Title
Geovisualizing attribute uncertainty of interval and ratio variables: A framework and an implementation for vector data.
Abstract
Geovisualization of attribute uncertainty helps users to recognize underlying processes of spatial data. However, it still lacks an availability of uncertainty visualization tools in a standard GIS environment. This paper proposes a framework for attribute uncertainty visualization by extending bivariate mapping techniques. Specifically, this framework utilizes two cartographic techniques, choropleth mapping and proportional symbol mapping based on the types of attributes. This framework is implemented as an extension of ArcGIS in which three types of visualization tools are available: overlaid symbols on a choropleth map, coloring properties to a proportional symbol map, and composite symbols.
Year
DOI
Venue
2018
10.1016/j.jvlc.2017.11.007
Journal of Visual Languages & Computing
Keywords
Field
DocType
Uncertainty,Geovisualization,Bivariate mapping,GIS
Spatial analysis,Data mining,Geovisualization,Computer science,Choropleth map,Visualization,Choropleth Mapping,Bivariate analysis
Journal
Volume
ISSN
Citations 
44
1045-926X
2
PageRank 
References 
Authors
0.40
5
3
Name
Order
Citations
PageRank
Hyeongmo Koo120.74
Yongwan Chun2216.25
Daniel A. Griffith39123.76