The DOI matches its Crossref record.
The New Science of Cities
Abstract
A proposal for a new way to understand cities and their design not as artifacts but as systems composed of flows and networks. In The New Science of Cities, Michael Batty suggests that to understand cities we must view them not simply as places in space but as systems of networks and flows. To understand space, he argues, we must understand flows, and to understand flows, we must understand networks—the relations between objects that compose the system of the city. Drawing on the complexity sciences, social physics, urban economics, transportation theory, regional science, and urban geography, and building on his own previous work, Batty introduces theories and methods that reveal the deep structure of how cities function. Batty presents the foundations of a new science of cities, defining flows and their networks and introducing tools that can be applied to understanding different aspects of city structure. He examines the size of cities, their internal order, the transport routes that define them, and the locations that fix these networks. He introduces methods of simulation that range from simple stochastic models to bottom-up evolutionary models to aggregate land-use transportation models. Then, using largely the same tools, he presents design and decision-making models that predict interactions and flows in future cities. These networks emphasize a notion with relevance for future research and planning: that design of cities is collective action.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Network approach allows us to study the city as a formal emergent phenomenon, with a Bhidden hand^guiding its growth, and no top-down decision-maker guiding its physical and spatial organization (Batty 2013;Batty 2003).”
From A Network Approach to Link Visibility and Urban Activity Location (2018) · cites this paper as Batty 2013
Citations
Cites
Still being checked.
Cited by
Sorted by citations
Items 201–300 of 1,000
Evidence for the homothetic scaling of urban forms
Rémi Lemoy, A., & Caruso, G. (2018) · Environment and Planning B Urban Analytics and City Science · doi:10.1177/2399808318810532 · Cited by 49
Cozzolino, S. (2019) · Environment and Planning B Urban Analytics and City Science · doi:10.1177/2399808319857451 · Cited by 49
A more-than-human perspective on understanding the performance of the built environment
Loh, S., Foth, M., Caldwell, G. A., Garcia-Hansen, V., & Thomson, M. (2020) · Architectural Science Review · doi:10.1080/00038628.2019.1708258 · Cited by 50
Knowledge Discovery in Smart City Digital Twins
Mohammadi, N., & Taylor, J. E. (2020) · Hawaii International Conference on System Sciences (HICSS) · doi:10.24251/hicss.2020.204 · Cited by 49
Liu, Y., Singleton, A. D., Arribas‐Bel, D., & Chen, M. (2021) · Computers Environment and Urban Systems · doi:10.1016/j.compenvurbsys.2020.101592 · Cited by 49
Examining ecological justice within the social-ecological-technological system of New York City, USA
Pineda-Pinto, M., Herreros-Cantis, P., McPhearson, T., Frantzeskaki, N., Wang, J., & Zhou, W. (2021) · Landscape and Urban Planning · doi:10.1016/j.landurbplan.2021.104228 · Cited by 48
Quek, H. Y., Sielker, F., Akroyd, J., Bhave, A. N., von Richthofen, A., Herthogs, P., Yamu, C. V. D. L., Wan, L., Nochta, T., Burgess, G., et al. (2023) · Data & Policy · doi:10.1017/dap.2023.1 · Cited by 48
Quantifying the impact of urban road networks on the efficiency of local trips
