Cited by 1,700Urban Design and Spatial AnalysisAgglomeration and Urban SystemsGlobal Urban Networks and Dynamics

The DOI matches its Crossref record.

The New Science of Cities

Batty, Michael·2013·The MIT Press eBooks

Open this paper in CoChat — free account

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.

Integrity signals

Registry

Crossref · 10.7551/mitpress/9399.001.0001

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

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?

Still being checked.

Sorted by citations

Items 301–400 of 1,000

Spatial applications of topological data analysis: Cities, snowflakes, random structures, and spiders spinning under the influence
Feng, M., & Porter, M. A. (2020) · Physical Review Research · doi:10.1103/physrevresearch.2.033426 · Cited by 34
Living concrete: Democratizing living walls
Riley, B., Larrard, F. D., Malécot, V., Dubois-Brugger, I., Lequay, H., & Lecomte, G. (2019) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2019.04.065 · Cited by 43
The Global Urban: Difference and Complexity in Urban Studies and the Science of Cities
Parnell, S. M., & Robinson, J. (2017) · SAGE Publications Ltd eBooks · doi:10.4135/9781526402059.n2 · Cited by 34
Tracking urban activity growth globally with big location data
Daggitt, M. L., Noulas, A., Shaw, B., & Cecilia Mascolo, C. (2016) · Royal Society Open Science · doi:10.1098/rsos.150688 · Cited by 33
Geographic information science III
Roche, S. (2016) · Progress in Human Geography · doi:10.1177/0309132516650352 · Cited by 33
Agent-Based Modeling
Crooks, A. T., Heppenstall, A. J., & Malleson, N. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-409548-9.09704-9 · Cited by 42
Land suitability analysis of urban development in the Aqaba area, Jordan, using a GIS-based analytic hierarchy process
AlFanatseh, A. (2021) · GeoJournal · doi:10.1007/s10708-021-10488-1 · Cited by 33
Generic patterns in the evolution of urban water networks: Evidence from a large Asian city
Krueger, E., Klinkhamer, C., Urich, C., Zhan, X., & Rao, P. S. C. (2017) · Physical review. E · doi:10.1103/physreve.95.032312 · Cited by 33
Exploring the role of spatial cognition in predicting urban traffic flow through agent-based modelling
Manley, E., & Cheng, T. (2018) · Transportation Research Part A Policy and Practice · doi:10.1016/j.tra.2018.01.020 · Cited by 33
More bark than bytes? Reflections on 21+ years of geocomputation
Harris, R., O’Sullivan, D., GAHEGAN, M. N., Charlton, M. E., Comber, A., Longley, P., Brunsdon, C., Malleson, N., Heppenstall, A. J., Singleton, A. D., et al. (2017) · Environment and Planning B Urban Analytics and City Science · doi:10.1177/2399808317710132 · Cited by 34
Human-Centric Data Science for Urban Studies
Resch, B., & Szell, M. (2019) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi8120584 · Cited by 32
An urban informatics approach to understanding residential mobility in Metro Chicago
Pan, H., Chen, S., Gao, Y., Deal, B. M., & Liu, J. (2020) · Environment and Planning B Urban Analytics and City Science · doi:10.1177/2399808320924437 · Cited by 32
Consuming water smartly: the significance of sociocultural differences to water-saving initiatives
Watson, S. (2017) · Local Environment · doi:10.1080/13549839.2017.1334143 · Cited by 32
Constructing a universal logic of urban control?
Schindler, S., & Marvin, S. (2018) · City · doi:10.1080/13604813.2018.1451021 · Cited by 32
Reinvestigating China’s urbanization through the lens of allometric scaling
Lang, W., Long, Y., Chen, T., & Li, X. (2019) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2019.04.075 · Cited by 32
