An optimal parameters-based geographical detector model enhances geographic characteristics of explanatory variables for spatial heterogeneity analysis: cases with different types of spatial data
文献类型：期刊论文
| 作者 | Song, Yongze2; Wang, Jinfeng1; Ge, Yong1 ; Xu, Chengdong1
|
| 刊名 | GISCIENCE & REMOTE SENSING
 |
| 出版日期 | 2020-05-13 |
| 页码 | 17 |
| 关键词 | GIS spatial analysis geographical detector spatial stratified heterogeneity spatial factors exploration R package GD |
| ISSN号 | 1548-1603 |
| DOI | 10.1080/15481603.2020.1760434 |
| 通讯作者 | Song, Yongze(yongze.song@curtin.edu.au) |
| 英文摘要 | Spatial heterogeneity represents a general characteristic of the inequitable distributions of spatial issues. The spatial stratified heterogeneity analysis investigates the heterogeneity among various strata of explanatory variables by comparing the spatial variance within strata and that between strata. The geographical detector model is a widely used technique for spatial stratified heterogeneity analysis. In the model, the spatial data discretization and spatial scale effects are fundamental issues, but they are generally determined by experience and lack accurate quantitative assessment in previous studies. To address this issue, an optimal parameters-based geographical detector (OPGD) model is developed for more accurate spatial analysis. The optimal parameters are explored as the best combination of spatial data discretization method, break number of spatial strata, and spatial scale parameter. In the study, the OPGD model is applied in three example cases with different types of spatial data, including spatial raster data, spatial point or areal statistical data, and spatial line segment data, and an R "GD" package is developed for computation. Results show that the parameter optimization process can further extract geographical characteristics and information contained in spatial explanatory variables in the geographical detector model. The improved model can be flexibly applied in both global and regional spatial analysis for various types of spatial data. Thus, the OPGD model can improve the overall capacity of spatial stratified heterogeneity analysis. The OPGD model and its diverse solutions can contribute to more accurate, flexible, and efficient spatial heterogeneity analysis, such as spatial patterns investigation and spatial factor explorations. |
| WOS关键词 | WEIGHTED REGRESSION ; INNER-MONGOLIA ; VEGETATION ; ASSOCIATION ; LANDSCAPE ; DENSITY ; IMPACT ; CHINA |
| 资助项目 | National Natural Science Foundation of China[41421001] |
| WOS研究方向 | Physical Geography ; Remote Sensing |
| 语种 | 英语 |
| WOS记录号 | WOS:000535621700001 |
| 出版者 | TAYLOR & FRANCIS LTD |
| 资助机构 | National Natural Science Foundation of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/159534]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Song, Yongze |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China 2.Curtin Univ, Sch Design & Built Environm, Perth, WA, Australia |
| 推荐引用方式 GB/T 7714 | Song, Yongze,Wang, Jinfeng,Ge, Yong,et al. An optimal parameters-based geographical detector model enhances geographic characteristics of explanatory variables for spatial heterogeneity analysis: cases with different types of spatial data[J]. GISCIENCE & REMOTE SENSING,2020:17. |
| APA | Song, Yongze,Wang, Jinfeng,Ge, Yong,&Xu, Chengdong.(2020).An optimal parameters-based geographical detector model enhances geographic characteristics of explanatory variables for spatial heterogeneity analysis: cases with different types of spatial data.GISCIENCE & REMOTE SENSING,17. |
| MLA | Song, Yongze,et al."An optimal parameters-based geographical detector model enhances geographic characteristics of explanatory variables for spatial heterogeneity analysis: cases with different types of spatial data".GISCIENCE & REMOTE SENSING (2020):17. |
入库方式： OAI收割
来源：地理科学与资源研究所
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