DOI: 10.1016/j.jag.2013.09.005
Scopus记录号: 2-s2.0-84897061993
论文题名: Spatial data discretization methods for geocomputation
作者: Cao F ; , Ge Y ; , Wang J
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2014
卷: 26, 期: 1 起始页码: 432
结束页码: 440
语种: 英语
英文关键词: Discretization
; Geocomputation
; Spatial autocorrelation
; Spatial data
; Spatial heterogeneity
Scopus关键词: autocorrelation
; heterogeneity
; numerical method
; spatial data
; China
; Shanxi
英文摘要: Geocomputation provides solutions to complex geographic problems. Continuous and discrete spatialdata are involved in the geocomputational process; however, geocomputational methods for discretespatial data cannot be directly applied to continuous or mixed spatial data. Therefore, discretizationmethods for continuous or mixed spatial data are involved in the process. Since spatial data has spatialfeatures, such as association, heterogeneity and spatial structure, these features cannot be handled bytraditional discretization methods. Therefore, this work develops feature-based spatial data discretizationmethods that achieve optimal discretization results for spatial data using spatial information implicit inthose features. Two discretization methods considering the features of spatial data are presented. One isan unsupervised method considering autocorrelation of spatial data and the other is a supervised methodconsidering spatial heterogeneity. Discretization processes of the two methods are exemplified usingneural tube defects (NTD) for Heshun County in Shanxi Province, China. Effectiveness is also assessed. © 2013 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79741
Appears in Collections: 气候变化事实与影响
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作者单位: State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographic Sciences and Nature Resources Research, Chinese Academy of Sciences, A11 Datun Road, Beijing 100101, China
Recommended Citation:
Cao F,, Ge Y,, Wang J. Spatial data discretization methods for geocomputation[J]. International Journal of Applied Earth Observation and Geoinformation,2014-01-01,26(1)