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A High Performance Computing Framework for Continental-Scale Forest Fire Spread Prediction.

, , , , and . ICCS, volume 108 of Procedia Computer Science, page 1712-1721. Elsevier, (2017)

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Coupled Dynamic Data-Driven Framework for Forest Fire Spread Prediction., , and . DyDESS, volume 8964 of Lecture Notes in Computer Science, page 54-67. Springer, (2014)Wind Field Uncertainty in Forest Fire Propagation Prediction., , , and . ICCS, volume 29 of Procedia Computer Science, page 1535-1545. Elsevier, (2014)Coupling Wind Dynamics into a DDDAS Forest Fire Propagation Prediction System., , , and . ICCS, volume 9 of Procedia Computer Science, page 1110-1118. Elsevier, (2012)Effect of Wind Field Parallelization on Forest Fire Spread Prediction., , , and . ICCSA (4), volume 8582 of Lecture Notes in Computer Science, page 538-549. Springer, (2014)A High Performance Computing Framework for Continental-Scale Forest Fire Spread Prediction., , , , and . ICCS, volume 108 of Procedia Computer Science, page 1712-1721. Elsevier, (2017)Enhancing multi-model forest fire spread prediction by exploiting multi-core parallelism., , , and . J. Supercomput., 70 (2): 721-732 (2014)Determining map partitioning to accelerate wind field calculation., , , and . HPCS, page 96-103. IEEE, (2014)Coupling Diagnostic and Prognostic Models to a Dynamic Data Driven Forest Fire Spread Prediction System., , and . ICCS, volume 18 of Procedia Computer Science, page 1851-1860. Elsevier, (2013)A comprehensive methodology to predict forest res behavior using complementary models.. Autonomous University of Barcelona, Spain, (2014)