Towards Utilizing Heterogeneous Analytics Interfaces in Coastal Infrastructure Management
University of North Carolina at Charlotte
Geo-spatial data such as multiple return LIDAR terrain data, sonar data and ocean surge data play a significant role in various emergency response and planning scenarios. Such multi-planar and volumetric data is rich in geographic features; more importantly, it also contains a significant temporal component. Understanding geospatial-temporal changes is a fundamental aspect of analyzing, understanding and responding to natural phenomena (e.g. hurricane impacts, coastal infrastructure changes, and ocean surges). We are collaborating with a number of scientific colleagues on projects relating to prediction of and response to various natural disasters such as hurricanes and oil spills. These colleagues and their supporting agencies have identified several visual analytic needs relating to inspecting and cleaning up multi-return LIDAR and sonar data and volumetric ocean flows. These include the ability to provide efficient interactive display systems and user interfaces for navigating, selecting and inspecting outlier 3D points or flow vectors; the ability for multiple co-located, collaborating scientists to perform such analysis on visually dense 3D data; and the ability of the system to semi-automatically extract high-level features from large data sets and to then help the scientist construct a narrative that explains the salient temporal-spatial features in a concise textual and abstract visual form.
X. Wang, T. Butkiewicz,I. Cho, and Z. Wartell,“Towards utilizing heterogeneous analytics interfaces in coastal infrastructure management,” in Charlotte Visualization Center: Technical Report UNCC‑CVC‑12‑15, University of North Carolina at Charlotte, 2012