An extensible toolbox for modeling nature-society interactions

Modeling interactions between social and natural systems is a hard task. It involves collecting data, building up a conceptual approach, implementing, calibrating, simulating, validating, and possibly repeating these steps again and again. There are different conceptual approaches proposed in the literature to tackle this problem. However, for complex problems it is better to combine different approaches, giving rise to a need for flexible and extensible frameworks for modeling nature-society interactions. In this paper we present TerraME, an open source toolbox that supports multi-paradigm and multi-scale modeling of coupled human-environmental systems. It enables models that combine agent-based, cellular automata, system dynamics, and discrete event simulation paradigms. TerraME has a GIS interface for managing real-world geospatial data and uses Lua, an expressive scripting language. TerraME is a toolbox for modeling and simulation of nature-society interactions.Novel abstractions and services support multiscale spatiotemporal modeling.It allows the combined use of several paradigms for model implementation.It provides an extensible high-level modeling language.GIS integration supports real-world case studies.

[1]  Robert Muetzelfeldt,et al.  The Simile visual modelling environment , 2003 .

[2]  Marco A. Casanova,et al.  TerraLib: An Open Source GIS Library for Large-Scale Environmental and Socio-Economic Applications , 2008 .

[3]  M. B. Beck,et al.  Accounting for structural error and uncertainty in a model: An approach based on model parameters as stochastic processes , 2012, Environ. Model. Softw..

[4]  Nicholas R. Jennings,et al.  Intelligent agents: theory and practice , 1995, The Knowledge Engineering Review.

[5]  Bjarne Stroustrup,et al.  The Design and Evolution of C , 1994 .

[6]  Derek Karssenberg,et al.  Integrating dynamic environmental models in GIS: The development of a Dynamic Modelling language , 1996, Trans. GIS.

[7]  Michael Batty,et al.  A Generic Framework for Computational Spatial Modelling , 2012 .

[8]  Anthony J. Jakeman,et al.  Ten iterative steps in development and evaluation of environmental models , 2006, Environ. Model. Softw..

[9]  André Faaij,et al.  Spatio-temporal uncertainty in Spatial Decision Support Systems: A case study of changing land availability for bioenergy crops in Mozambique , 2012, Comput. Environ. Urban Syst..

[10]  R. Costanza.  MODEL GOODNESS OF FIT: A MULTIPLE RESOLUTION PROCEDURE , 1989 .

[11]  Derek Karssenberg,et al.  The PCRaster Software and Course Materials for Teaching Numerical Modelling in the Environmental Sciences , 2001, Trans. GIS.

[12]  M. Janssen,et al.  Multi-Agent Systems for the Simulation of Land-Use and Land-Cover Change: A Review , 2003 .

[13]  Peter Salamon,et al.  A software framework for construction of process-based stochastic spatio-temporal models and data assimilation , 2010, Environ. Model. Softw..

[14]  Guy Engelen,et al.  Cellular Automata as the Basis of Integrated Dynamic Regional Modelling , 1997 .

[15]  Jim Gray,et al.  The Transaction Concept: Virtues and Limitations (Invited Paper) , 1981, VLDB.

[16]  Derek Karssenberg,et al.  Dynamic environmental modelling in GIS: 1. Modelling in three spatial dimensions , 2005, Int. J. Geogr. Inf. Sci..

[17]  Jim Gray,et al.  The Transaction Concept: Virtues and Limitations (Invited Paper) , 1981, VLDB.

[18]  N Roberts,et al.  Introduction to Computer Simulation—A System Dynamics Modeling Approach , 1994 .

[19]  B. P. Ziegler,et al.  Theory of Modeling and Simulation , 1976 .

[20]  P. Heuberger,et al.  Calibration of process-oriented models , 1995 .

[21]  J. Forrester.  Industrial Dynamics , 1997 .

[22]  John von Neumann,et al.  Theory Of Self Reproducing Automata , 1967 .

[23]  Robert L. Eberlein,et al.  Understanding models with Vensim , 1992 .

[24]  Roberto Ierusalimschy,et al.  Lua—An Extensible Extension Language , 1996, Softw. Pract. Exp..

[25]  Erwan Bocher,et al.  An overview on current free and open source desktop GIS developments , 2009, Int. J. Geogr. Inf. Sci..

[26]  C. Tomlin.  Geographic information systems and cartographic modeling , 1990 .

[27]  Uri Wilensky,et al.  NetLogo: A simple environment for modeling complexity , 2014 .

[28]  R. Pontius,et al.  Death to Kappa: birth of quantity disagreement and allocation disagreement for accuracy assessment , 2011 .

[29]  Andrew Crooks,et al.  The Integration of Agent-Based Modelling and Geographical Information for Geospatial Simulation , 2012 .

[30]  Keith Beven,et al.  The future of distributed models: model calibration and uncertainty prediction. , 1992 .

[31]  Ronald R Rindfuss,et al.  Developing a science of land change: challenges and methodological issues. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[32]  Gordon Weller,et al.  Environmental social science: human–environment interactions and sustainability , 2012 .

[33]  Michael J. North,et al.  Experiences creating three implementations of the repast agent modeling toolkit , 2006, TOMC.

[34]  Roberto Ierusalimschy,et al.  Lua—An Extensible Extension Language , 1996 .

[35]  Jean-Baptiste Filippi,et al.  JDEVS: an implementation of a DEVS based formal framework for environmental modelling , 2004, Environ. Model. Softw..