Merchán, D., Winkenbach, M., & Snoeck, A. (2020) · Transportation Research Part A Policy and Practice · doi:10.1016/j.tra.2020.02.015 · Cited by 48
Smart City Planning from an Evolutionary Perspective
Komninos, N., Kakderi, C., Panori, A., & Tsarchopoulos, P. (2020) · Routledge eBooks · doi:10.4324/9781003132851-2 · Cited by 47
Transportation and spatial development: An overview and a future direction
Kii, M., Nakanishi, H., Nakamura, K., & Doi, K. (2016) · Transport Policy · doi:10.1016/j.tranpol.2016.04.015 · Cited by 47
Conceptualizing “Smart Cities”
Finger, M., & Razaghi, M. (2016) · Informatik-Spektrum · doi:10.1007/s00287-016-1002-5 · Cited by 48
Ibrahim, M. R., Titheridge, H., Cheng, T., & Haworth, J. (2019) · Computers Environment and Urban Systems · doi:10.1016/j.compenvurbsys.2019.03.005 · Cited by 47
Association between population distribution and urban GDP scaling
Ribeiro, H. V., Oehlers, M., Moreno-Monroy, A. I., Kropp, J. P., & Diego Rybski, A. (2021) · PLoS ONE · doi:10.1371/journal.pone.0245771 · Cited by 51
Fractal signatures of the COVID-19 spread
Abbasi, M., Bollini, A. L., Castillo, J. L. B., Deppman, A., Guidio, J. P., Matuoka, P. T., Meirelles, A. D. C., Policarpo, J. M. P., Ramos, A. A. G. F., Simionatto, S., et al. (2020) · Chaos Solitons & Fractals · doi:10.1016/j.chaos.2020.110119 · Cited by 45
Foresight in cities: on the possibility of a “strategic urban intelligence”
Ravetz, J., & Miles, I. D. (2016) · foresight · doi:10.1108/fs-06-2015-0037 · Cited by 52
Emergence of encounter networks due to human mobility
Riascos, A. P., & Mateos, J. L. (2017) · PLoS ONE · doi:10.1371/journal.pone.0184532 · Cited by 48
Peris, A., Meijers, E. J., & van Ham, M. (2018) · Networks and Spatial Economics · doi:10.1007/s11067-018-9410-5 · Cited by 46
The universal pathway to innovative urban economies
Hong, I., Frank, M. R., Rahwan, I., Jung, W., & Youn, H. (2020) · Science Advances · doi:10.1126/sciadv.aba4934 · Cited by 50
Measure of Landmark Semantic Salience through Geosocial Data Streams
Quesnot, T., & Roche, S. (2014) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi4010001 · Cited by 45
Zuo, Z., & Tang, W. (2016) · Applied Geography · doi:10.1016/j.apgeog.2016.03.004 · Cited by 45
The future of sustainable urbanism: a redefinition
Roggema, R. (2016) · City Territory and Architecture · doi:10.1186/s40410-016-0052-y · Cited by 56
The Structure and Dynamics of Cities
Barthélemy, M. (2016) · Cambridge University Press eBooks · doi:10.1017/9781316271377 · Cited by 251
Urban form, infrastructure and spatial organisation in the Roman Empire
Hanson, J., Ortman, S. G., Bettencourt, L. M. A., & Mazur, L. C. (2019) · Antiquity · doi:10.15184/aqy.2018.192 · Cited by 46
Loo, B. P. Y., & Tang, W. S. M. (2019) · Journal of Urban Technology · doi:10.1080/10630732.2019.1576467 · Cited by 45
Who, Where, Why and When? Using Smart Card and Social Media Data to Understand Urban Mobility
Yang, Y., Heppenstall, A. J., Turner, A. G. D., & Comber, A. (2019) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi8060271 · Cited by 45
Liu, X., Wu, J., Huang, J. W., Zhang, J., Chen, B. Y., & Chen, A. (2021) · Journal of Transport Geography · doi:10.1016/j.jtrangeo.2021.102991 · Cited by 45
Fractal evolution of urban street networks in form and structure: a case study of Hong Kong
Zhang, H., Lan, T., & Li, Z. (2021) · International Journal of Geographical Information Systems · doi:10.1080/13658816.2021.1974451 · Cited by 45
Integrating space syntax with spatial interaction
