Dynamic Wildfire Navigation System
AbstractWildfire, a natural part of many ecosystems, has also resulted in significant disasters impacting ecology and human life in Australia. This study proposes a prototype of fire propagation prediction as an extension of preceding research; this system is called “Cloud computing based bushfire prediction”, the computational performance of which is expected to be about twice that of the traditional client-server (CS) model. As the first step in the modelling approach, this prototype focuses on the prediction of fire propagation. The direction of fire is limited in regular grid approaches, such as cellular automata, due to the shape of the uniformed grid, while irregular grids are freed from this constraint. In this prototype, fire propagation is computed from a centroid regardless of grid shape to remove the above constraint. Additionally, the prototype employs existing fire indices, including the Grassland Fire Danger Index (GFDI), Forest Fire Danger Index (FFDI) and Button Grass Moorland Fire Index (BGML). A number of parameters, such as Digital Elevation Model (DEM) and forecast weather data, are prepared for use in the calculation of the indices above. The fire study area is located around Lake Mackenzie in the central north of Tasmania where a fire burnt approximately 247.11
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Ozaki, M.; Aryal, J.; Fox-Hughes, P. Dynamic Wildfire Navigation System. ISPRS Int. J. Geo-Inf. 2019, 8, 194.
Ozaki M, Aryal J, Fox-Hughes P. Dynamic Wildfire Navigation System. ISPRS International Journal of Geo-Information. 2019; 8(4):194.Chicago/Turabian Style
Ozaki, Mitsuhiro; Aryal, Jagannath; Fox-Hughes, Paul. 2019. "Dynamic Wildfire Navigation System." ISPRS Int. J. Geo-Inf. 8, no. 4: 194.
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