文献类型： 外文期刊

作者： Zhu, A-Xing ¹ ; Zhang, Guiming ³ ; Wang, Wei ⁷ ; Xiao, Wen ⁸ ; Huang, Zhi-Pang ⁸ ; Dunzhu, Ge-Sang ³ ; Ren, Guopeng ⁸ ; Qin, Cheng-Zhi ³ ; Yang, Lin ³ ; Pei, Tao ³ ; Yang, Shengtian ⁶ ;

作者机构： 1.Nanjing Normal Univ, Key Lab Virtual Geog Environm, Nanjing, Jiangsu, Peoples R China

2.State Key Lab Cultivat Base Geog Environm Evolut, Nanjing, Jiangsu, Peoples R China

3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China

4.Univ Wisconsin, Dept Geog, Madison, WI 53706 USA

5.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing, Jiangsu, Peoples R China

6.Beijing Normal Univ, Dept Geog, Beijing 100875, Peoples R China

7.Chinese Res Inst Environm Sci, Beijing, Peoples R China

8.Dali Univ, Inst Eastern Himalaya Biodivers Res, Dali, Peoples R China

9.Tibet Acad Agr & Anim Sci, Lhasa, Peoples R China

关键词： spatial bias; Rhinopithecus bieti; volunteered geographic information (VGI); citizen data; location imprecision

期刊名称：INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE （ 影响因子：5.152； 五年影响因子：5.081 ）

ISSN： 1365-8816

年卷期： 2015 年 29 卷 10 期

页码：

收录情况： SCI

摘要： The vast accumulation of environmental data and the rapid development of geospatial visualization and analytical techniques make it possible for scientists to solicit information from local citizens to map spatial variation of geographic phenomena. However, data provided by citizens (referred to as citizen data in this article) suffer two limitations for mapping: bias in spatial coverage and imprecision in spatial location. This article presents an approach to minimizing the impacts of these two limitations of citizen data using geospatial analysis techniques. The approach reduces location imprecision by adopting a frequency-sampling strategy to identify representative presence locations from areas over which citizens observed the geographic phenomenon. The approach compensates for the spatial bias by weighting presence locations with cumulative visibility (the frequency at which a given location can be seen by local citizens). As a case study to demonstrate the principle, this approach was applied to map the habitat suitability of the black-and-white snub-nosed monkey (Rhinopithecus bieti) in Yunnan, China. Sightings of R. bieti were elicited from local citizens using a geovisualization platform and then processed with the proposed approach to predict a habitat suitability map. Presence locations of R. bieti recorded by biologists through intensive field tracking were used to validate the predicted habitat suitability map. Validation showed that the continuous Boyce index (B-cont(0.1)) calculated on the suitability map was 0.873 (95% CI: [0.810, 0.917]), indicating that the map was highly consistent with the field-observed distribution of R. bieti. B-cont(0.1) was much lower (0.173) for the suitability map predicted based on citizen data when location imprecision was not reduced and even lower (-0.048) when there was no compensation for spatial bias. This indicates that the proposed approach effectively minimized the impacts of location imprecision and spatial bias in citizen data and therefore effectively improved the quality of mapped spatial variation using citizen data. It further implies that, with the application of geospatial analysis techniques to properly account for limitations in citizen data, valuable information embedded in such data can be extracted and used for scientific mapping.