Batty, M. (2022) · Urban Informatics · doi:10.1007/s44212-022-00004-2 · Cited by 45
Self-citationUrban planning in the era of large language models
Zheng, Y., Xu, F., Lin, Y., Santi, P., Ratti, C., Wang, Q., & Li, Y. (2025) · Nature Computational Science · doi:10.1038/s43588-025-00846-1 · Cited by 54
Geography and computers: Past, present, and future
Arribas‐Bel, D., & Reades, J. (2018) · Geography Compass · doi:10.1111/gec3.12403 · Cited by 44
Ullah, H., Wan, W., Haidery, S. A., Khan, N. U., Ebrahimpour, Z., & Luo, T. (2019) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi8110506 · Cited by 44
Zhong, T., Lü, G., Zhong, X., Tang, H., & Ye, Y. (2020) · Sustainability · doi:10.3390/su12114712 · Cited by 44
Urban Techno-Politics: Knowing, Governing, and Imagining the City
Karvonen, A. (2020) · Science as Culture · doi:10.1080/09505431.2020.1766011 · Cited by 45
Planning and complexity: Engaging with temporal dynamics, uncertainty and complex adaptive systems
Sengupta, U., Rauws, W. S., & de Roo, G. (2016) · Environment and Planning B Planning and Design · doi:10.1177/0265813516675872 · Cited by 56
Re-engineering the City: Platform Ecosystems and the Capture of Urban Big Data
Barns, S. (2020) · Frontiers in Sustainable Cities · doi:10.3389/frsc.2020.00032 · Cited by 33
Thinking organic, acting civic: The paradox of planning for Cities in Evolution
Batty, M., & Marshall, S. (2016) · Landscape and Urban Planning · doi:10.1016/j.landurbplan.2016.06.002 · Cited by 52
Self-citationTactical urbanism as a means of testing relational processes in space: A complex systems perspective
Wohl, S. (2017) · Planning Theory · doi:10.1177/1473095217722809 · Cited by 43
Gravity model in dockless bike-sharing systems within cities
Li, R., Gao, S., Luo, A., Yao, Q. H., Chen, B., Shang, F., Jiang, R., & Stanley, E. (2021) · Physical review. E · doi:10.1103/physreve.103.012312 · Cited by 43
Antwi-Afari, P., Owusu‐Manu, D., Simons, B., Debrah, C., & Ghansah, F. A. (2021) · Sustainable Futures · doi:10.1016/j.sftr.2021.100044 · Cited by 49
He, J., Wei, Y., & Yu, B. (2023) · International Journal of Geographical Information Systems · doi:10.1080/13658816.2023.2192122 · Cited by 42
Segregated Networks in the City
Netto, V. M., Soares, M. P., & Paschoalino, R. (2015) · International Journal of Urban and Regional Research · doi:10.1111/1468-2427.12346 · Cited by 42
Examining the Interaction of Taxi and Subway Ridership for Sustainable Urbanization
Li, M., Dong, L., Shen, Z., Lang, W., & Ye, X. (2017) · Sustainability · doi:10.3390/su9020242 · Cited by 42
Measuring inter-city connectivity in an urban agglomeration based on multi-source data
Lin, J., Wu, Z., & Li, X. (2019) · International Journal of Geographical Information Systems · doi:10.1080/13658816.2018.1563302 · Cited by 42
Open Geospatial Analytics with PySAL
Rey, S. J., Anselin, L., Li, X., Pahle, R., Laura, J. R., Li, W., & Koschinsky, J. (2015) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi4020815 · Cited by 42
Lin, J., & Li, X. (2015) · International Journal of Geographical Information Systems · doi:10.1080/13658816.2015.1034721 · Cited by 41
Omer, I., & Goldblatt, R. (2016) · Environment and Planning B Urban Analytics and City Science · doi:10.1177/0265813516647061 · Cited by 41
Kitchin, R. (2017) · Routledge eBooks · doi:10.4324/9781315407388-4 · Cited by 41
Creative actors and historical–cultural assets in urban regions
Kourtit, K., & Nijkamp, P. J. (2018) · Regional Studies · doi:10.1080/00343404.2018.1541077 · Cited by 41
