Towards Mathematics, Computers and Environment: A Disasters Perspective

1. Front Matter

   Pages i-xix

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2. An Overview of the El Niño, La Niña, and the Southern Oscillation Phenomena: Theory, Observations, and Modeling Links

   • Léo Siqueira, Enver Ramírez, Rosio Camayo

   Pages 1-18

3. Observation, Theory, and Numerical Modeling: Atmospheric Teleconnections Leading to Generalized Frosts over Southeast South America

   • Gabriela V. Müller, Guillermo Berri, Marilia de Abreu Gregorio

   Pages 19-36

4. Balances in the Atmosphere and Ocean: Implications for Forecasting and Reliability

   • Enver Ramírez, Léo Siqueira, Rosio Camayo

   Pages 37-58

5. Pollutant Dispersion Modeling via Mathematical Homogenization and Integral Transform-Based Multilayer Methods

   • Camila P. da Costa, Leslie D. Pérez-Fernández, Julián Bravo-Castillero

   Pages 59-82

6. Data Mining Approaches to the Real-Time Monitoring and Early Warning of Convective Weather Using Lightning Data

   • Stephan Stephany, Cesar Strauss, Alan James Peixoto Calheiros, Glauston Roberto Teixeira de Lima, João Victor Cal Garcia, Alex Sandro Aguiar Pessoa

   Pages 83-101

7. Methodological Proposal for the Prediction of Hydrological Responses to Land-Uses and Land-Cover Changes in a Brazilian Watershed

   • Lidiane dos Santos Lima, Paulo Cesar Colonna Rosman, Julia Celia Mercedes Strauch, Nelson Ferreira Fernandes, Letícia de Carvalho Giannella

   Pages 103-124

8. Computational Modeling and Simulation of Surface Waterflood in Mountainous Urban Watersheds with the MOHID Platform: Case Study Nova Friburgo, Brazil

   • Wagner R. Telles, Diego N. Brandão, Jader Lugon Jr., Pedro P. G. W. Rodrigues, Antônio J. Silva Neto

   Pages 125-143

9. Applied Time Series—Natural Disasters Perspective of Use: Landslide and Flood

   • Alessandra C. Corsi, Filipe A. M. Falcetta, Marcela P. P. Guimarães, Eduardo S. de Macedo

   Pages 145-162

10. Bayesian Analysis of the Disaster Damage in Brazil

    • Camila Bertini Martins, Viviana Aguilar Muñoz, André Yoshizumi Gomes, Ricardo Manhães Savii, Carolina Locatelli Colla

    Pages 163-183

11. About Interfaces Between Machine Learning, Complex Networks, Survivability Analysis, and Disaster Risk Reduction

    • Leonardo Bacelar Lima Santos, Luciana R. Londe, Tiago José de Carvalho, Daniel S. Menasché, Didier A. Vega-Oliveros

    Pages 185-215

12. Digital Humanities and Big Microdata: New Approaches for Demographic Research

    • Pier Francesco De Maria, Leonardo Tomazeli Duarte, Álvaro de Oliveira D’Antona, Cristiano Torezzan

    Pages 217-231

13. Modeling Social and Geopolitical Disasters as Extreme Events: A Case Study Considering the Complex Dynamics of International Armed Conflicts

    • Reinaldo Roberto Rosa, Joshi Neelakshi, Gabriel Augusto L. L. Pinheiro, Paulo Henrique Barchi, Elcio Hideiti Shiguemori

    Pages 233-254

14. Back Matter

    Pages 255-258

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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.

• applied mathematics
• inverse problems
• geological problems
• natural disasters
• natural hazards
• latin america
• partial differential equations

“The book provides a good selection of valuable papers in the area of environmental research. The main research methods used to study complex and multiscale systems are clearly presented. The target audience includes students of sustainable development, researchers, and even science enthusiasts.” (Alexander Tzanov, Computing Reviews, February 16, 2021)

• National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN), São José dos Campos, Brazil

  Leonardo Bacelar Lima Santos

• Institute of Science and Technology, São Paulo State University (UNESP), São José dos Campos, Brazil

  Rogério Galante Negri

• Department of Informatics, Federal Institute of São Paulo (IFSP), Campinas, Brazil

  Tiago José de Carvalho

Leonardo B. L. Santos is an adjunct researcher at the National Center for Early Warning of Natural Disasters (Cemaden), Brazil. He holds a PhD in Computing from the National Institute of Space Research (INPE, 2014) and a Bachelor’s degree in Physics from the Federal University of Bahia (UFBA, 2009). He received an honorable mention for a talk at the Institute for Pure and Applied Mathematics (IMPA, 2008) and twice as supervisor of best research (INPE, 2015 and 2016), having published more than 25 papers in journals and book chapters. He is the principal investigator of the Brazilian Society of Computational and Applied Mathematics (SBMAC) research group “Mathematics and Natural Disasters.”


Rogério G. Negri completed his Major’s degree in Mathematics (2006) at the São Paulo State University (UNESP), and his Master (2009) and PhD(2013) in Applied Computation at the Brazilian National Institute for Space Research (INPE), Brazil. He has experience in pattern recognition, radar image processing, geostatistics, and GIS. His recent research focuses on the development of image classification, segmentation, and change detection algorithms with applications on remote sensing data. He is currently a professor at Institute of Science and Technology, UNESP, Brazil.



Tiago Carvalho received his Bachelor’s degree in Computer Science from the Federal University of Juiz de Fora (UFJF), Brazil (2008). He holds a Master (2010) and a PhD (2014) degree, both in Computer Science, from the University of Campinas (Unicamp), Brazil. During his PhD he developed digital forensics methods for detecting image splicing in cooperation with some leading international research teams, including those led by Dr Hany Farid (Dartmouth College, USA) and by Dr Elli Angelopoulo (University of Erlangen-Nuremberg, Germany).

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