An optimal parameters-based geographical detector model enhances geographic characteristics of explanatory variables for spatial heterogeneity analysis: cases with different types of spatial data

doi:10.1080/15481603.2020.1760434

	An optimal parameters-based geographical detector model enhances geographic characteristics of explanatory variables for spatial heterogeneity analysis: cases with different types of spatial data
	Song, Yongze 1; Wang, Jinfeng 2; Ge, Yong 2; Xu, Chengdong 2
刊名	GISCIENCE & REMOTE SENSING
	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.
资助项目	National Natural Science Foundation of China[41421001]
WOS关键词	WEIGHTED REGRESSION ; INNER-MONGOLIA ; VEGETATION ; ASSOCIATION ; LANDSCAPE ; DENSITY ; IMPACT ; CHINA
WOS研究方向	Physical Geography ; Remote Sensing
语种	英语
出版者	TAYLOR & FRANCIS LTD
WOS记录号	WOS:000535621700001
资助机构	National Natural Science Foundation of China
内容类型	期刊论文
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.Curtin Univ, Sch Design & Built Environm, Perth, WA, Australia 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China
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.