A representativeness-directed approach to mitigate spatial bias in VGI for the predictive mapping of geographic phenomena

doi:10.1080/13658816.2019.1615071

	A representativeness-directed approach to mitigate spatial bias in VGI for the predictive mapping of geographic phenomena
	Zhang, Guiming 5; Zhu, A-Xing 1,2,3,4,6
刊名	INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
	2019-09-02
卷号	33 期号:9 页码:1873-1893
关键词	Volunteered geographic information (VGI) spatial bias sample representativeness predictive mapping habitat suitability mapping
ISSN号	1365-8816
DOI	10.1080/13658816.2019.1615071
通讯作者	Zhang, Guiming(guiming.zhang@du.edu)
英文摘要	Volunteered geographic information (VGI) contains valuable field observations that represent the spatial distribution of geographic phenomena. As such, it has the potential to provide regularly updated low-cost field samples for predictively mapping the spatial variations of geographic phenomena. The predictive mapping of geographic phenomena often requires representative samples for high mapping accuracy, but samples consisting of VGI observations are often not representative as they concentrate on specific geographic areas (i.e. spatial bias) due to the opportunistic nature of voluntary observation efforts. In this article, we propose a representativeness-directed approach to mitigate spatial bias in VGI for predictive mapping. The proposed approach defines and quantifies sample representativeness by comparing the probability distributions of sample locations and the mapping area in the environmental covariate space. Spatial bias is mitigated by weighting the sample locations to maximize their representativeness. The approach is evaluated using species habit suitability mapping as a case study. The results show that the accuracy of predictive mapping using weighted sample locations is higher than using unweighted sample locations. A positive relationship between sample representativeness and mapping accuracy is also observed, suggesting that sample representativeness is a valid indicator of predictive mapping accuracy. This approach mitigates spatial bias in VGI to improve predictive mapping accuracy.
资助项目	University of Denver ; Department of Geography, University of Wisconsin-Madison
WOS关键词	SAMPLE SELECTION BIAS ; POINT PATTERN-ANALYSIS ; SPECIES DISTRIBUTIONS ; DISTRIBUTION MODELS ; CITIZEN DATA ; INFORMATION ; KNOWLEDGE ; IMPROVE ; INFERENCE ; REDUCE
WOS研究方向	Computer Science ; Geography ; Physical Geography ; Information Science & Library Science
语种	英语
出版者	TAYLOR & FRANCIS LTD
WOS记录号	WOS:000485047400009
资助机构	University of Denver ; Department of Geography, University of Wisconsin-Madison
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/69767]
专题	中国科学院地理科学与资源研究所
通讯作者	Zhang, Guiming
作者单位	1.Jiangsu Ctr Collaborat Innovat Geog Informat Res, Nanjing, 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, Peoples R China 4.State Key Lab Cultivat Base Geog Environm Evolut, Nanjing, Jiangsu, Peoples R China 5.Univ Denver, Dept Geog & Environm, Denver, CO 80208 USA 6.Nanjing Normal Univ, Minist Educ, Key Lab Virtual Geog Environm, Nanjing, Jiangsu, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Guiming,Zhu, A-Xing. A representativeness-directed approach to mitigate spatial bias in VGI for the predictive mapping of geographic phenomena[J]. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE,2019,33(9):1873-1893.
APA	Zhang, Guiming,&Zhu, A-Xing.(2019).A representativeness-directed approach to mitigate spatial bias in VGI for the predictive mapping of geographic phenomena.INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE,33(9),1873-1893.
MLA	Zhang, Guiming,et al."A representativeness-directed approach to mitigate spatial bias in VGI for the predictive mapping of geographic phenomena".INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE 33.9(2019):1873-1893.