Welcome!
To use the personalized features of this site, please log in or register.
If you have forgotten your username or password, we can help.
My Menu
Saved Items

Geo-spatial Data Analysis, Quality Assessment and Visualization

Yong Ge1, 2 Contact Information, Bai HexiangContact Information and Sanping LiContact Information

(1)  State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences & Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
(2)  Department of Earth and Space Science and Engineering, York University, Canada
Abstract
As GIS and Remote Sensing technologies develops rapidly, they provide the strong technical support for multi-level geo-spatial data acquisition. However, serious lag of spatial analysis technology leads to the “data explosion but knowledge poverty”. At the same time, the lack of quality assessment means allows users to doubt the reliability of colourful “high-tech” geospatial products. This paper would propose an advanced and integrated architecture to establish the relations between spatial data analysis, the uncertainty and reliability of geo-spatial data in terms of geo-spatial data processing flow. This provides a quality assessment for geo-spatial analysis outcome from multi-source information fusion and integration, and a support for decision maker based on the reliability. Furthermore, geo-visualization technology would help people intuitively know the quantity, distribution, spatial structure and tendency of uncertainty of geo-spatial data and information. A case study is followed to describe the framework.

Keywords  Geo-spatial data analysis - quality assessment - visualization


Contact Information Yong Ge
Email: gey@lreis.ac.cn
Email: gey@yorku.ca

Contact Information Bai Hexiang
Email: baihx@lreis.ac.cn

Contact Information Sanping Li
Email: lisp@lreis.ac.cn
Fulltext Preview (Small, Large)
Image of the first page of the fulltext

References secured to subscribers.



Export this chapter
Export this chapter as RIS | Text
 
Remote Address: 38.107.191.103 • Server: mpweb24
HTTP User Agent: CCBot/1.0 (+http://www.commoncrawl.org/bot.html)