Gravity model explained by the radiation model on a population landscape

The diaspora model for human migration

Migration's impact spans various social dimensions, including demography, sustainability, politics, economy, and gender disparities. Yet, the decision-making process behind migrants choosing their destination remains elusive. Existing models primarily rely on population size and travel distance to explain the spatial patterns of migration flows, overlooking significant population heterogeneities. Paradoxically, migrants often travel long distances and to smaller destinations if their diaspora is present in those locations. To address this gap, we propose the diaspora model of migration, incorporating intensity (the number of people moving to a country), and assortativity (the destination within the country). Our model considers only the existing diaspora sizes in the destination country, influencing the probability of migrants selecting a specific residence. Despite its simplicity, our model accurately reproduces the observed stable flow and distribution of migration in Austria (postal code level) and US metropolitan areas, yielding precise estimates of migrant inflow at various geographic scales. Given the increase in international migrations, this study enlightens our understanding of migration flow heterogeneities, helping design more inclusive, integrated cities.

On an Aggregated Estimate for Human Mobility Regularities through Movement Trends and Population Density

This article introduces an analytical framework that interprets individual measures of entropy-based mobility derived from mobile phone data. We explore and analyze two widely recognized entropy metrics: random entropy and uncorrelated Shannon entropy. These metrics are estimated through collective variables of human mobility, including movement trends and population density. By employing a collisional model, we establish statistical relationships between entropy measures and mobility variables. Furthermore, our research addresses three primary objectives: firstly, validating the model; secondly, exploring correlations between aggregated mobility and entropy measures in comparison to five economic indicators; and finally, demonstrating the utility of entropy measures. Specifically, we provide an effective population density estimate that offers a more realistic understanding of social interactions. This estimation takes into account both movement regularities and intensity, utilizing real-time data analysis conducted during the peak period of the COVID-19 pandemic.

Latent sub-structural resilience mechanisms in temporal human mobility networks during urban flooding

In studying resilience in temporal human networks, relying solely on global network measures would be inadequate; latent sub-structural network mechanisms need to be examined to determine the extent of impact and recovery of these networks during perturbations, such as urban flooding. In this study, we utilize high-resolution aggregated location-based data to construct temporal human mobility networks in Houston in the context of the 2017 Hurricane Harvey. We examine motif distribution, motif persistence, temporal stability, and motif attributes to reveal latent sub-structural mechanisms related to the resilience of human mobility networks during disaster-induced perturbations. The results show that urban flood impacts persist in human mobility networks at the sub-structure level for several weeks. The impact extent and recovery duration are heterogeneous across different network types. Also, while perturbation impacts persist at the sub-structure level, global topological network properties indicate that the network has recovered. The findings highlight the importance of examining the microstructures and their dynamic processes and attributes in understanding the resilience of temporal human mobility networks (and other temporal networks). The findings can also provide disaster managers, public officials, and transportation planners with insights to better evaluate impacts and monitor recovery in affected communities.

Spatial Patterns and Determinants of Inter-county Migration in California: A Multilevel Gravity Model Approach

Understanding migration patterns and their determinants is crucial for population estimation and resource allocation for policymakers. Utilizing residential mobility data collected by the Department of Motor Vehicles, this present study provides a spatiotemporal analysis of inter-county migration in California for the period 2014-2021. We use multilevel gravity models to address the hierarchical nature of migration data and the effects of migration flows sharing common origins, destinations, and regions, providing a substantively complete examination of push and pull forces affecting migration. Our findings show that populous counties in Southern California and the San Francisco Bay Area represent the largest origins and destinations, despite a systemic decline in intra-state migration. Migration is strongly associated with population size, geographic proximity (i.e., distance and contiguity), job availability, and industrial composition similarity between origins and destinations. Our findings also highlight the contribution of shared origins, destinations, and regions in explaining the systematic variation of migration flows. Counties vary more in the number of migrants they attract than the number they send. The purposed multilevel modeling approach is useful in identifying place-specific influences on migration and in improving estimation accuracy.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11113-023-09782-2.

Multiscale Accessibility—A New Perspective of Space Structuration

Spatial accessibility is fundamentally related to the functional, economic and social performances of cities and geographical systems and, therefore, constitutes an essential aspect for spatial planning. Despite the significant progress made in accessibility research, little attention is given to the central role of accessibility in space organization and structuration. This study aimed to fill this gap. Based on an intensive literature review, our work shows the critical role of accessibility in space organization at different scales and sizes, starting from the basic concept of accessibility and its foundations in the classical locational theories and further to the methods and theories at the forefront of research. These processes also point to a unique contribution of multiscale accessibility in space structuration. Accordingly, we offer a conceptual framework to describe the multiscale process of space structuration with respect to local-urban, regional and national scales. We believe this framework may help in studying space and, more importantly, in understanding space. We hope this perspective forms an additional tier at the conceptual and methodological levels concerning accessibility and spatial organization and will encourage empirical studies in light of the suggested view.