AwaP-IC—An Open-Source GIS Tool for Measuring Walkable Access
Majić, I., & Pafka, E. (2019) · Urban Science · doi:10.3390/urbansci3020048 · Cited by 32
Big geodata mining: Objective, connotations and research issues
Pei, T., Song, C., Guo, S., Shu, H., Liu, Y., Du, Y., Ma, T., & Zhou, C. (2020) · Journal of Geographical Sciences · doi:10.1007/s11442-020-1726-7 · Cited by 32
The metabolic urban network: Urbanisation as hierarchically ordered space of flows
Inostroza, L., & Zepp, H. (2020) · Cities · doi:10.1016/j.cities.2020.103029 · Cited by 32
Urbanization and Socioeconomic Development in Inner Mongolia in 2000 and 2010: A GIS Analysis
Huang, G., & Jiang, Y. (2017) · Sustainability · doi:10.3390/su9020235 · Cited by 32
Towards incorporating location choice into integrated land use and transport planning and policy: A multi-scale analysis of residential and job location choice behaviour
Acheampong, R. A. (2018) · Land Use Policy · doi:10.1016/j.landusepol.2018.07.007 · Cited by 32
The wicked city: Genealogies of interdisciplinary hubris in urban thought
Barnett, C. (2021) · Transactions of the Institute of British Geographers · doi:10.1111/tran.12483 · Cited by 31
The right tools for the job: The case for spatial science tool‐building
Boeing, G. (2020) · Transactions in GIS · doi:10.1111/tgis.12678 · Cited by 32
Multi-Objective Optimisation of Urban Form: A Framework for Selecting the Optimal Solution
Showkatbakhsh, M., & Makki, M. (2022) · Buildings · doi:10.3390/buildings12091473 · Cited by 31
The UN, the Urban Sustainable Development Goal, and the New Urban Agenda
Rudd, A., Simon, D., Cardama, M., Birch, E. L., & Revi, A. (2018) · Cambridge University Press eBooks · doi:10.1017/9781316647554.011 · Cited by 32
Automated Detection of Missing Links in Bicycle Networks
Vybornova, A., Cunha, T., Gühnemann, A., & Szell, M. (2022) · Geographical Analysis · doi:10.1111/gean.12324 · Cited by 30
Great cities look small
Sim, A., Yaliraki, S. N., Barahona, M., & Stumpf, M. P. H. (2015) · Journal of The Royal Society Interface · doi:10.1098/rsif.2015.0315 · Cited by 30
Visualizing aggregate movement in cities
Batty, M. (2018) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2017.0236 · Cited by 28
Self-citation
A global analysis of cities’ geosocial temporal signatures for points of interest hours of operation
Sparks, K. A., Thakur, G. M., Pasarkar, A., & Urban, M. (2019) · International Journal of Geographical Information Systems · doi:10.1080/13658816.2019.1615069 · Cited by 30
The spatiotemporal scaling laws of urban population dynamics
Tan, X., Huang, B., Batty, M., Li, W., Wang, Q., Zhou, Y., & Gong, P. (2025) · Nature Communications · doi:10.1038/s41467-025-58286-4 · Cited by 32
Self-citation
Research on the Sustainable Synergetic Development of Chinese Urban Economies in the Context of a Study of Industrial Agglomeration
Wang, C., & Meng, Q. (2020) · Sustainability · doi:10.3390/su12031122 · Cited by 29
Citywide Traffic Analysis Based on the Combination of Visual and Analytic Approaches
Liu, F., Andrienko, G., Andrienko, N. V., Chen, S., Janssens, D., Wets, G., & Theodoridis, Y. (2020) · Journal of Geovisualization and Spatial Analysis · doi:10.1007/s41651-020-00057-4 · Cited by 29
The strategic, organizational, and entrepreneurial evolution of smart cities
Schiavone, F., Appio, F. P., Mora, L., & Risitano, M. (2020) · International Entrepreneurship and Management Journal · doi:10.1007/s11365-020-00696-5 · Cited by 29
Urban Spatial Organization, Multifractals, and Evolutionary Patterns in Large Cities
