cellular automata; land use prediction; urban densification; urban models; urban simulation; Global and Planetary Change; Ecology; Nature and Landscape Conservation
Abstract :
[en] The creation of an accurate simulation of future urban growth is considered to be one of the most important challenges of the last five decades that involves spatial modeling within a GIS environment. Even though built-up densification processes, or transitions from low to high density, are critical for policymakers concerned with limiting sprawl, the literature on models for urban study reveals that most of them focus solely on the expansion process. Although the majority of these models have similar goals, they differ in terms of implementation and theoretical assumptions. Cellular automata (CA) models have been proven to be successful at simulating urban growth dynamics and projecting future scenarios at multiple scales. This paper aims to revisit urban CA models to determine the various approaches for a realistic simulation and prediction of urban densification. The general characteristics of CA models are described with respect to analysis of various driving factors that influence urban scenarios. This paper also critically analyzes various hybrid models based on CA such as the Markov chain, artificial neural network (ANN), and logistic regression (LR). Limitation and uncertainties of CA models, namely, neighborhood cell size, may be minimized when integrated with empirical and statistical models. The result of this review suggests that it is useful to use CA models with multinomial logistic regression (MLR) in order to analyze and model the effects of various driving factors related to urban densification. Realistic simulations can be achieved when multidensity class labels are integrated in the modeling process.
Chakraborty, Anasua ; Université de Liège - ULiège > Urban and Environmental Engineering
Sikder, Sujit ; Leibniz Institute of Ecological Urban and Regional Development, Dresden, Germany
Omrani, Hichem ; Urban Development and Mobility, Luxembourg Institute of Socio-Economic Research, University of Luxembourg, Esch-sur-Alzette, Luxembourg
Teller, Jacques ; Université de Liège - ULiège > Département ArGEnCo > LEMA (Local environment management and analysis)
Language :
English
Title :
Cellular Automata in Modeling and Predicting Urban Densification: Revisiting the Literature since 1971
F.R.S.-FNRS - Fonds de la Recherche Scientifique [BE] FNR - Fonds National de la Recherche [LU]
Funding text :
This research was funded by the INTER program and cofunded by the Fond National de la Recherche, Luxembourg (FNR) and the Fund for Scientific Research-FNRS, Belgium (F.R.S—FNRS), T.0233.20,—‘Sustainable Residential Densification’ project (SusDens, 2020–2023).
Liu X. Ma L. Li X. Ai B. Li S. He Z. Simulating urban growth by integrating landscape expansion index (LEI) and cellular automata Int. J. Geogr. Inf. Sci. 2014 28 148 163 10.1080/13658816.2013.831097
Lambin E.F. Turner B.L. Geist H.J. Agbola S.B. Angelsen A. Bruce J.W. Coomes O.T. Dirzo R. Fischer G. Folke C. The causes of land-use and land-cover change: Moving beyond the myths Glob. Environ. Chang. 2001 11 261 269 10.1016/S0959-3780(01)00007-3
Rasoul G. Noushad S. Smart growth strategy in urban development, principles and approaches J. Geogr. Develop. 2008 6 163 180
Shi L. Shao G. Cui S. Li X. Lin T. Yin K. Zhao J. Urban three-dimensional expansion and its driving forces—A case study of Shanghai, China Chin. Geogr. Sci. 2009 19 291 298 10.1007/s11769-009-0291-x
Teller J. Regulating urban densification: What factors should be used? Build. Cities 2021 2 302 317 10.5334/bc.123