Weaving seams with data: Conceptualizing City APIs as elements of infrastructures
Raetzsch, C., Pereira, G., Vestergaard, L. S., & Brynskov, M. (2019) · Big Data & Society · doi:10.1177/2053951719827619 · Cited by 42
Jin, M., Gong, L., Cao, Y., Zhang, P., Gong, Y., & Liu, Y. (2021) · Computers Environment and Urban Systems · doi:10.1016/j.compenvurbsys.2021.101625 · Cited by 41
Exploring the relevance of ‘smart city’ approaches to low-income communities in Medellín, Colombia
Smith, H. C., Medero, G. M., Narváez, S. C. D., & Mera, W. E. C. (2022) · GeoJournal · doi:10.1007/s10708-022-10574-y · Cited by 47
Generating mobility networks with generative adversarial networks
Mauro, G., Luca, M., Longa, A., Lepri, B., & Pappalardo, L. (2022) · EPJ Data Science · doi:10.1140/epjds/s13688-022-00372-4 · Cited by 40
Global city size hierarchy: Spatial patterns, regional features, and implications for China
Fang, C., Pang, B., & Liu, H. (2017) · Habitat International · doi:10.1016/j.habitatint.2017.06.002 · Cited by 40
Yamu, C., & van Nes, A. (2017) · Urban Science · doi:10.3390/urbansci1040037 · Cited by 40
Big Data and government: Evidence of the role of Big Data for smart cities
Hong, S., Kim, S. H., Kim, Y., & Park, J. (2019) · Big Data & Society · doi:10.1177/2053951719842543 · Cited by 42
Xia, C., Zhang, A., Wang, H., & Liu, J. (2019) · Land Use Policy · doi:10.1016/j.landusepol.2019.104332 · Cited by 40
Polycentric Urban Development and its Determinants in China: A Geospatial Big Data Perspective
Lv, Y., Lan, Z., Kan, C., & Zheng, X. (2020) · Geographical Analysis · doi:10.1111/gean.12236 · Cited by 40
Yılmaz, M., & Terzi, F. (2021) · Land Use Policy · doi:10.1016/j.landusepol.2021.105487 · Cited by 40
Urban Futures in Planning, Policy and Regional Science: Are We Entering a Post-Urban World?
Westlund, H. (2014) · Built Environment · doi:10.2148/benv.40.4.447 · Cited by 40
Urban landscape infrastructures
Nijhuis, S., & Jauslin, D. (2015) · Repository hosted by TU Delft Library (TU Delft) · doi:10.7480/rius.3.874 · Cited by 40
Unveiling patterns of international communities in a global city using mobile phone data
Bajardi, P., Delfino, M., Panisson, A., Petri, G., & Tizzoni, M. (2015) · EPJ Data Science · doi:10.1140/epjds/s13688-015-0041-5 · Cited by 40
Greco, I., & Cresta, A. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-21407-8_40 · Cited by 39
Modelling the relation between income and commuting distance
Carra, G., Mulalic, I., Fosgerau, M., & Barthélemy, M. (2016) · Journal of The Royal Society Interface · doi:10.1098/rsif.2016.0306 · Cited by 39
A systemic approach of urban resilience: power laws and urban growth patterns
Salat, S. (2017) · International Journal of Urban Sustainable Development · doi:10.1080/19463138.2016.1277227 · Cited by 39
Re-examining urban region and inferring regional function based on spatial–temporal interaction
Tao, H., Wang, K., Zhuo, L., & Li, X. (2018) · International Journal of Digital Earth · doi:10.1080/17538947.2018.1425490 · Cited by 39
Forecasting innovations in science, technology, and education
Börner, K., Rouse, W. B., Trunfio, P. A., & Stanley, E. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1818750115 · Cited by 42
City unbound: emerging mega-conurbations in Asia
Friedmann, J. R. P., & Sørensen, A. (2019) · International Planning Studies · doi:10.1080/13563475.2019.1555314 · Cited by 39
Cities as complex systems—Collection overview
Diego Rybski, A., & González, M. C. (2022) · PLoS ONE · doi:10.1371/journal.pone.0262964 · Cited by 39