Tan, X., Huang, B., Batty, M., & Li, J. (2020) · Annals of the American Association of Geographers · doi:10.1080/24694452.2020.1823203 · Cited by 29
Self-citation
Quantifying ethnic segregation in cities through random walks
Sousa, S., & Nicosia, V. (2022) · Nature Communications · doi:10.1038/s41467-022-33344-3 · Cited by 29
A Zipf’s Law-Based Method for Mapping Urban Areas Using NPP-VIIRS Nighttime Light Data
Wu, W., Zhao, H., & Jiang, S. (2018) · Remote Sensing · doi:10.3390/rs10010130 · Cited by 29
Human mobility in bike-sharing systems: Structure of local and non-local dynamics
Loaiza-Monsalve, D., & Riascos, A. P. (2019) · PLoS ONE · doi:10.1371/journal.pone.0213106 · Cited by 29
Spatial inequalities and cities: A review
Sarkar, S., Cottineau, C., & Wolf, L. J. (2024) · Environment and Planning B Urban Analytics and City Science · doi:10.1177/23998083241263422 · Cited by 29
Knowledge politics in the smart city: A case study of strategic urban planning in Cambridge, UK
Nochta, T., Wahby, N., & Schooling, J. M. (2021) · Data & Policy · doi:10.1017/dap.2021.28 · Cited by 28
Scenario prediction of emerging coastal city using CA modeling under different environmental conditions: a case study of Lingang New City, China
Feng, Y., & Liu, Y. (2016) · Environmental Monitoring and Assessment · doi:10.1007/s10661-016-5558-y · Cited by 28
Urban data and city dashboards
Kitchin, R., & McArdle, G. (2017) · Routledge eBooks · doi:10.4324/9781315407388-9 · Cited by 28
Paradoxical impact of sprawling intra-Urban Heat Islets: Reducing mean surface temperatures while enhancing local extremes
Shreevastava, A., Bhalachandran, S., McGrath, G., Huber, M. S., & Rao, P. S. C. (2019) · Scientific Reports · doi:10.1038/s41598-019-56091-w · Cited by 29
Spatial interactions in urban scaling laws
Altmann, E. G. (2020) · PLoS ONE · doi:10.1371/journal.pone.0243390 · Cited by 29
Scaling laws in intra-urban systems and over time at the district level in Shanghai, China
Xu, G., Xu, Z., Gu, Y., Lei, W., Pan, Y., Liu, J., & Jiao, L. (2020) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2020.125162 · Cited by 28
Waste-to-Energy Framework: An intelligent energy recycling management
Kaya, K., Ak, E., Yaslan, Y., & Oktuğ, S. (2021) · Sustainable Computing Informatics and Systems · doi:10.1016/j.suscom.2021.100548 · Cited by 28
The Image of the Smart City: New Challenges
Borruso, G., & Balletto, G. (2022) · Urban Science · doi:10.3390/urbansci6010005 · Cited by 28
Agent-based modeling of urban exposome interventions: prospects, model architectures, and methodological challenges
Sonnenschein, T., Scheider, S., de Wit, G. A., Tonne, C. C., & Vermeulen, R. C. H. (2022) · Exposome · doi:10.1093/exposome/osac009 · Cited by 28
Towards a Social-Ecological Urbanism: Co-Producing Knowledge through Design in the Albano Resilient Campus Project in Stockholm
Aalto, H. E., Marcus, L., & Torsvall, J. (2018) · Sustainability · doi:10.3390/su10030717 · Cited by 31
The circularity of the urban ecosystem material productivity: The transformation of biomass into technomass in Southern Patagonia
Inostroza, L. (2018) · Sustainable Cities and Society · doi:10.1016/j.scs.2018.03.001 · Cited by 28
Balancing sustainability and security: A review of 5G and IoT in smart cities
Aldehim, G., Khan, S., Shahzad, T., Khan, M. A., Ghadi, Y., Jiang, W.-W., Mazhar, T., & Hamam, H. (2025) · Digit. Commun. Networks · doi:10.1016/j.dcan.2025.06.007 · Cited by 24
Viewpoint: Integrated urban modeling: Past, present, and future
Miller, E. J. (2018) · Journal of Transport and Land Use · doi:10.5198/jtlu.2018.1273 · Cited by 27
Power and Place in Etruria
