Name
Abstract | ||
|---|---|---|
The use of computer visualization as a means to analyze complex geographic datasets is discussed. Visualization is a valuable tool for conducting exploratory data analysis on geographical data; making good use of the human eye's unparalleled ability to recognize structure and relationships that may be inherent within the data. Traditional GIS are extremely poor at visualization, being limited to a very restricted set of visual attributes with which to convey information (position, size, color). The use of a more sophisticated approach is discussed in detail. Specifically, a system to visualise complex environmental datasets is described, which makes use of knowledge concerning the problem domain as well as knowledge concerning human cognition.In the realizations produced, the most salient attributes in the data, for a particular task, are assigned to the most striking visual attributes. Assignments are controlled by heuristics that may be changed to after system behavior. Results are presented showing the application of this approach on datasets involving several multidimensional thematic layers of environmental data, used in mineral exploration. |
Year | DOI | Venue |
|---|---|---|
1997 | 10.1142/S0218001497000111 | INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE |
Keywords | Field | DocType |
visualization, exploratory analysis, geographical data, knowledge-based | Information visualization,Problem domain,Visualization,Heuristics,Artificial intelligence,Knowledge base,Systems architecture,Environmental data,Exploratory data analysis,Geography,Machine learning | Journal |
Volume | Issue | ISSN |
11 | 2 | 0218-0014 |
Citations | PageRank | References |
2 | 0.49 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mark Gahegan | 1 | 571 | 55.38 |
| David O'brien | 2 | 2 | 0.49 |