Takahiro Yabe

Takahiro Yabe
Massachusetts Institute of Technology | MIT · Institute for Data Systems and Society

PhD

About

62
Publications
10,176
Reads
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666
Citations
Citations since 2017
58 Research Items
664 Citations
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Introduction
Takahiro (Taka) Yabe currently works at the MIT Institute for Data, Systems, and Society and the Media lab Human Dynamics Group. Taka conducts research in urban socioeconomic resilience using large scale mobility datasets and complex network models.

Publications

Publications (62)
Article
Large-scale disasters often trigger mass evacuation due to significant damages to urban systems. Understanding the evacuation and reentry (return) process of affected individuals is crucial for disaster management. Moreover, measuring the heterogeneity in the individuals' post-disaster behavior with respect to their socio-economic characteristics i...
Article
Despite the rising importance of enhancing community resilience to disasters, our understandings on when, how and why communities are able to recover from such extreme events are limited. Here, we study the macroscopic population recovery patterns in disaster affected regions, by observing human mobility trajectories of over 1.9 million mobile phon...
Article
Cities are complex systems comprised of socioeconomic systems relying on critical services delivered by multiple physical infrastructure networks. Due to interdependencies between social and physical systems, disruptions caused by natural hazards may cascade across systems, amplifying the impact of disasters. Despite the increasing threat posed by...
Article
Full-text available
With rapid urbanization and increasing climate risks, enhancing the resilience of urban systems has never been more important. Despite the availability of massive datasets of human behavior (e.g., mobile phone data, satellite imagery), studies on disaster resilience have been limited to using static measures as proxies for resilience. However, stat...
Article
Inter-business networks are important components of business dynamics and spatial clusters. Extensive literature proclaims the existence of a variety of networks and benefits of diversity within. However, the literature falls short to exhibit the subsistence of connections between economic activities which invariably contribute towards entry decisi...
Article
Accessibility is widely considered as the most crucial benefit of any transportation system. Low accessibility may cause compromise on living conditions, low economic growth, high unemployment, social seclusion, and long-term social inequalities. In developing countries of Sub-Saharan Africa, surveys fail to keep up with the pace of rapid urbanizat...
Preprint
Full-text available
Recurring outbreaks of COVID-19 have posed enduring effects on global society, which calls for a predictor of pandemic waves using various data with early availability. Existing prediction models that forecast the first outbreak wave using mobility data may not be applicable to the multiwave prediction, because the evidence in the USA and Japan has...
Preprint
Full-text available
Diversity of physical encounters and social interactions in urban environments are known to spur economic productivity and innovation in cities, while also to foster social capital and resilience of communities. However, mobility restrictions during the pandemic have forced people to substantially reduce urban physical encounters, raising questions...
Preprint
Diversity of physical encounters and social interactions in urban environments are known to spur economic productivity and innovation in cities, while also to foster social capital and resilience of communities. However, mobility restrictions during the pandemic have forced people to substantially reduce urban physical encounters, raising questions...
Article
Rapid urbanization and climate change trends, intertwined with complex interactions of various social, economic, and political factors, have resulted in an increase in the frequency and intensity of disaster events. While regions around the world face urgent demands to prepare for, respond to, and to recover from such disasters, large-scale locatio...
Preprint
Full-text available
People flow data are utilized in diverse fields such as urban and commercial planning and disaster management. However, people flow data collected from mobile phones, such as using global positioning system and call detail records data, are difficult to obtain because of privacy issues. Even if the data were obtained, they would be difficult to han...
Article
Full-text available
Quantifying the topological similarities of different parts of urban road networks (URNs) enables us to understand the urban growth patterns. While conventional statistics provide useful information about characteristics of either a single node’s direct neighbors or the entire network, such metrics fail to measure the similarities of subnetworks co...
Preprint
In recent geospatial research, the importance of modeling large-scale human mobility data via self-supervised learning is rising, in parallel with progress in natural language processing driven by self-supervised approaches using large-scale corpora. Whereas there are already plenty of feasible approaches applicable to geospatial sequence modeling...
Article
COVID-19 has disrupted the global economy and well-being of people at an unprecedented scale and magnitude. To contain the disease, an effective early warning system that predicts the locations of outbreaks is of crucial importance. Studies have shown the effectiveness of using large-scale mobility data to monitor the impacts of non-pharmaceutical...
Preprint
Full-text available
Rapid urbanization and climate change trends are intertwined with complex interactions of various social, economic, and political factors. The increased trends of disaster risks have recently caused numerous events, ranging from unprecedented category 5 hurricanes in the Atlantic Ocean to the COVID-19 pandemic. While regions around the world face u...
Preprint
Full-text available