Stoddart, S. (2020) · Cambridge University Press eBooks · doi:10.1017/9781139043687 · Cited by 29
Complex networks to understand the past: the case of roads in Bourbon Spain
Pablo-Martí, F., Pardo, A., & Sánchez, Á. (2020) · Cliometrica · doi:10.1007/s11698-020-00218-x · Cited by 30
Commuting network effect on urban wealth scaling
Alves, L. G. A., Diego Rybski, A., & Ribeiro, H. V. (2021) · Scientific Reports · doi:10.1038/s41598-021-02327-7 · Cited by 26
NEET Rural–Urban Ecosystems: The Role of Urban Social Innovation Diffusion in Supporting Sustainable Rural Pathways to Education, Employment, and Training
Erdoğan, E., Flynn, P., Nasya, B., Paabort, H., & Lendzhova, V. (2021) · Sustainability · doi:10.3390/su132112053 · Cited by 27
A Geometric Classification of World Urban Road Networks
Badhrudeen, M., Derrible, S., Verma, T., Kermanshah, A., & Furno, A. (2022) · Urban Science · doi:10.3390/urbansci6010011 · Cited by 27
Heri-Graphs: A Dataset Creation Framework for Multi-Modal Machine Learning on Graphs of Heritage Values and Attributes with Social Media
Bai, N., Nourian, P., Luo, R., & Roders, A. P. (2022) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi11090469 · Cited by 31
Why plans matter for cities
Lai, S. (2017) · Cities · doi:10.1016/j.cities.2017.10.014 · Cited by 29
Thinking about complexity and planning
Friedmann, J. R. P. (2019) · International Planning Studies · doi:10.1080/13563475.2018.1517594 · Cited by 27
Why Archaeology Is Necessary for a Theory of Urbanization
Ortman, S. G., Smith, M. E., Lobo, J., & Bettencourt, L. M. A. (2020) · Journal of Urban Archaeology · doi:10.1484/j.jua.5.120914 · Cited by 28
The spatially conscious machine learning model
Kiely, T. J., & Bastian, N. D. (2019) · Statistical Analysis and Data Mining The ASA Data Science Journal · doi:10.1002/sam.11440 · Cited by 26
People and Nature in an Urban World
Girardet, H. (2020) · One Earth · doi:10.1016/j.oneear.2020.02.005 · Cited by 28
Contrasting social and non-social sources of predictability in human mobility
Chen, Z., Kelty, S., Evsukoff, A. G., Welles, B. F., Bagrow, J. P., de Menezes, R. P., & Ghoshal, G. (2022) · Nature Communications · doi:10.1038/s41467-022-29592-y · Cited by 25
New Lens to Reveal the Street Interface. A Morphological-Visual Perception Methodological Contribution for Decoding the Public/Private Edge of Arterial Streets
Mushayt, N. S. A., Cin, F. D., & Proença, S. B. (2021) · Sustainability · doi:10.3390/su132011442 · Cited by 26
Understanding the urban scaling of urban land with an internal structure view to characterize China’s urbanization
Lei, W., Jiao, L., & Xu, G. (2021) · Land Use Policy · doi:10.1016/j.landusepol.2021.105781 · Cited by 26
Urban Sustainability: Integrating Socioeconomic and Environmental Data for Multi-Objective Assessment
Xie, Y., Liu, C., Chang, S., & Jiang, B. (2022) · Sustainability · doi:10.3390/su14159142 · Cited by 26
Rivers as integration devices in cities
Abshirini, E., & Koch, D. (2016) · City Territory and Architecture · doi:10.1186/s40410-016-0030-4 · Cited by 26
Generating and Analyzing Spatial Social Networks
Alizadeh, M., Cioffi‐Revilla, C. A., & Crooks, A. T. (2016) · Computational and Mathematical Organization Theory · doi:10.1007/s10588-016-9232-2 · Cited by 26
Transportation in Agent-Based Urban Modelling
Wise, S., Crooks, A. T., & Batty, M. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-51957-9_8 · Cited by 26
Self-citation
Learning from community indicators movements: Towards a citizen-powered urban data revolution
Pires, S. M., Magee, L., & Holden, M. (2017) · Environment and Planning C Politics and Space · doi:10.1177/2399654417691512 · Cited by 26
