; Department of Geography, University of Wisconsin-Madison ; National Natural Science Foundation of China ; National Basic Research Program of China ; PAPD ; Outstanding Innovation Team in Colleges and Universities in Jiangsu Province ; University of Wisconsin-Madison
WOS Research AreaAgriculture
WOS SubjectSoil Science
WOS IDWOS:000474495700013
PublisherELSEVIER SCIENCE BV
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/58350
Collection中国科学院地理科学与资源研究所
Corresponding AuthorZhang, Guiming
Affiliation1.Univ Denver, Dept Geog & Environm, Denver, CO 80208 USA
2.Univ Wisconsin, Dept Geog, Madison, WI 53706 USA
3.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Jiangsu, Peoples R China
4.Nanjing Normal Univ, Minist Educ, Key Lab Virtual Geog Environm, Nanjing 210023, Jiangsu, Peoples R China
5.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
Recommended Citation
GB/T 7714
Zhang, Guiming,Zhu, A-Xing. A representativeness heuristic for mitigating spatial bias in existing soil samples for digital soil mapping[J]. GEODERMA,2019,351:130-143.
APA Zhang, Guiming,&Zhu, A-Xing.(2019).A representativeness heuristic for mitigating spatial bias in existing soil samples for digital soil mapping.GEODERMA,351,130-143.
MLA Zhang, Guiming,et al."A representativeness heuristic for mitigating spatial bias in existing soil samples for digital soil mapping".GEODERMA 351(2019):130-143.
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