Sunday, 19 October 2008

Dinamica—a stochastic cellular automata model designed to simulate the landscape dynamics in an Amazonian colonization frontier

Britaldo Silveira Soares-FilhoCorresponding Author Contact Information, E-mail The Corresponding Author, a, Gustavo Coutinho CerqueiraE-mail The Corresponding Author, b and Cássio Lopes PennachinE-mail The Corresponding Author, c

a Department of Cartography, Federal University of Minas Gerais, Av. Antônio Carlos, Belo Horizonte 6627-31270-900, Minas Gerais, Brazil b Remote Sensing Center, Federal University of Minas Gerais, Av. Antônio Carlos, Belo Horizonte 6627-31270-900, Minas Gerais, Brazil c Intelligenesis do Brasil Ltda, Av. Brasil 1438, 1505, Belo Horizonte 30140-003, Brazil

Received 2 November 2000;
revised 28 November 2001;
accepted 21 December 2001.
Available online 18 April 2002.


Abstract

Image , a spatially explicit simulation model of landscape dynamics has been developed. Image is a cellular automata model that presents multi-scale vicinity-based transitional functions, incorporation of spatial feedback approach to a stochastic multi-step simulation engine, and the application of logistic regression to calculate the spatial dynamic transition probabilities. This model was initially conceived for the simulation of Amazonian landscape dynamics, particularly the landscapes evolved in areas occupied by small farms

For testing its performance, the model was used to simulate spatial patterns of land-use and land-cover changes produced by the Amazonian colonists in clearing the forest, cultivating the land, and eventually abandoning it for vegetation succession. The study area is located in an Amazonian colonization frontier in the north of Mato Grosso state, Brazil. The model was run for two sub-areas of colonization projects, using an 8-year time span, from 1986 to 1994. The simulated maps were compared with land-use and land-cover maps, obtained from digital classification of remote sensing images, using the multiple resolution fitting procedure and a set of landscape structure measures, including fractal dimension, contagion index, and the number of patches for each type of land-use and land-cover class. The results from the validation methods for the two areas showed a good performance of the model, indicating that it can be used for replicating the spatial patterns created by landscape dynamics in Amazonian colonization regions occupied by small farms. Possible applications of Image include the evaluation of landscape fragmentation produced by different architectures of colonization projects and the prediction of a region's spatial pattern evolution according to various dynamic phases.

Author Keywords: Land-use and land-cover change; Cellular automata; Simulation model; Image ; Amazonian landscape dynamics

Article Outline

1. Introduction
2. Methods
2.1. Model structure
2.1.1. The model data
2.1.2. The calculation of the dynamic variables
2.1.3. The calculation of the transition rates and quantities
2.1.4. The calculation of the spatial transition probabilities
2.1.5. The transitional functions
2.1.6. The Expander function
2.1.7. The Patcher function
2.1.8. The Image software
2.2. Test performance
2.2.1. The test site and its land change conceptual model
2.2.2. The time span for running the model
2.2.3. The input maps
2.3. Model calibration
3. Results and discussion
4. Conclusions
Acknowledgements
References


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Using cellular automata for integrated modelling of socio-environmental systems

JournalEnvironmental Monitoring and Assessment
PublisherSpringer Netherlands
ISSN0167-6369 (Print) 1573-2959 (Online)
IssueVolume 34, Number 2 / January, 1995
DOI10.1007/BF00546036
Pages203-214
Subject CollectionEarth and Environmental Science
SpringerLink DateTuesday, December 07, 2004

Guy Engelen1, Roger White2, Inge Uljee1 and Paul Drazan1

(1) RIKS Research Institute for Knowledge Systems, P.O. Box 463, 6200 AL Maastricht, The Netherlands
(2) Memorial University of Newfoundland, A1B 3X9 St. John's, NF, Canada
Abstract Cellular automata provide the key to a dynamic modelling and simulation framework that integrates socio-economic with environmental models, and that operates at both micro and macro geographical scales.
An application to the problem of forecasting the effect of climate change on a small island state suggests that such modelling techniques could help planners and policy makers design more effective policies — policies better tuned both to specific local needs and to overall socio-economic and environmental constraints.
Paper presented at the ldquoWorkshop on GIS Applications in Coastal Zone Management Of Small Island Statesrdquo, Barbados, April 20–22, 1994. RIKS publication 905000/94100, April 1994.


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Modelling dynamic spatial processes: simulation of urban future scenarios through cellular automatanext term

José I. BarredoCorresponding Author Contact Information, E-mail The Corresponding Author, Marjo Kasanko, Niall McCormick and Carlo Lavalle

European Commission, Joint Research Centre, Institute for Environment and Sustainability, CCR-TP 261, 21020, Ispra (VA), Italy

Received 15 October 2002;
accepted 22 October 2002. ;
Available online 2 December 2002.