The Architecture of Connectivity: A Key to Network Vulnerability, Complexity and Resilience
Reggiani, A. (2022) · Networks and Spatial Economics · doi:10.1007/s11067-022-09563-y · Cited by 45
Ripley’s K‐function for Network‐Constrained Flow Data
Kan, Z., Kwan, M., & Tang, L. (2021) · Geographical Analysis · doi:10.1111/gean.12300 · Cited by 38
Seeds of the Future in the Present
Pereira, L. M., Bennett, E. M., Biggs, R., Peterson, G., McPhearson, T., Norström, A. V., Olsson, P., Preiser, R., Raudsepp‐Hearne, C., & Vervoort, J. (2018) · Cambridge University Press eBooks · doi:10.1017/9781316647554.018 · Cited by 46
Organizing Theories for Disasters into a Complex Adaptive System Framework
Burger, A., Kennedy, W. G., & Crooks, A. T. (2021) · Urban Science · doi:10.3390/urbansci5030061 · Cited by 40
Slipstreaming human geosimulation in virtual geographic environments
Torrens, P. M. (2015) · Annals of GIS · doi:10.1080/19475683.2015.1009489 · Cited by 38
Questions of uncertainty in geography
Fusco, G. M., Caglioni, M., Emsellem, K., Mérad, M., Moreno, D., & Voiron‐Canicio, C. (2017) · Environment and Planning A Economy and Space · doi:10.1177/0308518x17718838 · Cited by 37
Derudder, B., & van Meeteren, M. (2019) · Urban Geography · doi:10.1080/02723638.2019.1585138 · Cited by 37
(So) Big Data and the transformation of the city
Andrienko, G., Andrienko, N. V., Boldrini, C., Caldarelli, G., Cintia, P., Cresci, S., Facchini, A., Giannotti, F., Gionis, A., Guidotti, R., et al. (2020) · International Journal of Data Science and Analytics · doi:10.1007/s41060-020-00207-3 · Cited by 35
A Review of Methods to Study Resilience of Complex Engineering and Engineered Systems
Naghshbandi, S. N., Varga, L., Purvis, A., McWilliam, R. P., Minisci, E. A., Vasile, M. L., Troffaes, M. C. M., Sedighi, T., Guo, W., Manley, E., et al. (2020) · IEEE Access · doi:10.1109/access.2020.2992239 · Cited by 37
Yang, C., & Qian, Z. (2022) · URBAN DESIGN International · doi:10.1057/s41289-022-00178-w · Cited by 37
Measuring urban sentiments from social media data: a dual-polarity metric approach
Gao, Y. C., Chen, Y., Mu, L., Gong, S., Zhang, P., & Liu, Y. (2022) · Journal of Geographical Systems · doi:10.1007/s10109-021-00369-z · Cited by 39
Huang, L., Zhu, X., Ye, X., Guo, W. J., & Wang, J. (2015) · Environment and Planning B Planning and Design · doi:10.1177/0265813515614456 · Cited by 36
Zhou, M., Yue, Y., Li, Q., & Wang, D. (2016) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi5120240 · Cited by 36
Analysis of urban agglomeration structure through spatial network and mobile phone data
Liu, X., Huang, J. W., Lai, J., Zhang, J., Senousi, A. M., & Zhao, P. (2021) · Transactions in GIS · doi:10.1111/tgis.12755 · Cited by 37
Multi-source Data-driven Identification of Urban Functional Areas: A Case of Shenyang, China
Xue, B., Xiao, X., Li, J., Zhao, B., & Fu, B. (2022) · Chinese Geographical Science · doi:10.1007/s11769-022-1320-2 · Cited by 36
Urban Echoes: Exploring the Dynamic Realities of Cities through Digital Twins
Boccardo, P., Riccia, L. L., & Yadav, Y. (2024) · Land · doi:10.3390/land13050635 · Cited by 35
The Promise of Urban Informatics: Some Speculations
Thrift, N. J. (2014) · Environment and Planning A Economy and Space · doi:10.1068/a472c · Cited by 35
Supersampling and Network Reconstruction of Urban Mobility
Sagarra, O., Szell, M., Santi, P., Dı́az-Guilera, A., & Ratti, C. (2015) · PLoS ONE · doi:10.1371/journal.pone.0134508 · Cited by 35