Increasingly available high-frequency location datasets derived from smartphones provide unprecedented insight into trajectories of human mobility. These datasets can play a significant and growing role in informing preparedness and response to natural disasters. However, limited tools exist to enable rapid analytics using mobility data, and tend n...
Preprint
Full-text available
Location data obtained from smartphones is increasingly finding use cases in disaster risk management. Where traditionally, CDR has provided the predominant digital footprint for human mobility, GPS data now has immense potential in terms of improved spatiotemporal accuracy, volume, availability, and accessibility. GPS data has already proven inval...
Article
Full-text available
The rapid early spread of COVID-19 in the US was experienced very differently by different socioeconomic groups and business industries. In this study, we study aggregate mobility patterns of New York City and Chicago to identify the relationship between the amount of interpersonal contact between people in urban neighborhoods and the disparity in...
Article
Full-text available
Disaster risk management, including response and recovery, are essential elements of sustainable development. With the recent increase in natural hazards, the importance of techniques to understand, model and predict the evacuation and returning behavior of affected individuals is rising. Studies have found that influence from real world social tie...
Preprint
Full-text available
Cities are complex systems comprised of socioeconomic systems relying on critical services delivered by multiple physical infrastructure networks. Due to interdependencies between social and physical systems, disruptions caused by natural hazards may cascade across systems, amplifying the impact of disasters. Despite the increasing threat posed by...
Preprint
Full-text available
The rapid early spread of COVID-19 in the U.S. was experienced very differently by different socioeconomic groups and business industries. In this study, we study aggregate mobility patterns of New York City and Chicago to identify the relationship between the amount of interpersonal contact between people in urban neighborhoods and the disparity i...
Article
Full-text available
Physical infrastructure networks in diverse urban settlements are designed to be robust and reliable, while the socio-economic systems offer the necessary adaptive capacity at household, city, and regional scales to recover from major service disruptions resulting from disasters. Here, our urban resilience analyses are based on exploring explicit l...
Article
Full-text available
In recent years, extreme shocks, such as natural disasters, are increasing in both frequency and intensity, causing significant economic loss to many cities around the world. Quantifying the economic cost of local businesses after extreme shocks is important for post-disaster assessment and pre-disaster planning. Conventionally, surveys have been t...
Preprint
Full-text available
COVID-19 has disrupted the global economy and well-being of people at an unprecedented scale and magnitude. To contain the disease, an effective early warning system that predicts the locations of outbreaks is of crucial importance. Studies have shown the effectiveness of using large-scale mobility data to monitor the impacts of non-pharmaceutical...
Article
Full-text available
Large-scale mobility data collected from mobile phones provide us with an opportunity to monitor and understand the impacts of non-pharmaceutical interventions during the COVID-19 outbreak with an unprecedented spatio-temporal granularity and scale. While such data has been used in various countries, the changes in mobility patterns in Japan where...
Article
Full-text available
Understanding individual and crowd dynamics in urban environments is critical for numerous applications, such as urban planning, traffic forecasting, and location-based services. However, researchers have developed travel demand models to accomplish this task with survey data that are expensive and acquired at low frequencies. In contrast, emerging...
Preprint
Full-text available
In recent years, extreme shocks, such as natural disasters, are increasing in both frequency and intensity, causing significant economic loss to many cities around the world. Quantifying the economic cost of local businesses after extreme shocks is important for post-disaster assessment and pre-disaster planning. Conventionally, surveys have been t...
Article
This report provides a summary of the 2019 edition of the International Workshop on Prediction of Human Mobility (PredictGIS 2019), which was held in conjunction with ACM SIGSPATIAL 2019, in Chicago, IL on November 5th, 2019.
Preprint
Full-text available
Place embeddings generated from human mobility trajectories have become a popular method to understand the functionality of places. Place embeddings with high spatial resolution are desirable for many applications, however, downscaling the spatial resolution deteriorates the quality of embeddings due to data sparsity, especially in less populated a...
Article
Full-text available
Following publication of the original article [1], the author reported to remove the name from the acknowledgements in the original article.
Preprint
Full-text available
Large mobility datasets collected from various sources have allowed us to observe, analyze, predict and solve a wide range of important urban challenges. In particular, studies have generated place representations (or embeddings) from mobility patterns in a similar manner to word embeddings to better understand the functionality of different places...
Conference Paper
Large mobility datasets collected from various sources have allowed us to observe, analyze, predict and solve a wide range of important urban challenges. In particular, studies have generated place representations (or embeddings) from mobility patterns in a similar manner to word embeddings to better understand the functionality of different places...
Article
Full-text available
Abstract Recent disasters have shown the existence of large variance in recovery trajectories across cities that have experienced similar damage levels. Case studies of such events reveal the high complexity of the recovery process of cities, where inter-city dependencies and intra-city coupling of social and physical systems may affect the outcome...
