VRFire: an Immersive Visualization Experience for Wildfire Spread Analysis

Sherman, William R.; Penick, Michael A.; Su, Simon; Brown, Timothy J.; Harris, Frederick C.

doi:10.1109/vr.2007.352491

Cited by 13 publications

(6 citation statements)

References 7 publications

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“…Virtual Scientific Visualization. Immersive visualizations are important for understanding complex processes in fire behavior and for testing best practices for visualizing fire event data [21]. Our prototype uses the osgEarth, an open source geospatial graphics platform that is part of OpenSceneGraph (OSG).…”

Section: Visualization and Communication Of Resultsmentioning

confidence: 99%

Towards an Integrated Cyberinfrastructure for Scalable Data-driven Monitoring, Dynamic Prediction and Resilience of Wildfires

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Callafon

et al. 2015

Procedia Computer Science

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Wildfires are critical for ecosystems in many geographical regions. However, our current urbanized existence in these environments is inducing the ecological balance to evolve into a different dynamic leading to the biggest fires in history. Wildfire wind speeds and directions change in an instant, and first responders can only be effective if they take action as quickly as the conditions change. What is lacking in disaster management today is a system integration of real-time sensor networks, satellite imagery, near-real time data management tools, wildfire simulation tools, and connectivity to emergency command centers before, during and after a wildfire. As a first time example of such an integrated system, the WIFIRE project is building an end-to-end cyberinfrastructure for real-time and data-driven simulation, prediction and visualization of wildfire behavior. This paper summarizes the approach and early results of the WIFIRE project to integrate networked observations, e.g., heterogeneous satellite data and real-time remote sensor data with computational techniques in signal processing, visualization, modeling and data assimilation to provide a scalable, technological, and educational solution to monitor weather patterns to predict a wildfire's Rate of Spread.

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Section: Visualization and Communication Of Resultsmentioning

confidence: 99%

Towards an Integrated Cyberinfrastructure for Scalable Data-driven Monitoring, Dynamic Prediction and Resilience of Wildfires

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Callafon

et al. 2015

Procedia Computer Science

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“…Several specialized implementations of physics have been investigated for various educational and training purposes, including bone dissection (Agus et al, 2003), wildfire spread (Sherman et al, 2007), and medical palpation (Ullrich and Kuhlen, 2012). Researchers have also investigated how to manipulate the perception of time within simulations (Schatzschneider et al, 2016).…”

Section: Scenario Fidelitymentioning

confidence: 99%

AFFECT: Altered-Fidelity Framework for Enhancing Cognition and Training

McMahan

Herrera

2016

Front. ICT

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In this paper, we present a new framework for analyzing and designing virtual reality (VR) techniques. This framework is based on two concepts -system fidelity (i.e., the degree with which real-world experiences are reproduced by a system) and memory (i.e., the formation and activation of perceptual, cognitive, and motor networks of neurons). The premise of the framework is to manipulate an aspect of system fidelity in order to assist a stage of memory. We call it the Altered-Fidelity Framework for Enhancing Cognition and Training (AFFECT). AFFECT provides nine categories of approaches to altering system fidelity to positively affect learning or training. These categories are based on the intersections of three aspects of system fidelity (interaction fidelity, scenario fidelity, and display fidelity) and three stages of memory (encoding, implicit retrieval, and explicit retrieval). In addition to discussing the details of our new framework, we show how AFFECT can be used as a tool for analyzing and categorizing VR techniques designed to facilitate learning or training. We also demonstrate how AFFECT can be used as a design space for creating new VR techniques intended for educational and training systems.

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“…VFire [1] is a wildfire simulation and visualization system, which provides an immersive virtual environment for users. It uses CAVE and Hydra as hardware, FARSITE as wildfire simulator, and OpenSceneGraph(OSG) as graphics engine [4]. Capaware [5][6] is an open source framework to develop 3D graphics applications.…”

Section: Introductionmentioning

confidence: 99%

Wildfire spread simulation and visualization in virtual environments

Yun

Chen

et al. 2011

Proceedings 2011 IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services

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Wildfire spread is a complicated phenomenon that affected by many factors, such as terrain, vegetation, and weather conditions. This paper presents a wildfire-spread simulation and visualization method. A simulation system was developed based on OSG(Open Scene Graph) and FARSITE (Fire Area Simulator). The system can visualize a realistic 3D wildfire scenario considering the influence factors. Wildfire is rendered by particle system, while LOD(Level Of Detail) and curve morphing technique are used to animate the flame and smoke under conditions of slope and wind. During the propagation of the procedural wildfire, the appearances of burned plants are changed automatically. The wildfire spread is visualized according to the calculations from the wildfire simulation engine. The users can not only manage the objects such as fire lines, fire-fighting vehicles and water-bombers, but also assess the damage. Keywords-Wildfire spread, 3D visualization, OSG, FARSITE, virtual environment I. INTRODUCTIONEvery year, wildfires cause huge damage around the world. In order to prevent and reduce the damage, scientists have developed various wildfire spread models for the wildfire behavior simulation and spread prediction. These fire models have been incorporated into many wildfire simulators, which can be divided into two types(vector-based and raster-based). Vector-based simulators which follow the idea of elliptical wave propagation[1] have accurate results, but they are complex and time-consuming in simulation. FARSITE[2] that developed by the Department of Agriculture of the United States is the most famous vector-based wildfire simulator. It incorporates a number of fire models including Rothermel's surface spread model and Van Wagner's crown fire model [3]. In comparison with vector-based simulators, the raster-based simulators which propagate fire through some set of rules across a uniform grid[1] implement easier and faster, but their results are less precise. FlamMap is a popular raster-based fire spread simulator, which assumes that the entire landscape is ignited and computes the spread characteristics for each cell of the terrain [3].The wildfire simulators advance in the fire behavior simulation and spread prediction, however, most of them visualize the wildfire simulation by two-dimensional(2D) images. The 2D images are difficult to realistically simulate the wildfire and the influence factors. Nowadays, the Virtual Reality(VR) technology can offer a better way to visualize

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VRFire: an Immersive Visualization Experience for Wildfire Spread Analysis

Cited by 13 publications

References 7 publications

Towards an Integrated Cyberinfrastructure for Scalable Data-driven Monitoring, Dynamic Prediction and Resilience of Wildfires

Towards an Integrated Cyberinfrastructure for Scalable Data-driven Monitoring, Dynamic Prediction and Resilience of Wildfires

AFFECT: Altered-Fidelity Framework for Enhancing Cognition and Training

Wildfire spread simulation and visualization in virtual environments

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