Mapping Urban Accessibility in Data Scarce Contexts Using Space Syntax and Location-Based Methods
Morales, J., Flacke, J., Morales, J., & Zevenbergen, J. A. (2017) · Applied Spatial Analysis and Policy · doi:10.1007/s12061-017-9239-1 · Cited by 35
Segregation through space: A scope of the flow-based spatial interaction model
Shen, Y. (2019) · Journal of Transport Geography · doi:10.1016/j.jtrangeo.2019.02.007 · Cited by 35
The urban data deluge: challenges for smart urban planning in the third data revolution
Kourtit, K., Elmlund, P., & Nijkamp, P. J. (2020) · International Journal of Urban Sciences · doi:10.1080/12265934.2020.1755353 · Cited by 35
Rethinking slums, cities, and urban planning: lessons from the COVID-19 pandemic
Patel, A., & Shah, P. (2020) · Cities & Health · doi:10.1080/23748834.2020.1790252 · Cited by 35
Viewpoint: City Information Modelling (CIM) and Digitizing Urban Design Practices
Stojanovski, T., Partanen, J., Samuels, I., Sanders, P. S., & Peters, C. (2020) · Built Environment · doi:10.2148/benv.46.4.637 · Cited by 35
Agent-Based Modeling and the City: A Gallery of Applications
Crooks, A. T., Heppenstall, A. J., Malleson, N., & Manley, E. (2021) · The urban book series · doi:10.1007/978-981-15-8983-6_46 · Cited by 47
Bassolas, A., & Nicosia, V. (2021) · Communications Physics · doi:10.1038/s42005-021-00580-w · Cited by 35
The co-evolutionary approach to nature-based solutions: A conceptual framework
Herrmann‐Pillath, C., Hiedanpää, J., & Soini, K. (2022) · Nature-Based Solutions · doi:10.1016/j.nbsj.2022.100011 · Cited by 35
Jiang, N., Crooks, A. T., Kavak, H., Burger, A., & Kennedy, W. G. (2022) · Computational Urban Science · doi:10.1007/s43762-022-00034-1 · Cited by 35
The angular nature of road networks
Molinero, C., Murcio, R., & Arcaute, E. (2017) · Scientific Reports · doi:10.1038/s41598-017-04477-z · Cited by 34
Administrative boundaries and urban areas in Italy: A perspective from scaling laws
Alvioli, M. (2020) · Landscape and Urban Planning · doi:10.1016/j.landurbplan.2020.103906 · Cited by 34
Kourtit, K. (2021) · Asia-Pacific Journal of Regional Science · doi:10.1007/s41685-021-00193-9 · Cited by 38
High-fidelity behaviours for model people on model streetscapes
Torrens, P. M. (2014) · Annals of GIS · doi:10.1080/19475683.2014.944933 · Cited by 34
Line structure representation for road network analysis
Marshall, S. (2015) · Journal of Transport and Land Use · doi:10.5198/jtlu.2015.744 · Cited by 34
Metadata
- Authors
- Batty, M.
- Corresponding author
- Batty, Michael
- ORCID
- Batty, Michael
- Venue
- The MIT Press eBooks
- Publisher
- The MIT Press
- Published
- 2013-11-01
- OpenAlex
- W202805313
- Cited by
- 1,700
- References
- 0
- Citations by year
- 2026: 225 · 2025: 161 · 2024: 107 · 2023: 106 · 2022: 106 · 2021: 156 · 2020: 170 · 2019: 146 · 2018: 176 · 2017: 121 · 2016: 96 · 2015: 84 · 2014: 45
- FWCI
- 79.85
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- The MIT Press eBooks (publishedVersion)
- Topics
- Social Sciences › Urban Studies › Urban Design and Spatial Analysis
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Agglomeration and Urban Systems
- Social Sciences › Urban Studies › Global Urban Networks and Dynamics
- Keywords
- urban systems, urban networks, flow, complexity science, social physics, urban design, city size, transportation routes, urban structure, stochastic modeling, evolutionary models, urban planning, collective action, urban decision-making
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review