A city of cities: Measuring how 15-minutes urban accessibility shapes human mobility in Barcelona

As cities expand, human mobility has become a central focus of urban planning and policy making to make cities more inclusive and sustainable. Initiatives such as the "15-minutes city" have been put in place to shift the attention from monocentric city configurations to polycentric structures, increasing the availability and diversity of local urban amenities. Ultimately they expect to increase local walkability and increase mobility within residential areas. While we know how urban amenities influence human mobility at the city level, little is known about spatial variations in this relationship. Here, we use mobile phone, census, and volunteered geographical data to measure geographic variations in the relationship between origin-destination flows and local urban accessibility in Barcelona. Using a Negative Binomial Geographically Weighted Regression model, we show that, globally, people tend to visit neighborhoods with better access to education and retail. Locally, these and other features change in sign and magnitude through the different neighborhoods of the city in ways that are not explained by administrative boundaries, and that provide deeper insights regarding urban characteristics such as rental prices. In conclusion, our work suggests that the qualities of a 15-minutes city can be measured at scale, delivering actionable insights on the polycentric structure of cities, and how people use and access this structure.

Gravity model in dockless bike-sharing systems within cities

Due to previous technical challenges with the collection of data on riding behaviors, there have only been a few studies focusing on patterns and regularities of biking traffic, which are crucial to understand to help achieve a greener and more sustainable future urban development. Recently, with the booming of the sharing economy, and the development of the Internet of Things (IoT) and mobile payment technology, dockless bike-sharing systems that record information for every trip provide us with a unique opportunity to study the patterns of biking traffic within cities. We first reveal a spatial scaling relation between the cumulative volume of riding activities and the corresponding distance to the city center, and a power law distribution on the volume of biking flows between fine-grained locations in both Beijing and Shanghai. We validate the effectiveness of the general gravity model on predicting biking traffic at fine spatial resolutions, where population-related parameters are less than unity, indicating that smaller populations are relatively more important per capita in generating biking traffic. We then further study the impacts of spatial scale on the gravity model and reveal that the distance-related parameter grows in a similar way as population-related parameters when the spatial scale of the locations increases. In addition, the flow patterns of some special locations (sources and sinks) that cannot be fully explained by the gravity model are studied.

Predicting highway freight transportation networks using radiation models

Highway freight transportation (HFT) plays an important role in the economic activities. Predicting HFT networks is not only scientifically significant in the understanding of the mechanism governing the formation and dynamics of these networks, but also of practical significance in highway planning and design for policymakers and truck allocation and route planning for logistic companies. In this work we apply parameter-free radiation models to predict the HFT network in mainland China and assess their predictive performance using metrics based on links and fluxes, which can be done in reference to the real directed and weighted HFT network between 338 Chinese cities constructed from about 15.06 million truck transportation records in five months. It is found that the radiation models exhibit relatively high accuracy in predicting links but low accuracy in predicting fluxes on links. Similar to gravity models, radiation models also suffer difficulty in predicting long-distance links and the fluxes on them. Nevertheless, the radiation models perform well in reproducing several scaling laws of the HFT network. The adoption of population or gross domestic product in the model has a minor impact on the results, and replacing the geographic distance by the path length taken by most truck drivers does not improve the results.

Research on the Spatial Structure of County Greenway Network Based on Gravitation-Resistance Measurement—A Case Study of Ning’an in China

The ecological value, cultural value, economic value and industrial value of the county space, where a variety of human activities and natural ecological processes are carried out, act as the key elements considered in county spatial planning. However, there is a lack of carrying space for integrating these values in the actual Chinese county construction. In this article, the construction of a county greenway network is based on multiple needs, such as ecological protection, characteristic landscape, leisure and recreation. The ecological, cultural and economic values of resources are taken as the basis of identifying a greenway network. We establish the gravitation-resistance model to measure network flow based on the attraction and resistance between resources. In particular, by means of network flow analysis and the geographic information system (GIS), the resistance and gravity are assigned to the resources and landscapes, respectively. The attraction between elements is then measured using the gravitation-resistance model. The distribution of resources and the trend of integration are analyzed by the combination of the centrality of resources and the ratio of supply to demand. Based on the analysis results of network flow, the paper puts forward a strategy for developing a county greenway network, and improves the scientific evaluation of the spatial resource. It provides a new perspective for the construction of a county greenway network.