A Systematic Review and Bibliometric Analysis of Wildland Fire Behavior Modeling by João Silva, João Marques, Inês Gonçalves, Rui Brito, Senhorinha Teixeira, José Teixeira, Filipe Alvelos

“…Hence, in view of further improvements in wildfire modeling, increases in computational resources will allow upscaling of physical models, and technological advancements are being developed to provide near real-time predictive fire behavior modeling. …”
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Evaluation of sampling strategies to estimate crown biomass by Krishna P Poudel, Hailemariam Temesgen, Andrew N Gray

“…Crown biomass estimation is useful for different purposes including evaluating the economic feasibility of crown utilization for energy production or forest products, fuel load assessments and fire management strategies, and wildfire modeling. However, crown biomass is difficult to predict because of the variability within and among species and sites. …”
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Evaluation of sampling strategies to estimate crown biomass by Krishna P Poudel, Hailemariam Temesgen, Andrew N Gray

“…Crown biomass estimation is useful for different purposes including evaluating the economic feasibility of crown utilization for energy production or forest products, fuel load assessments and fire management strategies, and wildfire modeling. However, crown biomass is difficult to predict because of the variability within and among species and sites. …”
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Increased wildfire hazard along South-Central Chile under the RCP8.5 scenario as revealed by high-resolution modeling by Isabella Ciocca, Alfonso Fernández, Edilia Jaque, Flavio Justino, Vanúcia Shumacher, Alex Santos da Silva, Ariel Muñoz, Francisco de la Barrera

“…This paper evaluates wildfire hazard for the SCZCh, based on environmental susceptibility to wildfire occurrence, using numerical regional climate and wildfire modeling for the 2002–2005 historical period and for the mid and late 21st-century under the RCP8.5 climate change scenario. …”
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Improvement of human-induced wildfire occurrence modeling from a spatial variation of anthropogenic ignition factor in the CLM5 by Lei Cai, Wenwen Shi, Weiyu Shi, Fang Li, Vladimir A Alexeev, Alexander Shiklomanov, Ruowen Yang, Shucheng Tan

“…This study develops an approach to advance human-induced wildfire modeling by calibrating the parameter of human ignition count (HIC) in the fire module of the Community Land Model version 5. …”
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Stability and Optimal Control of Tree-Insect Model under Forest Fire Disturbance by Xiaoxiao Liu, Chunrui Zhang

“…The results show that for the tree–insect–wildfire model, there is a coexistence equilibrium in the system. …”
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Resilient Multipath Routing Protocol to Enable Hazardous event Monitoring with Wireless Sensor Network by B. Á. Üveges, M. Lőrincz, A. Oláh

“…To evaluate the routing protocol, we perform simulations utilizing a cellular automaton-based wildfire model as the spatial event and provide measurement results including delivery ratio, consumed energy, and protocol-specific metrics.…”
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Modelling the daily probability of wildfire occurrence in the contiguous United States by Theodore Keeping, Sandy P Harrison, I Colin Prentice

“…The ensemble performed well in predicting the mean geospatial patterns of fire occurrence, the interannual variability in the number of fires, and the regional variation in the seasonal cycle of wildfire. Model runs gave an area under the receiver operating characteristic curve (AUC) of 0.85–0.88, indicating good predictive power. …”
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A Coupled Wildfire-Emission and Dispersion Framework for Probabilistic PM_2.5 Estimation by David Melecio-Vázquez, Chris Lautenberger, Ho Hsieh, Michael Amodeo, Jeremy R. Porter, Bradley Wilson, Mariah Pope, Evelyn Shu, Valentin Waeselynck, Edward J. Kearns

“…We present a flexible modeling framework for emissions sourced from the First Street Foundation Wildfire Model (FSF-WFM) to provide a national map for near-surface smoke conditions exceeding the threshold for unhealthy concentrations of particulate matter at or less than 2.5 µm, or PM_2.5. …”
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HexFire: A Flexible and Accessible Wildfire Simulator by Nathan H. Schumaker, Sydney M. Watkins, Julie A. Heinrichs

“…As fire frequency and severity grow throughout the world, scientists working across a range of disciplines will increasingly need to incorporate wildfire models into their research. However, fire simulators tend to be highly complex, time-consuming to learn, and difficult to parameterize. …”
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Incorporating Anthropogenic Influences into Fire Probability Models: Effects of Human Activity and Climate Change on Fire Activity in California. by Michael L Mann, Enric Batllori, Max A Moritz, Eric K Waller, Peter Berck, Alan L Flint, Lorraine E Flint, Emmalee Dolfi

“…Although a number of statistical and process-based wildfire models exist for California, there is enormous uncertainty about the location and number of future fires, with previously published estimates of increases ranging from nine to fifty-three percent by the end of the century. …”
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Electrical Responses of <i>Pinus halepensis</i> Mill. as an Indicator of Wildfire Risk in Mediterranean Forests by Complementing Live Fuel Moisture by Rodolfo Zapata, Jose-Vicente Oliver-Villanueva, Lenin-Guillermo Lemus-Zúñiga, Miguel A. Mateo Pla, Jorge E. Luzuriaga

