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This book provides a short, hands-on introduction to the science of complexity using simple computational models of natural complex systems-with models and exercises drawn from physics, chemistry, geology, and biology. By working through the models and engaging in additional computational explorations suggested at the end of each chapter, readers very quickly develop an understanding of how complex structures and behaviors can emerge in natural phenomena as diverse as avalanches, forest fires, earthquakes, chemical reactions, animal flocks, and epidemic diseases.Natural Complexity provides the necessary topical background, complete source codes in Python, and detailed explanations for all computational models. Ideal for undergraduates, beginning graduate students, and researchers in the physical and natural sciences, this unique handbook requires no advanced mathematical knowledge or programming skills and is suitable for self-learners with a working knowledge of precalculus and high-school physics.Self-contained and accessible, Natural Complexity enables readers to identify and quantify common underlying structural and dynamical patterns shared by the various systems and phenomena it examines, so that they can form their own answers to the questions of what natural complexity is and how it arises.
Complexity (Philosophy) --- Physics --- Computational complexity. --- Complexity, Computational --- Electronic data processing --- Machine theory --- Philosophy --- Emergence (Philosophy) --- Methodology. --- Burridge-Knopoff stick-slip model. --- Gutenberg-Richter law. --- Johannes Kepler. --- Olami-Feder-Christensen model. --- Python code. --- accretion. --- active flockers. --- agents. --- automobile traffic. --- avalanches. --- cells. --- cellular automata. --- chaos. --- clusters. --- complex behavior. --- complex structure. --- complex system. --- complexity. --- computational model. --- computer program. --- contagious diseases. --- criticality. --- diffusion-limited aggregation. --- earthquake forecasting. --- earthquakes. --- emergence. --- emergent behavior. --- emergent structure. --- epidemic spread. --- epidemic surges. --- excitable system. --- flocking. --- forest fires. --- fractal clusters. --- fractal geometry. --- growth. --- hodgepodge machine. --- infection rate. --- iterated growth. --- lattice. --- lichens. --- natural complex system. --- natural complexity. --- natural order. --- natural phenomena. --- nature. --- open dissipative system. --- panic. --- passive flockers. --- pattern formation. --- percolation threshold. --- percolation. --- phase transition. --- planetary motion. --- power-law. --- random walk. --- randomness. --- repulsion. --- rule-based growth. --- sandpile. --- scale invariance. --- segregation. --- self-organization. --- self-organized criticality. --- self-propulsion. --- self-similarity. --- simple rules. --- small-world network. --- solar flares. --- spaghetti. --- spatiotemporal pattern. --- spiral. --- tagging algorithm. --- traffic jams. --- waves. --- wildfire management.
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Wildfire risk can be perceived as the combination of wildfire hazards (often described by likelihood and intensity) with the susceptibility of people, property, or other valued resources to that hazard. Reflecting the seriousness of wildfire risk to communities around the world, substantial resources are devoted to assessing wildfire hazards and risks. Wildfire hazard and risk assessments are conducted at a wide range of scales, from localized to nationwide, and are often intended to communicate and support decision making about risks, including the prioritization of scarce resources. Improvements in the underlying science of wildfire hazard and risk assessment and in the development, communication, and application of these assessments support effective decisions made on all aspects of societal adaptations to wildfire, including decisions about the prevention, mitigation, and suppression of wildfire risks. To support such efforts, this Special Issue of the journal Fire compiles articles on the understanding, modeling, and addressing of wildfire risks to homes, water resources, firefighters, and landscapes.
wildfire risk --- object-oriented image analysis --- Sentinel-2 --- fire behavior --- flammap --- wildfire management --- water supply --- erosion --- wildfire containment --- Potential fire Operational Delineations --- Monte Carlo simulation --- transmission risk --- WUI --- fire --- defensible space --- prescribed fire --- community vulnerability --- fire suppression costs --- Zillow --- wildfire --- predictive modeling --- fire spread model --- Monte Carlo --- spatial modeling --- area difference index --- statistics --- precision --- recall --- principal components analysis --- risk assessment --- structure loss --- wildland–urban interface --- mitigation --- mapping --- land use --- disaster --- fire spread models --- surrogate modeling --- sensitivity analysis --- global sensitivity analysis --- colour coding --- communication --- forest fire --- ordinal categorization --- palette --- risk --- firefighter safety --- safe separation distance --- safety zones --- LCES --- Google Earth Engine --- lidar --- LANDFIRE --- Landsat --- GEDI --- parcel-level risk --- post-fire analysis --- risk mitigation --- rapid assessment --- natural hazards --- fuels --- fire hazard --- remote sensing --- LiDAR --- Sentinel --- modeling --- simulation
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Wildfire risk can be perceived as the combination of wildfire hazards (often described by likelihood and intensity) with the susceptibility of people, property, or other valued resources to that hazard. Reflecting the seriousness of wildfire risk to communities around the world, substantial resources are devoted to assessing wildfire hazards and risks. Wildfire hazard and risk assessments are conducted at a wide range of scales, from localized to nationwide, and are often intended to communicate and support decision making about risks, including the prioritization of scarce resources. Improvements in the underlying science of wildfire hazard and risk assessment and in the development, communication, and application of these assessments support effective decisions made on all aspects of societal adaptations to wildfire, including decisions about the prevention, mitigation, and suppression of wildfire risks. To support such efforts, this Special Issue of the journal Fire compiles articles on the understanding, modeling, and addressing of wildfire risks to homes, water resources, firefighters, and landscapes.
Research & information: general --- Biology, life sciences --- Forestry & related industries --- wildfire risk --- object-oriented image analysis --- Sentinel-2 --- fire behavior --- flammap --- wildfire management --- water supply --- erosion --- wildfire containment --- Potential fire Operational Delineations --- Monte Carlo simulation --- transmission risk --- WUI --- fire --- defensible space --- prescribed fire --- community vulnerability --- fire suppression costs --- Zillow --- wildfire --- predictive modeling --- fire spread model --- Monte Carlo --- spatial modeling --- area difference index --- statistics --- precision --- recall --- principal components analysis --- risk assessment --- structure loss --- wildland–urban interface --- mitigation --- mapping --- land use --- disaster --- fire spread models --- surrogate modeling --- sensitivity analysis --- global sensitivity analysis --- colour coding --- communication --- forest fire --- ordinal categorization --- palette --- risk --- firefighter safety --- safe separation distance --- safety zones --- LCES --- Google Earth Engine --- lidar --- LANDFIRE --- Landsat --- GEDI --- parcel-level risk --- post-fire analysis --- risk mitigation --- rapid assessment --- natural hazards --- fuels --- fire hazard --- remote sensing --- LiDAR --- Sentinel --- modeling --- simulation
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