A complex system approach to urban planning and development

• Grant number: 16/16987-7
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Start date: April 01, 2017
• End date: October 31, 2018
• Field of knowledge: Physical Sciences and Mathematics - Physics - General Physics
• Agreement: Coordination of Improvement of Higher Education Personnel (CAPES)
• Principal Investigator: Francisco Aparecido Rodrigues
• Grantee: Luiz Gustavo de Andrade Alves
• Host Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil

Abstract

There has been a remarkable increasing in the amount of stored data by private and public companies about urban systems. On one hand, these huge amounts of data enable a detailed historical review of the processes under investigation; on the other hand, this excess of data makes harder to extract summarized information and also to make good decisions supported by well-established empirical facts. Cities are complex systems in which the equations governing their dynamics depend on several social, economical, and environmental factors. A theory explaining how these attributes of cities influence cities performance would help to inform urban planning and development. It is clear that this is a timely and on the rise theme with many challenges that deserve attention from scientific community. In order to understand, investigate and extract patterns from cities, researchers usually need a wide range of skills such as those from Statistical Physics, Mathematics, Statistics, and Computer Science. In the course of this project, we intend to investigate several aspects of urban systems by employing the Statistical Physics and omputer Science framework. Specifically, the problems that must be addressed in this project are: i) The role of commuters in urban scaling; ii) Long-term migrations and its effects on urban scaling; iii) What are the mechanism that generate the fluctuations in the scaling laws? iv) How does population density affect urban indicators? v) Can the spread of crime be modelled by epidemic models? vi) Modelling urban systems via complex networks and multilayer networks. We believe that these studies may have potential applications in the allocation of new policies and resource in the context of urban planning and development. (AU)

Scientific publications

(6)

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

SPADON, GABRIEL; DE CARVALHO, ANDRE C. P. L. F.; RODRIGUES-JR, JOSE F.; ALVES, LUIZ G. A.. Reconstructing commuters network using machine learning and urban indicators. SCIENTIFIC REPORTS, v. 9, AUG 13 2019. (16/17078-0, 17/08376-0, 19/04461-9, 13/07375-0, 16/16987-7, 16/18615-0, 14/25337-0)

RIBEIRO, V, HAROLDO; ALVES, LUIZ G. A.; MARTINS, ALVARO F.; LENZI, ERVIN K.; PERC, MATJAZ. The dynamical structure of political corruption networks. JOURNAL OF COMPLEX NETWORKS, v. 6, n. 6, p. 989-1003, DEC 2018. (16/16987-7)

ALVES, LUIZ G. A.; RIBEIRO, V, HAROLDO; RODRIGUES, FRANCISCO A.. Crime prediction through urban metrics and statistical learning. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, v. 505, p. 435-443, SEP 1 2018. (13/07375-0, 16/16987-7, 16/25682-5)

ALVES, LUIZ G. A.; MANGIONI, GIUSEPPE; CINGOLANI, ISABELLA; RODRIGUES, FRANCISCO APARECIDO; PANZARASA, PIETRO; MORENO, YAMIR. The nested structural organization of the worldwide trade multi-layer network. SCIENTIFIC REPORTS, v. 9, FEB 27 2019. (13/07375-0, 16/16987-7, 16/25682-5)

ALVES, LUIZ G. A.; ANDRADE, JR., JOSE S.; HANLEY, QUENTIN S.; RIBEIRO, HAROLDO V.. The hidden traits of endemic illiteracy in cities. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, v. 515, p. 566-574, FEB 1 2019. (16/16987-7)

ALVES, LUIZ G. A.; MANGIONI, GIUSEPPE; RODRIGUES, FRANCISCO A.; PANZARASA, PIETRO; MORENO, YAMIR. Unfolding the Complexity of the Global Value Chain: Strength and Entropy in the Single-Layer, Multiplex, and Multi-Layer International Trade Networks. Entropy, v. 20, n. 12, DEC 2018. (13/07375-0, 16/16987-7, 16/25682-5)