Modelling transitions in sealed surface cover fraction with Quantitative State Cellular Automata

Autor: Frederik Priem, Frank Canters
Přispěvatelé: Brussels Centre for Urban Studies, Earth System Sciences, Geography, Cartography and Geographical Information Science, Faculty of Sciences and Bioengineering Sciences
Rok vydání: 2021
Předmět:
DYNAMICS
Public Administration
Computer science
sealed surfaces
Environmental Studies
SIMULATING URBAN-GROWTH
0211 other engineering and technologies
Social Sciences
Logistic regression
Support Vector Regression
02 engineering and technology
010501 environmental sciences
01 natural sciences
CALIBRATION
Geography
Ecology
cellular automata
021107 urban & regional planning
LAND-USE CHANGE
EXPANSION
Mutual information
LOGISTIC-REGRESSION
Cellular automaton
Geography
Physical
SUPPORT VECTOR MACHINES
Physical Sciences
Sealed surfaces
Life Sciences & Biomedicine
Algorithm
Environmental Sciences & Ecology
Cellular Automata
Regional & Urban Planning
Management
Monitoring
Policy and Law
Land cover change
Measure (mathematics)
VALIDATION
Component (UML)
Urban
0105 earth and related environmental sciences
Nature and Landscape Conservation
Science & Technology
logistic regression
SPRAWL
Urban Studies
Support vector machine
Support vector regression
Physical Geography
Cover (topology)
DENSITY
Spatial ecology
State (computer science)
urban
Zdroj: Landscape and Urban Planning. 211:104081
ISSN: 0169-2046
DOI: 10.1016/j.landurbplan.2021.104081
Popis: Cellular Automata (CA) applications simulating urban processes generally employ discrete land-use classes to characterise the physical environment. Yet there is an increasing demand for urban land cover models simulating quantitative change at the sub-cell level. The proposed Quantitative State Cellular Automata model (QCA) addresses this issue by relaxing part of the CA definition and considering real-valued quantitative cell states reflecting a physically meaningful measure. QCA entails two components of change: transition potential and quantity of change. The potential component addresses the likelihood of any change occurring in a cell, whereas the quantity component estimates the magnitude of change. The QCA concept is illustrated for Sealed Surface Density (SSD) transitions in Brussels and part of Flanders (Belgium). A Mutual Information (MI) approach is used to define the neighbourhood interaction framework. The QCA model is respectively calibrated and validated using Landsat-derived 1987–2001 and 2001–2013 SSD change on 30 m resolution. The results show that QCA successfully emulates spatial patterns of urban development, and significantly outperforms a random model in terms of quantitative and spatial distribution of SSD change. Further improvements can be achieved by explicitly integrating socio-economic information in the proposed workflow.
Databáze: OpenAIRE
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