Mustafa A.M. Heppenstall A. Omrani H. Saadi I. Cools M. Teller J. Modelling built-up expansion and densification with multinomial logistic regression, cellular automata and genetic algorithm Comput. Environ. Urban Syst. 2018 67 147 156 10.1016/j.compenvurbsys.2017.09.009
Gordon P. Richardson H.W. Are compact cities a desirable planning goal? J. Am. Plan. Assoc. 1997 63 96 106 10.1080/01944369708975727
Kaur M. Hewage K. Sadiq R. Investigating the impacts of urban densification on buried water infrastructure through DPSIR framework J. Clean. Prod. 2020 259 120897 10.1016/j.jclepro.2020.120897
Broitman D. Koomen E. Residential Density Change: Densification and Urban Expansion Geogr. Urban Process. (Sub-Top.) 2015 54 32 46 10.1016/j.compenvurbsys.2015.05.006
Leao S. Bishop I. Evans D. Simulating urban growth in a developing nation’s region using a CA-based model J. Urban Plan. Dev. 2004 130 145 158 10.1061/(ASCE)0733-9488(2004)130:3(145)
Herold M. Goldstein N.C. Clarke K.C. The spatiotemporal form of urban growth: Measurement, analysis and modeling Remote Sens. Environ. 2003 86 286 302 10.1016/S0034-4257(03)00075-0
Poelmans L. Van Rompaey A. Detecting and modelling spatial patterns of urban sprawl in highly fragmented areas: A case study in the Flanders–Brussels region Landsc. Urban Plan. 2009 93 10 19 10.1016/j.landurbplan.2009.05.018
Wang H. He S. Liu X. Dai L. Pan P. Hong S. Zhang W. Simulating urban expansion using a cloud-based cellular automata model: A case study of Jiangxia, Wuhan, China Landsc. Urban Plan. 2013 110 99 112 10.1016/j.landurbplan.2012.10.016
Santé I. García A.M. Miranda D. Crecente R. Cellular automata models for the simulation of real-world urban processes: A review and analysis Landsc. Urban Plan. 2010 96 108 122 10.1016/j.landurbplan.2010.03.001
Tobler W.R. A Computer Movie Simulating Urban Growth in the Detroit Region Econ. Geogr. 1970 46 234 240 10.2307/143141
Couclelis H. Cellular Worlds: A Framework for Modeling Micro—Macro Dynamics Environ. Plan. A 1985 17 585 596 10.1068/a170585
Phipps M. Dynamical Behavior of Cellular Automata under the Constraint of Neighborhood Coherence Geogr. Anal. 2010 21 197 215 10.1111/j.1538-4632.1989.tb00889.x
Batty M. Urban Evolution on the Desktop: Simulation with the Use of Extended Cellular Automata Environ. Plan. A 1998 30 1943 1967 10.1068/a301943
Aburas M.M. Ho Y.M. Ramli M.F. Ash’aari Z.H. The simulation and prediction of spatio-temporal urban growth trends using cellular automata models: A review Int. J. Appl. Earth Obs. GeoInf. 2016 52 380 389 10.1016/j.jag.2016.07.007
Liang X. Liu X. Li D. Zhao H. Chen G. Urban growth simulation by incorporating planning policies into a CA-based future land-use simulation model Int. J. Geogr. Inf. Sci. 2018 32 2294 2316 10.1080/13658816.2018.1502441
Tong X. Feng Y. A review of assessment methods for cellular automata models of land-use change and urban growth Int. J. Geogr. Inf. Sci. 2020 34 866 898 10.1080/13658816.2019.1684499
Al-sharif A. Pradhan B. A novel Approach for Predicting the Spatial Patterns of Urban Expansion by Combining the Chi-Squared Automatic Integration Detection Decision Tree, Markov Chain, and Cellular Automata Models in GIS Geocarto Int. 2015 30 858 881 10.1080/10106049.2014.997308
Singh A.K. Modelling Land Use Land Cover Changes Using Cellular Automata in a Geo-Spatial Environment Master’s Thesis ITC Enschede, The Netherlands 2003
Liu Y. Modelling Urban Development with Geographical Information Systems and Cellular Automata: A Case Study of Sydney since 1971 Taylor and Francis New York, NY, USA 2001
