Spatial-temporal multi-modal visualization of volumetric simulation and in situ satellite data

Abstract: This thesis describes the work done by two students from Link¨oping University during a five month stay at Community Coordinated Modelling Center (CCMC) at the National Aeronautics and Space Administration (NASA). The work includes the implementation of algorithms for rendering time-varying volume simulation data from space weather simulations hosted by the CCMC, as well as visualizing photo sequences taken by the Solar Dynamics Observatory (SDO) satellite orbiting Earth. Both these capabilities are added to the OpenSpace software to create a multi-modal visualization where scientists, as well as museum audiences, can observe the Sun’s activity and its effects on the heliosphere as a whole. Both the simulation data and the image sequence provided by the SDO are typically larger than what can be fitted into the main memory of modern computers, which requires the data to be streamed from disk. Due to limitations caused by disk and GPU bandwidth, it is not possible to stream the full resolution data sets in interactive frame rates. A multi-resolution bricking scheme is implemented to allow for interactive visualization of the large volumetric data sets. To decrease GPU memory usage and minimize data streaming, subvolumes are represented using different spatial and temporal resolution depending on their relative importance to the visual quality. By introducing the concept of a memory budget and a streaming budget, the algorithm allows the user to control how the limited memory and streaming resources are utilized. To decrease the amount of data to be streamed when visualizing image sequences from SDO, a simpler multi-resolution bricking scheme has been implemented. Spatial resolution of different subregions of the image is varied based on their visibility and projected size on the screen. Results show that the presented implementations enable interactive visualization of volumetric space weather data and satellite data. By varying the streaming budget and memory budget for a volumetric simulation, frame rate can be traded against visual quality.