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Dual Aspects of a Multi-Resolution Grid-Based Terrain Data Model with supplementary Irregular Data Points
Linköping University, Department of Computer and Information Science.
Linköping University, Department of Computer and Information Science, GIS - Geographical Information Science Group. Linköping University, The Institute of Technology.
2000 (English)In: Proceedings of the 3rd International Conference on Information Fusion, Paris, France, IEEE , 2000, Vol. 2, WED4/3-WED410 vol.2 p.Conference paper, Published paper (Refereed)
Abstract [en]

Digital terrain data models in high resolution are required in applications for visualization but also, e.g. for identification of various types of terrain features. These two aspects are in a way contradictory since the former application require a large number of data points to represent the high resolution, while the latter cannot deal with such a large number of data points without high demands for heavy computational powers. A solution to this problem is a structure that includes quantitative characteristics for visualization and a qualitative representation for feature analysis. A digital terrain data model characterized with these dual aspects has been designed and is presented in this work.

Place, publisher, year, edition, pages
IEEE , 2000. Vol. 2, WED4/3-WED410 vol.2 p.
Keyword [en]
data models, data visualisation, geographic information systems, spatial reasoning, terrain mapping, wavelet transforms
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-13309ISBN: 2-7257-0000-0 (print)OAI: oai:DiVA.org:liu-13309DiVA: diva2:18310
Conference
Third International Conference on Information Fusion, 10-13 July 2000, Paris, France
Available from: 2008-05-27 Created: 2008-05-27 Last updated: 2015-01-13
In thesis
1. Terrain Object recognition and Context Fusion for Decision Support
Open this publication in new window or tab >>Terrain Object recognition and Context Fusion for Decision Support
2008 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

A laser radar can be used to generate 3D data about the terrain in a very high resolution. The development of new support technologies to analyze these data is critical to the effective and efficient use of these data in decision support systems, due to the large amounts of data that are generated. Adequate technology in this regard is currently not available and development of new methods and algorithms to this end are important goals of this work.

A semi-qualitative data structure for terrain surface modelling has been developed. A categorization and triangulation process has also been developed to substitute the high resolution 3D model for this data structure. The qualitative part of the structure can be used for detection and recognition of terrain features. The quantitative part of the structure is, together with the qualitative part, used for visualization of the terrain surface. Substituting the 3D model for the semi-qualitative structures means that a data reduction is performed.

A number of algorithms for detection and recognition of different terrain objects have been developed. The algorithms use the qualitative part of the previously developed semi-qualitative data structure as input. The taken approach is based on matching of symbols and syntactic pattern recognition. Results regarding the accuracy of the implemented algorithms for detection and recognition of terrain objects are visualized.

A further important goal has been to develop a methodology for determining driveability using 3D-data and other geographic data. These data must be fused with vehicle data to determine the properties of the terrain context of our operations with respect to driveability. This fusion process is therefore called context fusion. The recognized terrain objects are used together with map data in this method. The uncertainty associated with the imprecision of the data has been taken into account as well.

Place, publisher, year, edition, pages
Institutionen för datavetenskap, 2008. 88 p.
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1371
Keyword
nformation Fusion, Terrain Elevation Model, Driveability, Context Fusion, Terrain Object Recognition
National Category
Computer Science
Identifiers
urn:nbn:se:liu:diva-11926 (URN)978-91-7393-861-7 (ISBN)
Presentation
2008-06-11, Alan Turing, Hus E, Campus Valla, Linköpings universitet, Linköping, 13:15 (English)
Opponent
Supervisors
Note
Report code: LiU-Tek-Lic-2008:29.Available from: 2008-05-27 Created: 2008-05-27 Last updated: 2009-05-05

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Jungert, Erland

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Citation style
  • apa
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Output format
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