Adapting Map Resolution to Accomplish Execution Time Constraints in Wind Field Calculation
Author(s) -
Gemma Calbo Sanjuan,
Tomàs Margalef,
Ana Cortés
Publication year - 2015
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2015.05.418
Subject(s) - computer science , field (mathematics) , digital elevation model , propagation of uncertainty , resolution (logic) , wind speed , data mining , real time computing , artificial intelligence , remote sensing , meteorology , algorithm , physics , mathematics , pure mathematics , geology
Forest fire propagation prediction is a key point to fight against such hazards. Several models and simulators have been developed to predict forest fire propagation. These models require input parameters such as digital elevation map, vegetation map, and other parameters describing the vegetation and meteorological conditions. Coupling wind field model and forest fire propagation model improves accuracy prediction, but increases significantly prediction time. This fact is critical since propagation prediction must be provided in advance to allow the control centers to manage firefighters in the best possible way. This work analyses WindNinja execution time, describes a WindNinja parallelisation based on map partitioning, determines the limitations of such methodology for large maps and presents an improvement based on adapting map resolution to accomplish execution time limitations
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