Basse R. Omrani H. Charif O. Gerber P. Bódis K. Land use changes modelling using advanced methods: Cellular automata and artificial neural networks. The spatial and explicit representation of land cover dynamics at the cross-border region scale Appl. Geogr. 2014 53 160 171 10.1016/j.apgeog.2014.06.016
Li X. Yeh A.G.O. Neural-network-based cellular automata for simulating multiple land use changes using GIS Int. J. Geogr. Inf. Sci. 2002 16 323 343 10.1080/13658810210137004
Li X. Liu X.P. An extended cellular automaton using case-based reasoning for simulating urban Int. J. Geogr. Inf. Sci. 2006 20 1109 1136 10.1080/13658810600816870
Liu X. Li X. Liu L. He J. Ai B. A bottom-up approach to discover transition rules of cellular automata using ant intelligence Int. J. Geogr. Inf. Sci. 2008 22 1247 1269 10.1080/13658810701757510
Mitsova D. Shuster W. Wang X. A cellular automata model of land cover change to integrate urban growth with open space conservation Landsc. Urban Plan. 2011 99 41 153 10.1016/j.landurbplan.2010.10.001
Mantelas L. Prastacos P. Hatzichristos T. Koutsopoulos K. Using fuzzy cellular automata to access and simulate urban growth GeoJournal 2012 77 13 28 10.1007/s10708-010-9372-8
Liu Y. Feng Y. A Logistic Based Cellular Automata Model for Continuous Urban Growth Simulation: A Case Study of the Gold Coast City, Australia Agent-Based Models of Geographical Systems Heppenstall A. Crooks A. See L. Batty M. Springer Dordrecht, The Netherlands 2012 10.1007/978-90-481-8927-4_32
Al-Shalabi Al-Sharif A.A. Pradhan B. Monitoring and predicting land use change in Tripoli Metropolitan City using an integrated Markov chain and cellular automata models in GIS Arab. J. Geosci. 2013 7 4291 4301 10.1007/s12517-013-1119-7
Wagner D.F. Cellular Automata and Geographic Information Systems Environ. Plan. B Plan. Des. 1997 24 219 234 10.1068/b240219
Sgandurra D. An Introduction to Cellular Automata (Powerpoint presentation) Bio-inspired Models of Computation, Dipartimento di Informatica, Università di Pisa Pisa, Italy 16 October 2009
Rodríguez Puente R. Pérez Betancourt Y.G. Mufeti K. Cellular Automata and Its Applications in Modeling and Simulating the Evolution of Diseases [Paper Presentation] National Research Symposium Windhoek, Namibia 2015
Wolfram S. Cellular automata as models of complexity Nature 1984 311 419 424 10.1038/311419a0
Grimm N. Grove M. Pickett S.T.A. Redman C. Integrated Approaches to Long-Term Studies of Urban Ecological Systems Springer Boston, MA, USA 2008 10.1007/978-0-387-73412-5_8
Allen J. Lu K. Modeling and Prediction of Future Urban Growth in the Charleston Region of South Carolina: A GIS-based Integrated Approach Conserv. Ecol. 2003 8 10.5751/ES-00595-080202
Amato F. Pontrandolfi P. Murgante B. Using Spatiotemporal Analysis in Urban Sprawl Assessment and Prediction Computational Science and Its Applications–ICCSA 2014. ICCSA 2014. Lecture Notes in Computer Science Springer Cham, Switzerland 2014 Volume 8580 758 773 10.1007/978-3-319-09129-7_55
Verburg P. Overmars K. Huigen M. Groot W. Veldkamp A. Analysis of the effects of land use change on protected areas in the Philippines Appl. Geogr. 2006 26 153 173 10.1016/j.apgeog.2005.11.005
Jokar Arsanjani J. Zipf A. Mooney P. Helbich M. An Introduction to OpenStreetMap in Geographic Information Science: Experiences, Research, and Applications OpenStreetMap in GIScience Jokar Arsanjani J. Zipf A. Mooney P. Helbich M. Lecture Notes in Geoinformation and Cartography; Springer Cham, Switzerland 2015 10.1007/978-3-319-14280-7_1
Poelmans L. Rompaey A.V. Complexity and performance of urban expansion models Comput. Environ. Urban Syst. 2010 34 17 27 10.1016/j.compenvurbsys.2009.06.001
