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.
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Ge, Y., Hexiang, B., Li, S. (2008). Geo-spatial Data Analysis, Quality Assessment and Visualization. In: Gervasi, O., Murgante, B., Laganà, A., Taniar, D., Mun, Y., Gavrilova, M.L. (eds) Computational Science and Its Applications – ICCSA 2008. ICCSA 2008. Lecture Notes in Computer Science, vol 5072. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69839-5_20
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DOI: https://doi.org/10.1007/978-3-540-69839-5_20
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