Seminar: A Geovisual Analytics Approach to Spatial and Visual Feature Organization and Exploration

Asikur Rahman
M.Sc. Candidate
Supervisor: Dr. Orland Hoeber

Department of Computer Science
Tuesday, Nov. 13, 2012, 12:00 p.m., Room EN 2022




Marine sonar data sets often cover large spatial regions and consist of many hundreds of thousands of sonar pings. The visual representations of the sonar data (echograms) are normally shown as long and narrow ribbons of data. The main challenge with analyzing sonar data using echograms is that the ratio of the length to the depth can be very high. As analysts zoom in to show the echogram in sufficient detail, much of the contextual information is lost and horizontal scrolling is necessary to explore and compare the data. In this thesis, a novel approach is proposed that couples a technique for visually clustering slices of the echogram based on visual similarity, with a geovisualization method that shows the spatial location of echogram slices on a virtual globe. A field trial with realworld data analysts was conducted and the results of the field trial illustrate the benefits of this


Department of Computer Science

230 Elizabeth Ave, St. John's, NL, CANADA, A1B 3X9

Postal Address: P.O. Box 4200, St. John's, NL, CANADA, A1C 5S7

Tel: (709) 864-8000