Verburg P. Dijst M. Schot P. Veldkamp A. Land Use Change Modelling: Current Practice and Research Priorities Geojournal 2004 61 309 324 10.1007/s10708-004-4946-y
Yagoub M.M. Bizreh A.A. Prediction of Land Cover Change Using Markov and Cellular Automata Models: Case of Al-Ain, UAE, 1992–2030 J. Indian Soc. Remote Sens. 2014 42 665 671 10.1007/s12524-013-0353-5
Clarke K.C. Hoppen S. Gaydos L. A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area Environ. Plan. B: Plan. Des. 1997 24 247 261 10.1068/b240247
Landis J. Zhang M. The second generation of the California urban futures model Environ. Plan. B Plan. Des. 1998 25 795 824 10.1068/b250795
Al-sharif A. Pradhan B. Shafri H. Mansor S. Quantitative analysis of urban sprawl in Tripoli using Pearson’s Chi-Square statistics and urban expansion intensity index IOP Conf. Ser. Earth Environ. Sci. 2014 20 012006 10.1088/1755-1315/20/1/012006
Hu Z. Lo C. Modeling urban growth in Atlanta using logistic regression Comput. Environ. Urban Syst. 2007 31 667 688 10.1016/j.compenvurbsys.2006.11.001
Li X. Gong P. Urban growth models: Progress and perspective Sci. Bull. 2016 61 1637 1650 10.1007/s11434-016-1111-1
Liu X. Andersson C. Assessing the impact of temporal dynamics on land-use change modeling Comput. Environ. Urban Syst. 2004 28 107 124 10.1016/S0198-9715(02)00045-5
Batty M. Urban Modelling: Algorithms, Calibrations, Predictions Cambridge University Press Cambridge, UK 1976 381
Clarke K. Gaydos L. Loose-Coupling a Cellular Automaton Model and GIS: Long-Term Urban Growth Prediction for San Francisco and Washington/Baltimore Int. J. Geogr. Inf. Sci. IJGIS 1998 12 699 714 10.1080/136588198241617 12294536
Matthews R. Gilbert N. Roach A. Polhill J.G. Gotts N. Agent-based land-use models: A review of applications Landsc. Ecol. 2007 22 1447 1459 10.1007/s10980-007-9135-1
Liu X. Li X. Shi X. Huang K. Liu Y. A multi-type ant colony optimization (MACO) method for optimal land use allocation in large areas Int. J. Geogr. Inf. Sci. 2012 26 1325 1343 10.1080/13658816.2011.635594
Pijanowski B. Brown D.G. Shellito B. Manik G. Using neural networks and GIS to forecast land use changes: A Land Transformation Model Comput. Environ. Urban Syst. 2002 26 553 575 10.1016/S0198-9715(01)00015-1
Waddell P. UrbanSim: Modeling Urban Development for Land Use, Transportation, and Environmental Planning J. Am. Plan. Assoc. 2002 68 297 314 10.1080/01944360208976274
Rahnama M. Forecasting land-use changes in Mashhad Metropolitan area using Cellular Automata and Markov chain model for 2016–2030 Sustain. Cities Soc. 2021 64 102548 10.1016/j.scs.2020.102548
Silva E.A. Clarke K. Calibration of the SLEUTH urban growth model for Lisbon and Porto, Portugal Comput. Environ. Urban Syst. 2002 26 525 552 10.1016/S0198-9715(01)00014-X
Mustafa A.M. Rompaey A.V. Cools M. Saadi I. Teller J. Addressing the determinants of built-up expansion and densification processes at the regional scale Urban Stud. 2018 55 3279 3298 10.1177/0042098017749176
Cao X. Luo P. Li M. Long A. Research on the Simulation of Urban Land Use Change Based on GIS and CA Models—A Case Study of Longgang District, Shenzhen City Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology Wuhan, China 4–5 July 2009 Volume 2 351 354
Ghadami M. Dittmann A. Safarrad T. Lack of Spatial Approach in Urban Density Policies: The Case of the Master Plan of Tehran Sustainability 2020 12 7285 10.3390/su12187285
Batty M. Artificial intelligence and smart cities Environ. Plan. B Urban Anal. City Sci. 2018 45 3 6 10.1177/2399808317751169