Conference Paper
Full-text available
Predicting the evacuation decisions of individuals before the disaster strikes is crucial for planning first response strategies. In addition to the studies on post-disaster analysis of evacuation behavior, there are various works that attempt to predict the evacuation decisions beforehand. Most of these predictive methods, however, require real ti...
Preprint
Full-text available
Predicting the evacuation decisions of individuals before the disaster strikes is crucial for planning first response strategies. In addition to the studies on post-disaster analysis of evacuation behavior, there are various works that attempt to predict the evacuation decisions beforehand. Most of these predictive methods, however, require real ti...
Preprint
Full-text available
Despite the rising importance of enhancing community resilience to disasters, our understanding on how communities recover from catastrophic events is limited. Here we study the population recovery dynamics of disaster affected regions by observing the movements of over 2.5 million mobile phone users across three countries before, during and after...
Article
Full-text available
Despite the importance of predicting evacuation mobility dynamics after large scale disasters for effective first response and disaster relief, our general understanding of evacuation behavior remains limited because of the lack of empirical evidence on the evacuation movement of individuals across multiple disaster instances. Here we investigate t...
Article
With the recent rise in frequency and intensity of severe disasters, increasing the resilience of urban systems is an urgent challenge. Local governments need to accurately predict the demand of public services such as gas, water and power after disasters in order to effectively allocate resources for recovery, and also to prevent secondary disaste...
Article
The prediction of human and vehicle mobility in a city is becoming an attracting field. This topic attracts researchers from broad fields including behavioral sciences, where understanding the complexity of the human mobility behavior is one of the hot topic, and also to the industrial partners, who apply such results to many beneficial application...
Preprint
Full-text available
Despite the importance of predicting evacuation mobility dynamics after large scale disasters for effective first response and disaster relief, our general understanding of evacuation behavior remains limited because of the lack of empirical evidence on the evacuation movement of individuals across multiple disaster instances. Here we investigate t...
Conference Paper
This paper is the first work to replicate and simulate urban dynamics by learning individuals' decision-making processes and creating human-like agents from GPS data. We develop a novel agent model by learning from historical data via reinforcement learning techniques. We test our methodology in different scenarios at the citywide level using real...
Article
The prediction of human and vehicle mobility in a city is becoming attracting field. This topic attracts researchers in broad field from the behavioral science, where understanding the complexity of the human mobility behavior is one of the hot topic, to industrial field, which apply the result to many beneficial applications. Recent progress to se...
Conference Paper
Understanding the daily movement of humans in space and time on different granularity levels is of critical value for urban planning, transport management, health care and commercial services. However, population's daily travel behavior data was collected by travel surveys that are infrequent, expensive, and disable to reflect changes in transporta...
Article
Economic loss caused by natural disasters is increasing in many cities around the world. There is an increasing demand for a method that effectively measures the fragility of people flow to appropriately plan the future investment into infrastructure. Conventional methods measure the fragility of urban systems using infrastructure data such as the...
Article
Natural disasters that frequently occur, such as typhoons and earthquakes, heavily affect human activities in urban areas by causing severe congestion and economic loss. Predicting the delay in usual commuting activities of individuals following such disasters is crucial for managing urban systems. We propose a novel method that predicts such delay...
Conference Paper
Mid-level disasters that frequently occur, such as typhoons and earthquakes, heavily affect human activities in urban areas by causing severe congestion and economic loss. Predicting the irregular movement of individuals following such disasters is crucial for managing urban systems. Past survey results show that mid-level disasters do not force ma...
Conference Paper
Real-time estimation of human mobility following a massive disaster will play a crucial role in disaster relief. Because human mobility in massive disasters is quite different from their usual mobility, real-time human location data is necessary for precise estimation. Due to privacy concerns, real-time data is anonymized and a popular form of anon...
Conference Paper
Large scale disasters cause severe social disorder and trigger mass evacuation activities. Managing the evacuation shelters efficiently is crucial for disaster management. Kumamoto prefecture, Japan, was hit by an enormous (Magnitude 7.3) earthquake on 16th of April, 2016. As a result, more than 10,000 buildings were severely damaged and over 100,0...
Article
Real-time estimation of people distribution immediately after a disaster is directly related to disaster reduction and is also highly beneficial in society. Recently, traffic estimation research has been actively performed using data assimilation techniques for observation data obtained from mobile phones. However, there has been no research on dat...

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Projects (3)
Project
Inter-city translation of urban insights and dynamics obtained from large scale data analysis and modeling