{"title":"区间和比率变量属性不确定性的地理可视化:矢量数据的框架与实现","authors":"Hyeongmo Koo , Yongwan Chun , Daniel A. Griffith","doi":"10.1016/j.jvlc.2017.11.007","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":54754,"journal":{"name":"Journal of Visual Languages and Computing","volume":"44 ","pages":"Pages 89-96"},"PeriodicalIF":0.0000,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.jvlc.2017.11.007","citationCount":"8","resultStr":"{\"title\":\"Geovisualizing attribute uncertainty of interval and ratio variables: A framework and an implementation for vector data\",\"authors\":\"Hyeongmo Koo , Yongwan Chun , Daniel A. Griffith\",\"doi\":\"10.1016/j.jvlc.2017.11.007\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>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.</p></div>\",\"PeriodicalId\":54754,\"journal\":{\"name\":\"Journal of Visual Languages and Computing\",\"volume\":\"44 \",\"pages\":\"Pages 89-96\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.jvlc.2017.11.007\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Visual Languages and Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1045926X15300070\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Visual Languages and Computing","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1045926X15300070","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Computer Science","Score":null,"Total":0}
Geovisualizing attribute uncertainty of interval and ratio variables: A framework and an implementation for vector data
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.
期刊介绍:
The Journal of Visual Languages and Computing is a forum for researchers, practitioners, and developers to exchange ideas and results for the advancement of visual languages and its implication to the art of computing. The journal publishes research papers, state-of-the-art surveys, and review articles in all aspects of visual languages.