Mustafa A.M. Cools M. Saadi I. Teller J. Coupling agent-based, cellular automata and logistic regression into a hybrid urban expansion model (HUEM) Land Use Policy 2017 69 529 540 10.1016/j.landusepol.2017.10.009
White R. Engelen G. Cellular Automata and Fractal Urban Form: A Cellular Modelling Approach to the Evolution of Urban Land-Use Patterns Environ. Plan. A 1993 25 1175 1199 10.1068/a251175
Liu Y. Corcoran J. Feng Y. Cellular automata International Encyclopedia of Human Geography Elsevier Amsterdam, The Netherlands 2020 101 104 10.1016/b978-0-08-102295-5.10519-0
Liu Y. Dai L. Xiong H. Simulation of urban expansion patterns by integrating auto-logistic regression, Markov chain and cellular automata models J. Environ. Plan. Manag. 2015 58 1113 1136 10.1080/09640568.2014.916612
Almeida C. Gleriani J.M. Castejon E. Soares-Filho B. Using neural networks and cellular automata for modelling intra-urban land-use dynamics Int. J. Geogr. Inf. Sci. 2008 22 943 963 10.1080/13658810701731168
Xiao Y. Watson M. Guidance on Conducting a Systematic Literature Review J. Plan. Educ. Res. 2017 39 112 193 10.1177/0739456X17723971
Arsanjani J.J. Barron C. Bakillah M. Helbich M. Assessing the quality of OpenStreetMap contributors together with their contributions Proceedings of the AGILE Leuven, Belgium 14–17 May 2013 14 17
Liu Y. Batty M. Wang S. Corcoran J. Modelling urban change with cellular automata: Contemporary issues and future research directions Prog. Hum. Geogr. 2019 45 3 24 10.1177/0309132519895305
Musa S.I. Hashim M. Reba M.N. A review of geospatial-based urban growth models and modelling initiatives Geocarto Int. 2017 32 813 833 10.1080/10106049.2016.1213891
Aburas M.M. Ho Y. Ramli M.F. Ash’aari Z.H. Improving the capability of an integrated CA-Markov model to simulate spatio-temporal urban growth trends using an Analytical Hierarchy Process and Frequency Ratio Int. J. Appl. Earth Obs. Geoinf. 2017 59 65 78 10.1016/j.jag.2017.03.006
Kang J. Fang L. Li S. Wang X. Parallel Cellular Automata Markov Model for Land Use Change Prediction over MapReduce Framework ISPRS Int. J. Geo-Inf. 2019 8 454 10.3390/ijgi8100454
Yang Q. Li X. Nonlinear transition rules of urban cellular automata based on a Bayesian method Acat Sci. Nat. Univ. Sunyatseni 2007 46 105 109 (In Chinese)
Yang Q. Li X. Shi X. Cellular automata for simulating land use changes based on support vector machines Comput. Geosci. 2008 34 592 602 10.1016/j.cageo.2007.08.003
Palme M. Ramirez J.E. A Critical Assessment and Projection of Urban Vertical Growth in Antofagasta, Chile Sustainability 2013 5 2840 2855 10.3390/su5072840
Huang C. Homer C. Yang L. Regional forest land cover characterisation using medium spatial resolution satellite data Remote Sensing of Forest Environments Springer Boston, MA, USA 2003 389 410
Aristodemou E. Boganegra L.M. Mottet L. Pavlidis D. Constantinou A. Pain C.C. Robins A. ApSimon H.M. How tall buildings affect turbulent air flows and dispersion of pollution within a neighbourhood Environ. Pollut. 2018 233 782 796 10.1016/j.envpol.2017.10.041
Tang U.W. Wang Z.S. Influences of urban forms on traffic-induced noise and air pollution: Results from a modelling system Environ. Model. Softw. 2007 22 1750 1764 10.1016/j.envsoft.2007.02.003
Koziatek O. Dragićević S. iCity 3D: A geosimualtion method and tool for three-dimensional modeling of vertical urban development Landsc. Urban Plan. 2017 167 356 367 10.1016/j.landurbplan.2017.06.021
Jian S.U.N. Zhang L. Chunlu P.E.N.G. Zhongren P.E.N.G. Meng X.U. CA-based urban land use prediction model: A case study on orange county, Florida, US J. Transp. Syst. Eng. Inf. Technol. 2012 12 85 92
