ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume III-2
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-2, 129–136, 2016
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-2, 129–136, 2016

  02 Jun 2016

02 Jun 2016


B. H. Sibolla1,3, T. Van Zyl2, and S. Coetzee3 B. H. Sibolla et al.
  • 1Meraka Institute, Council for Scientific and Industrial Research, Pretoria, South Africa
  • 2School of Computer Science and Applied Mathematics, University of the Witwatersrand, Johannesburg, South Africa
  • 3Center for GeoInformation Science, Department of Geography, Geoinformation and Meteorology, University of Pretoria, South Africa

Keywords: Geovisualisation, Geospatial Visual Analytics, Sensor Networks, Taxonomy

Abstract. Geospatial data has very specific characteristics that need to be carefully captured in its visualisation, in order for the user and the viewer to gain knowledge from it. The science of visualisation has gained much traction over the last decade as a response to various visualisation challenges. During the development of an open source based, dynamic two-dimensional visualisation library, that caters for geospatial streaming data, it was found necessary to conduct a review of existing geospatial visualisation taxonomies. The review was done in order to inform the design phase of the library development, such that either an existing taxonomy can be adopted or extended to fit the needs at hand. The major challenge in this case is to develop dynamic two dimensional visualisations that enable human interaction in order to assist the user to understand the data streams that are continuously being updated. This paper reviews the existing geospatial data visualisation taxonomies that have been developed over the years. Based on the review, an adopted taxonomy for visualisation of geospatial streaming data is presented. Example applications of this taxonomy are also provided. The adopted taxonomy will then be used to develop the information model for the visualisation library in a further study.