“…Thus, electrical responses could add more knowledge about the phenological state of the trees in dependence on stress climatic conditions, allowing integration of these variables in the preventive wildfire modelling and management.…”
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Modeling Post‐Wildfire Hydrologic Response: Review and Future Directions for Applications of Physically Based Distributed Simulation by Brian A. Ebel, Zachary M. Shephard, Michelle A. Walvoord, Sheila F. Murphy, Trevor F. Partridge, Kim S. Perkins

“…America, Africa, Asia) and ecohydrologic regions (arid or dry subhumid climates), (b) incorporating all four major streamflow generation mechanisms (infiltration excess, saturation excess, subsurface storm flow, and groundwater flow), (c) representing integrated vadose zone and saturated zone processes to better capture subsurface streamflow generation, (d) building new remotely sensed model parameterization methods for precipitation interception, infiltration, and overland flow that account for burn severity and recovery, (e) incorporating distributed state variables (e.g., soil moisture, groundwater levels) in model performance assessment, (f) designing model intercomparison studies, including field datasets specifically for post‐wildfire model development and validation, (g) linking mechanistic vegetation regrowth models with hydrologic models to improve simulation of process shifts as ecosystems recover, and (h) creating a new community modeling framework to integrate modeling advances across the wildfire science community.…”
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A Novel Approach for Predicting Large Wildfires Using Machine Learning towards Environmental Justice via Environmental Remote Sensing and Atmospheric Reanalysis Data across the Uni... by Nikita Agrawal, Peder V. Nelson, Russanne D. Low

“…Six machine learning classification models (Logistic Regression, Decision Tree, Random Forest, eXtreme Gradient Boosting, K-Nearest Neighbors, and Support Vector Machine) were created and tested on the resulting dataset to determine their accuracy in predicting large wildfires. Model validation tests and variable importance analysis were performed. …”
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Facing the Wildfire Spread Risk Challenge: Where Are We Now and Where Are We Going? by Jingjing Sun, Wenwen Qi, Yuandong Huang, Chong Xu, Wentao Yang

“…Finally, the article proposes several prospects for future research on wildfire spread: strengthening the dynamic monitoring of wildfires and utilizing comprehensive data from multiple sources, further exploring the differential effects of key factors on wildfire spread, investigating differences in driving factors, improving wildfire models in China, developing applicable software, and conducting accurate and scientific assessments of wildfire risks to protect ecological resources.…”
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RADAR-Vegetation Structural Perpendicular Index (R-VSPI) for the Quantification of Wildfire Impact and Post-Fire Vegetation Recovery by Aakash Chhabra, Christoph Rüdiger, Marta Yebra, Thomas Jagdhuber, James Hilton

“…The precise information on fuel characteristics is essential for wildfire modelling and management. Satellite remote sensing can provide accurate and timely measurements of fuel characteristics. …”
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Classification of Mediterranean Shrub Species from UAV Point Clouds by Juan Pedro Carbonell-Rivera, Jesús Torralba, Javier Estornell, Luis Ángel Ruiz, Pablo Crespo-Peremarch

“…This study investigated the use of UAV-based digital aerial photogrammetry (UAV-DAP) point clouds to classify tree and shrub species in Mediterranean forests, and this information is key for the correct generation of wildfire models. In July 2020, two test sites located in the Natural Park of Sierra Calderona (eastern Spain) were analysed, registering 1036 vegetation individuals as reference data, corresponding to 11 shrub and one tree species. …”
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Physics-Based Simulations of Flow and Fire Development Downstream of a Canopy by Gilbert Accary, Duncan Sutherland, Nicolas Frangieh, Khalid Moinuddin, Ibrahim Shamseddine, Sofiane Meradji, Dominique Morvan

“…The behavior of a grassland fire propagating downstream of a forest canopy has been simulated numerically using the fully physics-based wildfire model FIRESTAR3D. This configuration reproduces quite accurately the situation encountered when a wildfire spreads from a forest to an open grassland, as can be the case in a fuel break or a clearing, or during a prescribed burning operation. …”
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The Construction of Probabilistic Wildfire Risk Estimates for Individual Real Estate Parcels for the Contiguous United States by Edward J. Kearns, David Saah, Carrie R. Levine, Chris Lautenberger, Owen M. Doherty, Jeremy R. Porter, Michael Amodeo, Carl Rudeen, Kyle D. Woodward, Gary W. Johnson, Kel Markert, Evelyn Shu, Neil Freeman, Mark Bauer, Kelvin Lai, Ho Hsieh, Bradley Wilson, Beth McClenny, Andrea McMahon, Farrukh Chishtie

“…The methodology used by the First Street Foundation Wildfire Model (FSF-WFM) to compute estimates of the 30-year, climate-adjusted aggregate wildfire hazard for the contiguous United States at 30 m horizontal resolution is presented. …”
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