Wang R. Murayama Y. Morimoto T. Scenario simulation studies of urban development using remote sensing and GIS: Review Remote Sens. Appl. Soc. Environ. 2021 22 100474 10.1016/j.rsase.2021.100474
Anand J. Gosain A. Khosa R. Prediction of land use changes based on Land Change Modeler and attribution of changes in the water balance of Ganga basin to land use change using the SWAT model Sci. Total Environ. 2018 644 503 519 10.1016/j.scitotenv.2018.07.017
Ewing R.H. Characteristics, causes, and effects of sprawl: A literature review Urban Ecology Springer New York, NY, USA 2008 519 535
Mieszkowski P. Mills E. The causes of metropolitan suburbanization J. Econ. Perspect. 1993 7 135 147 10.1257/jep.7.3.135
Pendall R. Do land-use controls cause sprawl? Environ. Plan. B Plan. Des. 1999 26 555 571 10.1068/b260555
Dieleman F. Wegener M. Compact city and urban sprawl Built Environ. 2004 30 308 323 10.2148/benv.30.4.308.57151
Landis J. The California Urban Futures Model: A New Generation of Metropolitan Simulation Models Environ. Plan. B Plan. Des. 1994 21 399 420 10.1068/b210399
Zhou L. Dang X. Mu H. Wang B. Wang S. Cities are going uphill: Slope gradient analysis of urban expansion and its driving factors in China Sci. Total Environ. 2021 775 145836 10.1016/j.scitotenv.2021.145836
Kim Y. Newman G. Güneralp B. A Review of Driving Factors, Scenarios, and Topics in Urban Land Change Models Land 2020 9 246 10.3390/land9080246 35685116
Liu C. Ma X. Analysis to driving forces of land use change in Lu’an mining area Trans. Nonferrous Met. Soc. China 2011 21 s727 s732 10.1016/S1003-6326(12)61670-7
Wu F. Calibration of stochastic cellular automata: The application to rural-urban land conversions Int. J. Geogr. Inf. Sci. 2002 16 795 818 10.1080/13658810210157769
Shu B. Bakker M.M. Zhang H. Li Y. Qin W. Carsjens G.J. Modeling urban expansion by using variable weights logistic cellular automata: A case study of Nanjing, China Int. J. Geogr. Inf. Sci. 2017 31 1314 1333 10.1080/13658816.2017.1283505
Pontius R. Huffaker D. Denman K. Useful techniques of validation for spatially explicit land-change models Ecol. Model. 2004 179 445 461 10.1016/j.ecolmodel.2004.05.010
Sargent R. An introductory tutorial on verification and validation of simulation models Proceedings of the 2015 Winter Simulation Conference (WSC) Huntington Beach, CA, USA 6–9 December 2015 1729 1740
Chung C. Fabbri A. Validation of Spatial Prediction Models for Landslide Hazard Mapping Nat. Hazards 2003 30 451 472 10.1023/B:NHAZ.0000007172.62651.2b
Vliet J.V. Calibration and Validation of Land-Use Models Ph.D. Thesis Wageningen University Wageningen, The Netherlands 2013 162 Available online: https://www.wur.nl/en/Publication-details.htm?publicationId=publication-way-343332353934 (accessed on 13 March 2022)
Rykiel E. Testing ecological models: The meaning of validation Ecol. Model. 1996 90 229 244 10.1016/0304-3800(95)00152-2
Soares-Filho B. Cerqueira G. Pennachin C. Dinamica—A stochastic cellular automata model designed to simulate the landscape dynamics in an Amazonian colonization frontier Ecol. Model. 2002 154 217 235 10.1016/S0304-3800(02)00059-5
Wu F. An Experiment on the Generic Polycentricity of Urban Growth in a Cellular Automatic City Environ. Plan. B Plan. Des. 1998 25 731 752 10.1068/b250731
González P.B. Gómez-Delgado M. Aguilera-Benavente F. From raster to vector cellular automata models: A new approach to simulate urban growth with the help of graph theory Comput. Environ. Urban Syst. 2015 54 119 131 10.1016/j.compenvurbsys.2015.07.004