Social Network Sites and Knowledge Transfer: An Urban Perspective
Tranos, E. (2020) · Journal of Planning Literature · doi:10.1177/0885412220921526 · Cited by 26
Underlying rules of evolutionary urban systems in Africa
Xu, G., Zhu, M., Чэн, Б., Salem, M., Xu, Z., Cobbinah, P. B., Li, X., Sumari, N. S., Zhang, X., Jiao, L., et al. (2025) · Nature Cities · doi:10.1038/s44284-025-00208-y · Cited by 25
Calibration of a density-based model of urban morphogenesis
Raimbault, J. (2018) · PLoS ONE · doi:10.1371/journal.pone.0203516 · Cited by 25
‘Downtown Is for People’: The street-level approach in Jane Jacobs' legacy and its resonance in the planning debate within the complexity theory of cities
Perrone, C. (2019) · Cities · doi:10.1016/j.cities.2018.12.023 · Cited by 25
Emergent self-similarity and scaling properties of fractal intra-urban heat islets for diverse global cities
Shreevastava, A., Rao, P. S. C., & McGrath, G. (2019) · Physical review. E · doi:10.1103/physreve.100.032142 · Cited by 25
A multilayer mobility network approach to inferring urban structures using shared mobility and taxi data
Zhang, J., Liu, X., & Senousi, A. M. (2021) · Transactions in GIS · doi:10.1111/tgis.12817 · Cited by 25
Geographical Network Analysis
Uitermark, J., & van Meeteren, M. (2021) · Tijdschrift voor Economische en Sociale Geografie · doi:10.1111/tesg.12480 · Cited by 28
Evolving settlement patterns, spatial interaction and the socio-political organisation of late Prepalatial south-central Crete
Paliou, E., & Bevan, A. (2016) · Journal of Anthropological Archaeology · doi:10.1016/j.jaa.2016.04.006 · Cited by 25
Cities in Disequilibrium
Batty, M. (2017) · Understanding complex systems · doi:10.1007/978-3-319-42424-8_6 · Cited by 25
Self-citation
Catch Me if You Can: Workplace Mobility and Big Data
Pajević, F., & Shearmur, R. (2017) · Journal of Urban Technology · doi:10.1080/10630732.2017.1334855 · Cited by 25
The case for microsimulation frameworks for integrated urban models
Miller, E. J. (2018) · Journal of Transport and Land Use · doi:10.5198/jtlu.2018.1257 · Cited by 25
Demarcating geographic regions using community detection in commuting networks with significant self-loops
He, M., Glasser, J., Pritchard, N., Bhamidi, S., & Kaza, N. (2020) · PLoS ONE · doi:10.1371/journal.pone.0230941 · Cited by 25
On the relation between transversal and longitudinal scaling in cities
Ribeiro, F. L., Meirelles, J., Netto, V. M., Neto, C. R., & Baronchelli, A. (2020) · PLoS ONE · doi:10.1371/journal.pone.0233003 · Cited by 26
Delineating the perceived functional regions of London from commuting flows
Shen, Y., & Batty, M. (2018) · Environment and Planning A Economy and Space · doi:10.1177/0308518x18786253 · Cited by 24
Self-citation
A multicriteria optimization framework for the definition of the spatial granularity of urban social media analytics
de Andrade, S. C., Restrepo‐Estrada, C., Nunes, L. H., Morales, C. A., Estrella, J. C., Delbem, A. C. B., & de Albuquerque, J. P. (2020) · International Journal of Geographical Information Systems · doi:10.1080/13658816.2020.1755039 · Cited by 24
Contextual Influences on Political Behavior in Cities: Toward Urban Electoral Geography
Weaver, R. C. (2014) · Geography Compass · doi:10.1111/gec3.12186 · Cited by 25
Effective Urban Structure Inference from Traffic Flow Dynamics
Sarkar, S., Chawla, S., Ahmad, S., Srivastava, J., Hammady, H., Filali, F., Znaidi, W., & Borge‐Holthoefer, J. (2017) · IEEE Transactions on Big Data · doi:10.1109/tbdata.2016.2641003 · Cited by 24
Geographic information science II: Mesogeography
