2D and 3D Geo-Visualisation by Spatial-temporal Data
Geovisualisation (short for geographic visualisation), refers to a set of tools and techniques supporting the analysis of geospatial data through the use of interactive visualisation. Like the related fields of scientific visualisation and information visualisation, geovisualisation emphasises knowledge construction over knowledge storage or information transmission. To do this, geovisualisation communicates geospatial information in ways that, when combined with human understanding, allow for data exploration and decision-making processes. Traditional, static maps have a limited exploratory capability; the graphical representations are inextricably linked to the geographical information beneath. GIS and geovisualisation allow for more interactive maps; including the ability to explore different layers of the map, to zoom in or out, and to change the visual appearance of the map, usually on a computer display. Geovisualisation represents a set of cartographic technologies and practices that take advantage of the ability of modern microprocessors to render changes to a map in real time, allowing users to adjust the mapped data on the fly.
We have publications of geo-visualisation as below:
Liu, Y., Wang, S., Fu, X., Xie, B. (2019). A network-constrained spatial identification of high-risk roads for hit-parked-vehicle collisions in Brisbane, Australia. Environment and Planning A: Economy and Space, 51(2), 279-282.
Wang, S., Liu, Y., Sigler, T., & Corcoran, J. (2019). 3D space–time visualization of individual settlement pathways of Mainland China-born migrants in Queensland, Australia. Environment and Planning A: Economy and Space, 51(2), 275-278.
Wang, S., Corcoran, J., Liu, Y., & Sigler, T. (2018). Visualising the internal migration of the mainland China-born population between Australian capital cities over time. Australian Population Studies, 2(1), 56-58.
Xie, B., & Liu, Y. (2018). Visualizing Australia’s urban extent: a comparison between residential housing addresses and night-time light data. Regional Studies, Regional Science, 5(1), 365-368.