Economics and Finance

Using machine learning to understand causal relationships between urban form and travel CO2 emissions across continents

Wagner, Felix
Nachtigall, Florian
Franken, Lukas
Milojevic-Dupont, Nikola
Pereira, Rafael H. M.
Koch, Nicolas
Runge, Jakob
Gonzalez, Marta
Creutzig, Felix
2023

Climate change mitigation in urban mobility requires policies reconfiguring urban form to increase accessibility and facilitate low-carbon modes of transport. However, current policy research has insufficiently assessed urban form effects on car travel at three levels: (1) Causality -- Can causality be established beyond theoretical and correlation-based analyses? (2) Generalizability -- Do relationships hold across different cities and world regions? (3) Context specificity -- How do relationships vary across neighborhoods of a city? Here, we address all three gaps via causal graph...

Urban Street Contexts Classification Using Convolutional Neural Networks and Streets Imagery

Alhasoun, Fahad
González, Marta
2019

The classification of streets on road networks has been focused on the vehicular transportational features of streets. Examples of street labels include arterials, major roads, minor roads and so forth based on their transportational use. City authorities on the other hand have been shifting to more wholistic planning of streets. The modern approach towards designing and planning streets is more inclusive of the street context, meaning the side use of a street combined with the transportational features of a street. Several city authorities are developing new classification schemes for...

Unraveling environmental justice in ambient PM2.5 exposure in Beijing: A big data approach

Xu, Yanyan
Jiang, Shan
Li, Ruiqi
Zhang, Jiang
Zhao, Jinhua
Abbar, Sofiane
González, Marta C.
2019

Air pollution imposes significant environmental and health risks worldwide and is expected to deteriorate in the coming decade as cities expand. Measuring population exposure to air pollution is crucial to quantifying risks to public health. In this work, we introduce a big data analytics framework to model residents' stay and commuters' travel exposure to outdoor PM2.5 and evaluate their environmental justice, with Beijing as an example. Using mobile phone and census data, we first infer travel demand of the population to derive residents' stay activities in each analysis zone, and then...

Understanding vehicular routing behavior with location-based service data

Xu, Yanyan
Clemente, Riccardo Di
González, Marta C.
2021

Properly extracting patterns of individual mobility with high resolution data sources such as the one extracted from smartphone applications offers important opportunities. Potential opportunities not offered by call detailed records (CDRs), which offer resolutions triangulated from antennas, are route choices, travel modes detection and close encounters. Nowadays, there is not a standard and large scale data set collected over long periods that allows us to characterize these. In this work we thoroughly examine the use of data from smartphone applications, also referred to as location-...

Spatial sensitivity analysis for urban land use prediction with physics-constrained conditional generative adversarial networks

Albert, Adrian
Kaur, Jasleen
Strano, Emanuele
Gonzalez, Marta
2019

Accurately forecasting urban development and its environmental and climate impacts critically depends on realistic models of the spatial structure of the built environment, and of its dependence on key factors such as population and economic development. Scenario simulation and sensitivity analysis, i.e., predicting how changes in underlying factors at a given location affect urbanization outcomes at other locations, is currently not achievable at a large scale with traditional urban growth models, which are either too simplistic, or depend on detailed locally-collected socioeconomic data...

Quantifying the Resilience of the U.S. Domestic Aviation Network During the COVID-19 Pandemic

Bauranov, Aleksandar
Parks, Steven
Jiang, Xuan
Rakas, Jasenka
González, Marta C.
2021

This paper analyzes the impacts of COVID-19 pandemic on the United States air transportation network between March and August 2020. Despite dramatic reductions in flight and passenger volumes, the network remained robust and resilient against perturbation. Although 24% of airports closed, the reduction in network efficiency was only 5.1%, which means airlines continued to serve most destinations. A deeper analysis of airport closures reveals that 1) small peripheral airports were the most likely to be closed; 2) socio-economic and epidemiological factors characterizing the airport’s region...

Projecting battery adoption in the prosumer era

Barbour, Edward
González, Marta C.
2018

Solar photovoltaic (PV) has the potential to make an important contribution to global sustainability, however, the misalignment between solar production and residential demand presents challenges for widespread PV adoption. Combining PV and storage is one way that this challenge can be overcome. In this work, we use one year of smart meter data from 369 consumers in three different US regions and calculate their economic benefits from both PV and coupled PV-battery systems. We consider a range of different electricity pricing schemes from the consumer regions, including both Feed-In-Tariff...

Multimicrogrid Load Balancing Through EV Charging Networks

Chen, Xi
Wang, Haihui
Wu, Fan
Wu, Yujie
González, Marta C.
Zhang, Junshan
2022

Energy demand and supply vary from area to area, where an unbalanced load may occur and endanger the system security constraints and cause significant differences in the locational marginal price (LMP) in the power system. With the increasing proportion of local renewable energy (RE) sources in microgrids that are connected to the power grid and the growing number of electric vehicle (EV) charging loads, the imbalance will be further magnified. In this article, we first model the EV charging network as a cyber–physical system (CPS) that is coupled with both the transportation networks and...

Mobile phone location data for disasters: A review from natural hazards and epidemics

Yabe, Takahiro
Jones, Nicholas K. W.
Rao, P. Suresh C.
Gonzalez, Marta C.
Ukkusuri, Satish V.
2022

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 location data collected from mobile phone devices have opened up novel approaches to tackle these challenges. Mobile phone location data have enabled us to observe, estimate, and model human mobility dynamics at an unprecedented spatio-temporal...

Mining urban lifestyles: urban computing, human behavior and recommender systems

Xu, Sharon
Clemente, Riccardo Di
González, Marta C.
2019

In the last decade, the digital age has sharply redefined the way we study human behavior. With the advancement of data storage and sensing technologies, electronic records now encompass a diverse spectrum of human activity, ranging from location data, phone and email communication to Twitter activity and open-source contributions on Wikipedia and OpenStreetMap. In particular, the study of the shopping and mobility patterns of individual consumers has the potential to give deeper insight into the lifestyles and infrastructure of the region. Credit card records (CCRs) provide detailed...