Miller, H. J. (2017) · Progress in Human Geography · doi:10.1177/0309132517712154 · Cited by 24
The Scale Effect on Spatial Interaction Patterns: An Empirical Study Using Taxi O-D data of Beijing and Shanghai
Zhang, S., Zhu, D., Yao, X., Cheng, X., He, H., & Liu, Y. (2018) · IEEE Access · doi:10.1109/access.2018.2869378 · Cited by 24
Applying a Systems Perspective on the Notion of the Smart City
Colding, J., Wallhagen, M., Sörqvist, P., Marcus, L., Hillman, K. M., Samuelsson, K., & Barthel, S. (2020) · Smart Cities · doi:10.3390/smartcities3020022 · Cited by 26
Spatial inequality of bus transit dependence on urban streets and its relationships with socioeconomic intensities: A tale of two megacities in China
Liu, C., & Duan, D. (2020) · Journal of Transport Geography · doi:10.1016/j.jtrangeo.2020.102768 · Cited by 24
Organizing for Smart City Development: Research at the crossroads. Introduction to the Special Issue
Mora, L., Appio, F. P., Foss, N. J., Gault, D. A., & Zhang, X. (2023) · Organization Studies · doi:10.1177/01708406231197815 · Cited by 29
On critical dynamics and thermodynamic efficiency of urban transformations
Crosato, E., Nigmatullin, R., & Prokopenko, M. (2018) · Royal Society Open Science · doi:10.1098/rsos.180863 · Cited by 21
Sociotype and cultural evolution: The acceleration of cultural change alongside industrial revolutions
Marijuán, P. C., & Navarro, J. (2020) · Biosystems · doi:10.1016/j.biosystems.2020.104170 · Cited by 24
Comparative quantification of local climate regulation by green and blue urban areas in cities across Europe
Goldenberg, R., Kalantari, Z., & Destouni, G. (2021) · Scientific Reports · doi:10.1038/s41598-021-03140-y · Cited by 23
Reconciling big data and thick data to advance the new urban science and smart city governance
Hong, A., Baker, L., Prieto-Curiel, R., Duminy, J., Buswala, B., Guan, C., & Ravindranath, D. (2022) · Journal of Urban Affairs · doi:10.1080/07352166.2021.2021085 · Cited by 27
Green Infrastructure and Urban-Renewal Simulation for Street Tree Design Decision-Making: Moderating Demands of Stormwater Management, Sunlight and Visual Aesthetics
Langenheim, N., & White, M. R. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph19138220 · Cited by 23
Connecting intercity mobility with urban welfare
Mimar, S., Soriano‐Paños, D., Kirkley, A., Barbosa, H., Sadilek, A., Arenas, À., Gómez‐Gardeñes, J., & Ghoshal, G. (2022) · PNAS Nexus · doi:10.1093/pnasnexus/pgac178 · Cited by 24
Revealing intra-urban hierarchical spatial structure through representation learning by combining road network abstraction model and taxi trajectory data
Hu, S. H., Gao, S., Luo, W. P., Wu, L., Li, T., Xu, Y., & Zhang, Z. (2023) · Annals of GIS · doi:10.1080/19475683.2023.2241526 · Cited by 23
Supporting Mobile Cloud Computing in Smart Cities via Randomized Algorithms
Mazza, D., Pagès‐Bernaus, A., Tarchi, D., Juan, A. A., & Corazza, G. E. (2016) · IEEE Systems Journal · doi:10.1109/jsyst.2016.2578358 · Cited by 23
Introduction to ‘Planning Support Science for Smarter Urban Futures’
Geertman, S. C. M., Allan, A., Pettit, C. J., & Stillwell, J. (2017) · Lecture notes in geoinformation and cartography · doi:10.1007/978-3-319-57819-4_1 · Cited by 23

Authors: Batty, M.
Corresponding author: Batty, Michael
ORCID: Batty, Michael
Venue: The MIT Press eBooks
Publisher: The MIT Press
Published: 2013-11-01
DOI: 10.7551/mitpress/9399.001.0001
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

The New Science of Cities

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Citations

Cites

Cited by

Related

Metadata

Record

About these checks