Land use change simulation and analysis using a vector cellular automata (CA) model
A case study of Ipswich City, Queensland, Australia
Dados Bibliográficos
| ID | 21247920 |
|---|---|
| Autores | Yi Lü (0000-0001-7614-6661, UNSW Sydney, autor correspondente), Shawn W Laffan (0000-0002-5996-0570, UNSW Sydney), Christopher Pettit (0000-0002-1328-9830, UNSW Sydney), Min Cao (0000-0002-4497-5841, Nanjing Normal University) |
| Ano | 2020 |
| Volume | 47 |
| Fascículo | 9 |
| Páginas | 1605-1621 |
| Data de publicação | 2020-11-01 |
| Peer Reviewed | Sim |
| Open Access | Sim |
| Tipo | ARTICLE |
| Periódico | Environment and Planning B Urban Analytics and City Science (JOURNAL) |
| Identificadores do periódico | ISSN: 2399-8083 • E-ISSN: 2399-8091 |
| Editora | SAGE Publications (PUBLISHER • US) |
| DOI | 10.1177/2399808319830971 |
| OpenAlex | W2920454119 |
| Idioma | EN |
| Citações recebidas | 14 |
| Referências citadas | 51 |
The loss of accuracy in vector-raster conversion has always been an issue for land use change models, particularly for raster based Cellular Automata models. Here we describe a vector-based cellular automata (CA) model that uses land parcels as the basic unit of analysis, and compare its results with a raster CA model. Transition rules are calibrated using an artificial neural network (ANN) and historical land use data. Using Ipswich City in Queensland, Australia as the study area, the simulation results show that the vector and raster CA models achieve 96.64% and 93.88% producer’s spatial accuracy, respectively. In addition, the vector CA model achieves a higher kappa coefficient and more consistent frequency of misclassification, while also having faster processing times. Consequently, the vector-based CA model can be applied to explore regulations of land use transformation in urban growth process, and provide a better understanding of likely urban growth to inform city planners
Algorithm · Automaton · Biology · Cellular automaton · Civil engineering · Land use · Land use, land-use change and forestry · Programming language · Raster graphics · Computer Science · Engineering · Land Use and Ecosystem Services · Urban Design and Spatial Analysis · Artificial Intelligence
Mapping the vertical city
Spatio-temporal modeling of parcel-level land-use changes using machine learning methods
The impact of heterogeneous accessibility to metro stations on land use changes in a bike-sharing context
Investigating the interactions between spatiotemporal land use/land cover dynamics and private land ownership
Modeling urban land-use changes using a landscape-driven patch-based cellular automaton (LP-CA)
Applicability and sensitivity analysis of vector cellular automata model for land cover change
Modeling multi-type urban landscape dynamics along the horizontal and vertical dimensions
An Innovative Proposal for Developing a Dynamic Urban Growth Model Through Adaptive Vector Cellular Automata
Grid, Patch, or Multi‐Scale Integration? A Comparative Analysis for Cellular Automata‐Based Urban Growth Simulations
Urban land use transitions
Environment and Planning B
Toward volumetric urbanism
Modeling land-use change using partitioned vector cellular automata while considering urban spatial structure
A Comprehensive Review on the Development and Evolution of Urban Growth Models and Current Challenges
A Self-Modifying Cellular Automaton Model of Historical Urbanization in the San Francisco Bay Area
A future land use simulation model (FLUS) for simulating multiple land use scenarios by coupling human and natural effects
Delineating multi-scenario urban growth boundaries with a CA-based FLUS model and morphological method
The Use of Constrained Cellular Automata for High-Resolution Modelling of Urban Land-Use Dynamics
Neural-network-based cellular automata for simulating multiple land use changes using GIS
Calibration of stochastic cellular automata
Planning Support Systems for Sustainable Urban Development
Implementation and calibration of a new irregular cellular automata-based model for local urban growth simulation
Integration of land use, land cover, transportation, and environmental impact models
A Coefficient of Agreement for Nominal Scales
An Artificial-Neural-Network-based, Constrained CA Model for Simulating Urban Growth
Land use change modelling
The Use of Artificial Neural Networks in a Geographical Information System for Agricultural Land-Suitability Assessment
| Obras citantes distintas | 14 |
|---|---|
| Citações por ano | 4,67 |
| Intervalo de citações | 2023 - 2026 (4) |
| Velocidade de citação | current |
| Altamente citado | Não |
| Tipos de citação | Neutras: 9 |