Triantakonstantis D.P. Mountrakis G. Urban Growth Prediction: A Review of Computational Models and Human Perceptions J. Geogr. Inf. Syst. 2012 4 555 587 10.4236/jgis.2012.46060
Benguigui L. Czamanski D. Roth R. Modeling Cities in 3D: A Cellular Automaton Approach Environ. Plan. B Plan. Des. 2008 35 413 430 10.1068/b33075
Semboloni F. The Growth of an Urban Cluster into a Dynamic Self-Modifying Spatial Pattern Environ. Plan. B Plan. Des. 2000 27 549 564 10.1068/b2673
Agius T. Sabri S. Kalantari M. Three-Dimensional Rule-Based City Modelling to Support Urban Redevelopment Process ISPRS Int. J. Geo Inf. 2018 7 413 10.3390/ijgi7100413
Alomía G. Loaiza D. Zúñiga C. Luo X. Asorey-Cacheda R. Procedural modeling applied to the 3D city model of bogota: A case study Virtual Real. Intell. Hardw. 2021 3 423 433 10.1016/j.vrih.2021.06.002
Lin J. Huang B. Chen M. Huang Z. Modeling urban vertical growth using cellular automata—Guangzhou as a case study Appl. Geogr. 2014 53 172 186 10.1016/j.apgeog.2014.06.007
Güneralp B. Zhou Y. ürge-Vorsatz D. Gupta M.K. Yu S. Patel P. Fragkias M. Li X. Seto K.C. Global scenarios of urban density and its impacts on building energy use through 2050 Proc. Natl. Acad. Sci. USA 2017 114 8945 8950 10.1073/pnas.1606035114 28069957
Vuckovic M. Loibl W. Tötzer T. Stollnberger R. Potential of Urban Densification to Mitigate the Effects of Heat Island in Vienna, Austria Environments 2019 6 82 10.3390/environments6070082
Barredo J. Kasanko M. McCormick N. Lavalle C. Modelling dynamic spatial processes: Simulation of urban future scenarios through cellular automata Landsc. Urban Plan. 2003 64 145 160 10.1016/S0169-2046(02)00218-9
Shukla A. Jain K. Ramsankaran R. Rajasekaran E. Understanding the macro-micro dynamics of urban densification: A case study of different sized Indian cities Land Use Policy 2021 107 105469 10.1016/j.landusepol.2021.105469
Wang L. Omrani H. Zhao Z. Francomano D. Li K. Pijanowski B. Analysis on urban densification dynamics and future modes in southeastern Wisconsin, USA PLoS ONE 2019 14 e0211964 10.1371/journal.pone.0211964
Saganeiti L. Mustafa A.M. Teller J. Murgante B. Modeling urban sprinkling with cellular automata Sustain. Cities Soc. 2020 65 102586 10.1016/j.scs.2020.102586
Guan D. Li H. Inohae T. Su W. Nagaie T. Hokao K. Modeling urban land use change by the integration of cellular automaton and Markov model Ecol. Model. 2011 222 3761 3772 10.1016/j.ecolmodel.2011.09.009
García A.M. Santé-Riveira I. Boullón-Magán M. Crecente-Maseda R. Calibration of an urban cellular automaton model by using statistical techniques and a genetic algorithm. Application to a small urban settlement of NW Spain Int. J. Geogr. Inf. Sci. 2013 27 1593 1611 10.1080/13658816.2012.762454
Nowak A. Kuś M. Urbaniak J. Zarycki T. Simulating the coordination of individual economic decisions Phys. A-Stat. Mech. Its Appl. 2000 287 613 630 10.1016/S0378-4371(00)00397-6
White S.H. Rey Á.M. Sánchez G.R. Modeling epidemics using cellular automata Appl. Math. Comput. 2007 186 193 202 10.1016/j.amc.2006.06.126 32287494
Sieburg H.B. McCutchan H.W. Clay O.K. Caballero L. Ostlund J. Simulation of HIV-infection in artificial immune systems Phys. D Nonlinear Phenom. 1990 45 208 227 10.1016/0167-2789(90)90184-Q
Omrani H. Tayyebi A. Pijanowski B.C. Integrating the multi-label land-use concept and cellular automata with the artificial neural network-based Land Transformation Model: An integrated ML-CA-LTM modeling framework GIScience Remote Sens. 2017 54 283 304 10.1080/15481603.2016.1265706
Chaturvedi V. de Vries W.T. Machine Learning Algorithms for Urban Land Use Planning: A Review Urban Sci. 2021 5 68 10.3390/urbansci5030068