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- Albertoni, Riccardo, et al.
(author)
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Knowledge Extraction by Visual Data Mining of Metadata in Site Planning
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Other publication (other academic/artistic)abstract
- The paper describes a tool designed within the first stage of the European project INVISIP in order to explore geographical metadata in the site planning process. A visual data mining approach is applied to a database of geographical metadata to help the user find an optimal subset of the existing geographical datasets for his particular planning task. It allows the user to perform both confirmative and explorative analysis. The approach is implemented in the Visual Data Mining tool, which integrates different types of visualisations with various interaction functionalities. It includes the interactive communication with the user and the brushing and linking process between different visualisations. The paper also presents an example of an application on a test metadatabase which was created for this purpose.
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| 3. |
- Andersson, L.C., et al.
(author)
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Lineament mapping in Northern Sweden from Landsat images using orthogonal image transforms
- 1980
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In: Sixth Annual Symposium Machine Processing of Remotely Sensed Data and Soil Information Systems and Remote Sensing and Soil Survey, June 3 - 6, 1980, Purdue Univ., Laboratory for Applications of Remote Sensing, West Lafayette, Ind. - New York : IEEE Communications Society. ; , s. 147-157
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Conference paper (peer-reviewed)abstract
- The emphasis of this paper is put on mapping of geological linear structures, and in particular the correlation between these structures orientation and geological or geophysical data. It is also the intention of the authors to present a method to map these structures more objectively than up to now
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| 4. |
- Andersson, L.C., et al.
(author)
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Lineaments analysis using global and local Fourier transforms
- 1983
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In: Proceedings of the fourth international conference on basement tectonics, Oslo, Norway, August 10-14, 1981. - Salt Lake City : International Basement Tectonics Association. - 0916347001 ; , s. 63-69
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Conference paper (peer-reviewed)
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| 5. |
- Brindt, Lars, et al.
(author)
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Direction dependent interpolation of aeromagnetic data
- 1985
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In: Machine Processing of Remotely Sensed Data. - West Lafayette, Ind : Purdue University Press. ; , s. 86-95
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Conference paper (peer-reviewed)abstract
- A method for level correction and interpolation of anisotropically sampled aeromagnetic data is described. The level-correction is based on a piecewise comparison of adjacent flight-lines. The interpolation scheme is based on cubic splines and preserves thin linear structures in anisotropic potential field data. The design of such a method is seen as an important building block in the design of an image-based information system for geologic applications
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| 6. |
- Demšar, Urška, 1972-
(author)
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Data mining of geospatial data: combining visual and automatic methods
- 2006
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Doctoral thesis (other academic/artistic)abstract
- Most of the largest databases currently available have a strong geospatial component and contain potentially useful information which might be of value. The discipline concerned with extracting this information and knowledge is data mining. Knowledge discovery is performed by applying automatic algorithms which recognise patterns in the data. Classical data mining algorithms assume that data are independently generated and identically distributed. Geospatial data are multidimensional, spatially autocorrelated and heterogeneous. These properties make classical data mining algorithms inappropriate for geospatial data, as their basic assumptions cease to be valid. Extracting knowledge from geospatial data therefore requires special approaches. One way to do that is to use visual data mining, where the data is presented in visual form for a human to perform the pattern recognition. When visual mining is applied to geospatial data, it is part of the discipline called exploratory geovisualisation. Both automatic and visual data mining have their respective advantages. Computers can treat large amounts of data much faster than humans, while humans are able to recognise objects and visually explore data much more effectively than computers. A combination of visual and automatic data mining draws together human cognitive skills and computer efficiency and permits faster and more efficient knowledge discovery. This thesis investigates if a combination of visual and automatic data mining is useful for exploration of geospatial data. Three case studies illustrate three different combinations of methods. Hierarchical clustering is combined with visual data mining for exploration of geographical metadata in the first case study. The second case study presents an attempt to explore an environmental dataset by a combination of visual mining and a Self-Organising Map. Spatial pre-processing and visual data mining methods were used in the third case study for emergency response data. Contemporary system design methods involve user participation at all stages. These methods originated in the field of Human-Computer Interaction, but have been adapted for the geovisualisation issues related to spatial problem solving. Attention to user-centred design was present in all three case studies, but the principles were fully followed only for the third case study, where a usability assessment was performed using a combination of a formal evaluation and exploratory usability.
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