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. © 2008 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Ge, Y., Hexiang, B., & Li, S. (2008). Geo-spatial data analysis, quality assessment and visualization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5072 LNCS, pp. 258–267). https://doi.org/10.1007/978-3-540-69839-5_20
Mendeley helps you to discover research relevant for your work.