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You are in Geoinformatics - Creative Commons :: Introduction to Earth System Science Modelling :: Classes 2014

CST-317: Introduction to Earth System Modelling (INPE Course 2014)

Professors: Gilberto Câmara, Pedro R. Andrade

References

  • Modeling the Environment (2nd edition), Andrew Ford. Island Press, 2010.
  • Thinking in Systems, Donella Meadows, Chelsea Green Publishing, 2008.
  • Dynamic Modeling of Environmental Systems, Michael L. Deaton & James J. Winebrake. Springer, 2000.
  • Simulation for the Social Scientist, Nigel Gilbert & Klaus Troitzsch, Open University Press, 2005.
  • Complex Adaptive Systems: An Introduction to Computational Models of Social Life, John H. Miller & Scott Page, Princeton University Press, 2007.
  • Cities and Complexity. Michael Batty. MIT Press, 2007.

Software Description

The models described in this course will be developed using TerraME. TerraME is an extension of the Lua language. Some useful documents about TerraME:

Students should read the TerraME EMS paper first, to get a sense of the language. Then they should read the Lua papers, to learn about programming in Lua.

Please also install the terrame_addons and the viewer package.


Classes

Additional Reading

Papers for Final Projects

The final project consists of an implementation and discussion of one of the following papers.

H. Balzter, P. W. Braun, W. Köhler (1998) Cellular automata models for vegetation dynamics. Ecological Modelling 107(2-3):113-125
J. Silvertown, S. Holtier, J. Johnson and P. Dale (1992) Cellular Automaton Models of Interspecific Competition for Space-The Effect of Pattern on Process. Journal of Ecology, 80(3):527-533
S. G. Berjak, J. W. Hearne (2002) An improved cellular automaton model for simulating fire in a spatially heterogeneous Savanna system. Ecological Modelling 148(2):133–15
Marcos Sanches, Diego Jatobá D. L. Dunkerley (1997) Banded vegetation: development under uniform rainfall from a simple cellular automaton model. Plant Ecology 129(2):103-111
D.L Dunkerley (1997) Banded vegetation: survival under drought and grazing pressure based on a simple cellular automaton model. Journal of Arid Environments 35(3):419–428
G.Ch Sirakoulis, I. Karafyllidis, A. Thanailakis (2000) A cellular automaton model for the effects of population movement and vaccination on epidemic propagation. Ecological Modelling 133(3): 209–223
C. Beauchemina, J. Samuelb, J. Tuszynskia (2005) A simple cellular automaton model for influenza A viral infections. Journal of Theoretical Biology 232(2) 223–234
Phillip Edson, Raquel Melo Medeiros, L. C., Castilho, C. A. R., Braga, C., de Souza, W. V., Regis, L., Monteiro, A. M. V. (2011). Modeling the dynamic transmission of dengue fever: investigating disease persistence. PLOS neglected tropical diseases, 5(1), e942.
H. Nakanishi (1990) Cellular-automaton model of earthquakes with deterministic dynamics. Phys. Rev. A 41:7086–7089
Raquel Carvalho R. Toivonen, J. Onnela, J. Saramaki, J. Hyvonen, K. Kaski (2006) A model for social networks. Physica A: Statistical Mechanics and its Applications 371(2):851–860
Barros, J. Urban Growth in Latin American Cities. PhD thesis, CASA/UCL
Iane Cycles in Predator and Prey Populations, Chapter 20 of A. Ford, Modeling the Environment
Sex, Culture and Conflict in SugarScape. From J Epstein, R. Axtell, Growing Artificial Societies: Social Science from the Bottom Up. MIT Press, 1996.
Trade in SugarScape. From J Epstein, R. Axtell, Growing Artificial Societies: Social Science from the Bottom Up. MIT Press, 1996.
S Bergin (2012). Torsten Hägerstrand’s Spatial Innovation Diffusion Model. Available in CoMSES Computational Model Library.
S Heckbert (2013). MayaSim: An agent-based model of the ancient Maya social-ecological system. Available in CoMSES Computational Model Library.
R Axelrod (1997). “The dissemination of culture - A model with local convergence and global polarization.” Journal of Conflict Resolution 41: 203-226.Replicated in CoMSES Computational Model Library.
J Pepper and B Smuts (2000). The evolution of cooperation in an ecological context: an agent-based model. Replicated in CoMSES Computational Model Library.
K Kahn (2013) A model of the Spanish Flu Pandemic. Available in CoMSES Computational Model Library.
Schindler J (2012) A simple Multi-Agent System of the Tragedy Of the Commons. Available in CoMSES Computational Model Library.
A K Knittel, R Riolo and R Snow (2011). Development and evaluation of an agent-based model of sexual partnership. Adaptive Behavior (available at CoMSES Computational Model Library.
M Janssen and N.D. Rollins (2012). Evolution of cooperation in asymmetric commons dilemmas. Journal of Economic Behavior and Organization, 81: 220-229. Available in CoMSES Computational Model Library).
Marcio, Eduardo Axtell, Epstein, et al. (2002) Population Growth and Collapse in a Multi-Agent Model of the Kayenta Anasazi in Long House Valley. PNAS 99(3): 7275-7279. Replicated in M Janssen and available in CoMSES Computational Model Library.
S Bandini, F Celada, S Manzoni, G Vizzari (2007). Modelling the immune system: the case of situated cellular agents, Natural Computing, 6(1):19-32.
S. Yassemi, S. Dragićevića, M. Schmidt(2008), Design and implementation of an integrated GIS-based cellular automata model to characterize forest fire behaviour , Ecological Modelling, 210(1–2), 71–84
G.Ch Sirakoulis, I. Karafyllidis, A. Thanailakis (2000) A cellular automaton model for the effects of population movement and vaccination on epidemic propagation. Ecological Modelling 133(3): 209–223
S. Hoya White, A. Martín del Rey, G. Rodríguez Sánchez(2007), Modeling epidemics using cellular automata. Applied Mathematics and Computation, 186(1):193-202
F. Feitosa, A.M. Monteiro, Urban Conventions and Residential Location Choice. CAMUSS Conference (Cellular Automata Modeling forUrban and Spatial Systems 2012)
cst-317/classes2014.txt · Last modified: 2014/09/10 11:06 by gilberto