A representativeness-directed approach to mitigate spatial bias in VGI for the predictive mapping of geographic phenomena
文献类型：期刊论文
| 作者 | Zhang, Guiming5; Zhu, A-Xing1,2,3,4,6
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| 刊名 | INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
 |
| 出版日期 | 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. |
| WOS关键词 | SAMPLE SELECTION BIAS ; POINT PATTERN-ANALYSIS ; SPECIES DISTRIBUTIONS ; DISTRIBUTION MODELS ; CITIZEN DATA ; INFORMATION ; KNOWLEDGE ; IMPROVE ; INFERENCE ; REDUCE |
| 资助项目 | University of Denver ; Department of Geography, University of Wisconsin-Madison |
| WOS研究方向 | Computer Science ; Geography ; Physical Geography ; Information Science & Library Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000485047400009 |
| 出版者 | TAYLOR & FRANCIS LTD |
| 资助机构 | University of Denver ; Department of Geography, University of Wisconsin-Madison |
| 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. |
入库方式： OAI收割
来源：地理科学与资源研究所
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