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An Icon Map-based exploratory analytical approach for multivariate geospatial data
Zhang XianFeng ; Liao ChunHua ; Liu Yu ; Li, Jonathan
刊名science china information sciences
2013
关键词iconmap soil fertility visualization icon blocks multivariate geospatial data 3D GEOVISUALIZATION VISUALIZATION
DOI10.1007/s11432-012-4692-6
英文摘要This paper discusses an iconmap-based visualization technique that enables multiple geospatial variables to be illustrated in a single GIS raster layer. This is achieved by extending the conventional pixel-based data structure to an iconic design. In this way, spatial patterns generated by the interaction of geographic variables can be disclosed, and geospatial information mining can be readily achieved. As a case study, a visual analysis of soil organic matter and soil nutrients for Shuangliu County in the city of Chengdu, China, was undertaken using the prototype Icon Mapper software, developed by the authors. The results show that the static Icon Map can accurately exhibit trends in the distribution of organic matter and nutrients in soil. The dynamic iconmap can both reflect interaction patterns between organic matter and the nutrient variables, and display soil fertility levels in a comprehensive way. Thus, the iconmap-based visualization approach is shown to be a non-fused, exploratory analytical approach for multivariate data analysis and as a result is a valuable method for visually analyzing soil fertility conditions.; Computer Science, Information Systems; SCI(E); 0; ARTICLE; 1; 56
语种英语
内容类型期刊论文
源URL[http://ir.pku.edu.cn/handle/20.500.11897/155668]  
专题地球与空间科学学院
推荐引用方式
GB/T 7714
Zhang XianFeng,Liao ChunHua,Liu Yu,et al. An Icon Map-based exploratory analytical approach for multivariate geospatial data[J]. science china information sciences,2013.
APA Zhang XianFeng,Liao ChunHua,Liu Yu,&Li, Jonathan.(2013).An Icon Map-based exploratory analytical approach for multivariate geospatial data.science china information sciences.
MLA Zhang XianFeng,et al."An Icon Map-based exploratory analytical approach for multivariate geospatial data".science china information sciences (2013).
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