Abstract

One of the most potentially useful applications of previous termcellular automatanext term (CA) from the point of view of spatial planning is their use in simulations of urban growth at local and regional level. Urban simulations are of particular interest to urban and regional planners since the future impacts of actions and policies are critically important. However, urban growth processes are usually difficult to simulate.

This paper addresses from a theoretical point of view the question of why to use CA for urban scenario generation. In the first part of the paper, complexity as well as other properties of digital cities are analysed. The role of the urban land use allocation factors is also studied in order to propose a bottom-up approach which integrates the land use factors with the dynamic approach of the CA for modelling future urban land use scenarios.

The second part of the paper presents an application of an urban CA in the city of Dublin. A simulation for 30 years has been produced using a CA software prototype. The results of the model have been tested by means of the fractal dimension and the comparison matrix methods. The simulation results are realistic and relatively accurate confirming the effectiveness of the proposed urban CA approach.

Author Keywords: previous termCellular automatanext term; Land use dynamics; Urban and regional planning; Scenario simulation; previous termGISnext term



Article Outline

1. Introduction
1.1. Characteristics and factors of the urban land use dynamics
1.2. How urban land use factors work: an approach
2. Modelling dynamic spatial systems
2.1. A bottom-up approach for urban land use simulation
3. Methods
3.1. The cell space
3.2. The cell neighbourhood
3.3. The cell states
3.4. The neighbourhood effect
3.5. The transition rules
3.6. Land use demands
4. Results and discussion
4.1. Model results testing
4.1.1. Assessment of accuracy using the radial dimension
4.1.2. Assessment of accuracy using comparison matrices
5. Concluding remarks
Acknowledgements
References
Vitae



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Application of GIS and Web technologies for Danube waterway data management in Croatia

Application of GIS and Web technologies for Danube waterway data management in Croatia

Jadranka Pecar-IlicCorresponding Author Contact Information, a, E-mail The Corresponding Author and Ivica Ruzica

aDivision for Marine & Environmental Research of the Rudjer Boskovic Institute, Bijenicka 54, HR-10000 Zagreb, Croatia

Received 3 May 2006;
accepted 3 May 2006.
Available online 15 June 2006.


Abstract

The paper gives a general description of the Danube waterway data management in Croatia at both national and Pan-European levels. For these purposes, we initiated the development of a specialized geographic information system (GIS), the so-called River IS, which provides efficient waterway related data management for the Croatian part of the Danube River. In addition, Croatian activities in the Pan-European programme Consortium Operational Management Platform River Information Services (COMPRIS) and INTERREG project data warehouse for the Danube waterway (D4D) are described. Focusing on how to solve the major problems identified by “GIS Forum Danube” expert groups, we present our solutions for two important D4D project objectives. The first project objective concerns preparation of national GIS data of the participating countries in the world geodetic WGS84 coordinates as well as checking the transnational compatibility of GIS data. The second important project objective concerns the development of a commonly agreed catalogue of object types and their attributes necessary to describe waterway related data. For example, the conversion of the Croatian national geographic data into Inland ECDIS digital navigation maps is described.

Keywords: Danube waterway; Croatian part of the Danube River; Enviromatics; Environmental informatics; Geographic information system; GIS Forum Danube; COMPRIS; D4D project; Inland ECDIS; Object catalogue




Software availability


Name of software:
River IS; Croatian Inland ECDIS maps

Developer:
Division for Marine and Environmental Research

Contact address:
Rudjer Boskovic Institute, Bijenicka 54, HR-10000 Zagreb, Croatia

Tel.:
+ 385 1 4561140

Fax:
+ 385 1 4680117

E-mail:
pecar@irb.hr; ruzic@irb.hr

Hardware required (for users):
Intel Pentium IV with running Microsoft IE (>6.0)

Software required (for users):
Autodesk MapGuide Viewer (>6.0); Seven Cs AG & Co. KG Inland ECDIS Viewer

Program language:
Java and ASP

Availability and cost:
River IS – restricted (CRORIS project); Croatian Inland ECDIS maps – free from CRUP Web (http://www.crup.hr/eng/index.php)

Article Outline

Nomenclature
1. Introduction
1.1. Inland navigation and environmental protection
1.2. River information services
2. Danube waterway data management in Croatia
2.1. CRORIS project
2.2. Main functionalities of the River Information System (River IS)
3. Data warehouse for the Danube waterway – D4D project
4. Results of our activities in the D4D expert groups
4.1. Development of the inland ECDIS digital navigation map
4.2. Development of the object catalogue
5. Summary and conclusions
Acknowledgements
Glossary
References

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