Santos L.B.L., Negri R.G., de Carvalho T.J. (Eds.) Towards Mathematics, Computers and Environment: A Disasters Perspective

Springer, 2019. — 270 p. — ISBN: 978-3-030-21204-9.With relevant, timely topics, this book gathers carefully selected, peer-reviewed scientific works and offers a glimpse of the state-of-the-art in disaster prevention research, with an emphasis on challenges in Latin America. Topics include studies on surface frost, an extreme meteorological event that occasionally affects parts of Argentina, Bolivia, Peru, and southern Brazil, with serious impacts on local economies; near-ground pollution concentration, which affects many industrial, overpopulated cities within Latin America; disaster risk reduction and management, which are represented by mathematical models designed to assess the potential impact of failures in complex networks; and the intricate dynamics of international armed conflicts, which can be modeled with the help of stochastic theory. The book offers a valuable resource for professors, researchers, and students from both mathematical and environmental sciences, civil defense coordinators, policymakers, and stakeholders.An Overview of the El Niño, La Niña, and the Southern Oscillation Phenomena: Theory, Observations, and Modeling Links
Observation, Theory, and Numerical Modeling: Atmospheric Teleconnections Leading to Generalized Frosts over Southeast South America
Balances in the Atmosphere and Ocean: Implications for Forecasting and Reliability
Pollutant Dispersion Modeling via Mathematical Homogenization and Integral Transform-Based Multilayer Methods
Data Mining Approaches to the Real-Time Monitoring and Early Warning of Convective Weather Using Lightning Data
Methodological Proposal for the Prediction of Hydrological Responses to Land-Uses and Land-Cover Changes in a Brazilian Watershed
Computational Modeling and Simulation of Surface Waterflood in Mountainous Urban Watersheds with the MOHID Platform: Case Study Nova Friburgo, Brazil
Applied Time Series — Natural Disasters Perspective of Use: Landslide and Flood
Bayesian Analysis of the Disaster Damage in Brazil
About Interfaces Between Machine Learning, Complex Networks, Survivability Analysis, and Disaster Risk Reduction
Digital Humanities and Big Microdata: New Approaches for Demographic Research
Modeling Social and Geopolitical Disasters as Extreme Events: A Case Study Considering the Complex Dynamics of International Armed Conflicts