The Levy Flight of Cities: Analyzing Social-Economical Trajectories with Auto-Embedding

• URL: http://arxiv.org/abs/2112.14594v1
• Date: Wed, 29 Dec 2021 15:06:26 GMT
• Title: The Levy Flight of Cities: Analyzing Social-Economical Trajectories with Auto-Embedding
• Authors: Linfang Tian and Kai Zhao and Jiaming Yin and Huy Vo and Weixiong Rao
• Abstract summary: It has been found that human mobility exhibits random patterns following the Levy flight, where human movement contains many short flights and some long flights. In this paper, we study the social-economical development trajectories of urban cities.
• Score: 4.874892390548224
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: It has been found that human mobility exhibits random patterns following the Levy flight, where human movement contains many short flights and some long flights, and these flights follow a power-law distribution. In this paper, we study the social-economical development trajectories of urban cities. We observe that social-economical movement of cities also exhibit the Levy flight characteristics. We collect the social and economical data such as the population, the number of students, GDP and personal income, etc. from several cities. Then we map these urban data into the social and economical factors through a deep-learning embedding method Auto-Encoder. We find that the social-economical factors of these cities can be fitted approximately as a movement pattern of a power-law distribution. We use the Stochastic Multiplicative Processes (SMP) to explain such movement, where in the presence of a boundary constraint, the SMP leads to a power law distribution. It means that the social-economical trajectories of cities also follow a Levy flight pattern, where some years have large changes in terms of social-economical development, and many years have little changes.

Related papers

• MetaUrban: An Embodied AI Simulation Platform for Urban Micromobility [52.0930915607703]
  Recent advances in Robotics and Embodied AI make public urban spaces no longer exclusive to humans. Micromobility enabled by AI for short-distance travel in public urban spaces plays a crucial component in the future transportation system. We present MetaUrban, a compositional simulation platform for the AI-driven urban micromobility research.
  arXiv  Detail & Related papers  (2024-07-11T17:56:49Z)
• Urban highways are barriers to social ties [0.0]
  We show that urban highways are associated with decreased social connectivity. This barrier effect is especially strong for short distances and consistent with historical cases of highways that were built to purposefully disrupt or isolate Black neighborhoods. Our study can inform reparative planning for an evidence-based reduction of spatial inequality.
  arXiv  Detail & Related papers  (2024-04-17T17:49:08Z)
• Prediction of Transportation Index for Urban Patterns in Small and Medium-sized Indian Cities using Hybrid RidgeGAN Model [0.0]
  This research addresses several challenges in predicting the urban transportation index for small and medium-sized Indian cities. A hybrid framework based on Kernel Ridge Regression (KRR) and CityGAN is introduced to predict transportation index. The proposed hybrid pipeline, we call it RidgeGAN model, can evaluate the sustainability of urban sprawl.
  arXiv  Detail & Related papers  (2023-06-09T15:05:40Z)
• Urban form and COVID-19 cases and deaths in Greater London: an urban morphometric approach [63.29165619502806]
  The COVID-19 pandemic generated a considerable debate in relation to urban density. This is an old debate, originated in mid 19th century's England with the emergence of public health and urban planning disciplines. We describe urban form at individual building level and then aggregate information for official neighbourhoods.
  arXiv  Detail & Related papers  (2022-10-16T10:01:10Z)
• JKOnet: Proximal Optimal Transport Modeling of Population Dynamics [69.89192135800143]
  We propose a neural architecture that combines an energy model on measures, with (small) optimal displacements solved with input convex neural networks (ICNN) We demonstrate the applicability of our model to explain and predict population dynamics.
  arXiv  Detail & Related papers  (2021-06-11T12:30:43Z)
• Methodological Foundation of a Numerical Taxonomy of Urban Form [62.997667081978825]
  We present a method for numerical taxonomy of urban form derived from biological systematics. We derive homogeneous urban tissue types and, by determining overall morphological similarity between them, generate a hierarchical classification of urban form. After framing and presenting the method, we test it on two cities - Prague and Amsterdam.
  arXiv  Detail & Related papers  (2021-04-30T12:47:52Z)
• Smart Urban Mobility: When Mobility Systems Meet Smart Data [55.456196356335745]
  Cities around the world are expanding dramatically, with urban population growth reaching nearly 2.5 billion people in urban areas and road traffic growth exceeding 1.2 billion cars by 2050. The economic contribution of the transport sector represents 5% of the GDP in Europe and costs an average of US $482.05 billion in the U.S.
  arXiv  Detail & Related papers  (2020-05-09T13:53:01Z)
• City limits in the age of smartphones and urban scaling [0.0]
  Urban planning still lacks appropriate standards to define city boundaries across urban systems. ICT provide the potential to portray more accurate descriptions of the urban systems. We apply computational techniques over a large volume of mobile phone records to define urban boundaries.
  arXiv  Detail & Related papers  (2020-05-06T17:31:21Z)
• Socio-economic, built environment, and mobility conditions associated with crime: A study of multiple cities [9.78342936850961]
  We propose a Bayesian model to explore how crime is related to socio-economic factors. We find that the combined use of socio-economic conditions, mobility information and physical characteristics of the neighbourhood effectively explain the emergence of crime. We show that the socio-ecological factors of neighbourhoods relate to crime very differently from one city to another.
  arXiv  Detail & Related papers  (2020-04-13T08:36:59Z)
• Socioeconomic correlations of urban patterns inferred from aerial images: interpreting activation maps of Convolutional Neural Networks [0.10152838128195464]
  Urbanisation is a great challenge for modern societies, promising better access to economic opportunities while widening socioeconomic inequalities. Here we close this gap by predicting socioeconomic status across France from aerial images and interpreting class activation mappings in terms of urban topology. These results pave the way to build interpretable models, which may help to better track and understand urbanisation and its consequences.
  arXiv  Detail & Related papers  (2020-04-10T04:57:20Z)
• Measuring Spatial Subdivisions in Urban Mobility with Mobile Phone Data [58.720142291102135]
  By 2050 two thirds of the world population will reside in urban areas. This growth is faster and more complex than the ability of cities to measure and plan for their sustainability. To understand what makes a city inclusive for all, we define a methodology to identify and characterize spatial subdivisions.
  arXiv  Detail & Related papers  (2020-02-20T14:37:46Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.