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1. Lifestyle pattern analysis unveils recovery trajectories of communities impacted by disasters

   https://doi.org/10.1057/s41599-023-02312-7  

   Coleman, Natalie; Liu, Chenyue; Zhao, Yiqing; Mostafavi, Ali (December 2023, Humanities and Social Sciences Communications)

   Abstract Lifestyle recovery captures the collective effects of population activities as well as the restoration of infrastructure and business services. This study uses a novel approach to leverage privacy-enhanced location intelligence data, which is anonymized and aggregated, to characterize distinctive lifestyle patterns and to unveil recovery trajectories after 2017 Hurricane Harvey in Harris County, Texas (USA). The analysis integrates multiple data sources to record the number of visits from home census block groups (CBGs) to different points of interest (POIs) in the county during the baseline and disaster periods. For the methodology, the research utilizes unsupervised machine learning and ANOVA statistical testing to characterize the recovery of lifestyles using privacy-enhanced location intelligence data. First, primary clustering using k-means characterized four distinct essential and non-essential lifestyle patterns. For each primary lifestyle cluster, the secondary clustering characterized the impact of the hurricane into four possible recovery trajectories based on the severity of maximum disruption and duration of recovery. The findings further reveal multiple recovery trajectories and durations within each lifestyle cluster, which imply differential recovery rates among similar lifestyles and different demographic groups. The impact of flooding on lifestyle recovery extends beyond the flooded regions, as 59% of CBGs with extreme recovery durations did not have at least 1% of direct flooding impacts. The findings offer a twofold theoretical significance: (1) lifestyle recovery is a critical milestone that needs to be examined, quantified, and monitored in the aftermath of disasters; (2) spatial structures of cities formed by human mobility and distribution of facilities extend the spatial reach of flood impacts on population lifestyles. These provide novel data-driven insights for public officials and emergency managers to examine, measure, and monitor a critical milestone in community recovery trajectory based on the return of lifestyles to normalcy. 

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2. The impact of ridesourcing on equity and sustainability in North American cities: A systematic review of the literature

   https://doi.org/10.1016/j.cities.2022.104122  

   McKane, Rachel G.; Hess, David (February 2023, Cities)

   Research on ridesourcing has grown exponentially in recent years. This study details the results of a systematic review of 161 publications on ridesourcing that explore environmental sustainability and equity in North American cities. We identify five main areas of research. First, ridesourcing is associated with two modal shifts: a decline of the taxi industry and a more complicated association with public transit ridership. Second, several studies have documented workers' rights and the challenges of contingent labor. Third, demographic studies show associations between ridesouring and affluent riders, and spatial analyses indicate that ridesourcing may exacerbate existing patterns of inequity in cities. Fourth, ridesourcing has dubious claims to improve environmental sustainability: it has only a small effect on vehicle ownership, but it increases emissions associated with deadheading, and pooled services do not reduce vehicle miles traveled. Fifth, ridesourcing companies also tend to oppose regulatory responses and sharing data with potential regulators. The review concludes with suggestions on areas for future research. 

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3. Point-to-Region Co-learning for Poverty Mapping at High Resolution Using Satellite Imagery

   https://doi.org/10.1609/aaai.v37i12.26675  

   Li, Zhili; Xie, Yiqun; Jia, Xiaowei; Stuart, Kara; Delaire, Caroline; Skakun, Sergii (June 2023, Proceedings of the AAAI Conference on Artificial Intelligence)

   Despite improvements in safe water and sanitation services in low-income countries, a substantial proportion of the population in Africa still does not have access to these essential services. Up-to-date fine-scale maps of low-income settlements are urgently needed by authorities to improve service provision. We aim to develop a cost-effective solution to generate fine-scale maps of these vulnerable populations using multi-source public information. The problem is challenging as ground-truth maps are available at only a limited number of cities, and the patterns are heterogeneous across cities. Recent attempts tackling the spatial heterogeneity issue focus on scenarios where true labels partially exist for each input region, which are unavailable for the present problem. We propose a dynamic point-to-region co-learning framework to learn heterogeneity patterns that cannot be reflected by point-level information and generalize deep learners to new areas with no labels. We also propose an attention-based correction layer to remove spurious signatures, and a region-gate to capture both region-invariant and variant patterns. Experiment results on real-world fine-scale data in three cities of Kenya show that the proposed approach can largely improve model performance on various base network architectures. 

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4. Identifying latent activity behaviors and lifestyles using mobility data to describe urban dynamics

   https://doi.org/10.1140/epjds/s13688-023-00390-w  

   Yang, Yanni; Pentland, Alex; Moro, Esteban (May 2023, EPJ Data Science)

   Abstract Urbanization and its problems require an in-depth and comprehensive understanding of urban dynamics, especially the complex and diversified lifestyles in modern cities. Digitally acquired data can accurately capture complex human activity, but it lacks the interpretability of demographic data. In this paper, we study a privacy-enhanced dataset of the mobility visitation patterns of 1.2 million people to 1.1 million places in 11 metro areas in the U.S. to detect the latent mobility behaviors and lifestyles in the largest American cities. Despite the considerable complexity of mobility visitations, we found that lifestyles can be automatically decomposed into only 12 latent interpretable activity behaviors on how people combine shopping, eating, working, or using their free time. Rather than describing individuals with a single lifestyle, we find that city dwellers’ behavior is a mixture of those behaviors. Those detected latent activity behaviors are equally present across cities and cannot be fully explained by main demographic features. Finally, we find those latent behaviors are associated with dynamics like experienced income segregation, transportation, or healthy behaviors in cities, even after controlling for demographic features. Our results signal the importance of complementing traditional census data with activity behaviors to understand urban dynamics. 

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5. Integrated assessment of urban water supply security and resilience: towards a streamlined approach

   https://doi.org/10.1088/1748-9326/ac78f4  

   Krueger, Elisabeth H; McPhearson, Timon; Levin, Simon A (July 2022, Environmental Research Letters)

   Abstract Urbanization and competing water demand, as well as rising temperatures and changing weather patterns, are manifesting as gradual processes that increasingly challenge urban water supply security. Cities are also threatened by acute risks arising at the intersection of aging infrastructure, entrenched institutions, and the increasing occurrence of extreme weather events. To better understand these multi-layered, interacting challenges of providing urban water supply for all, while being prepared to deal with recurring shocks, we present an integrated analysis of water supply security in New York City and its resilience to acute shocks and chronic disturbances. We apply a revised version of a recently developed, quantitative framework (‘Capital Portfolio Approach’, CPA) that takes a social-ecological-technological systems perspective to assess urban water supply security as the performance of water services at the household scale. Using the parameters of the CPA as input, we use a coupled systems dynamics model to investigate the dynamics of services in response to shocks—under current conditions and in a scenario of increasing shock occurrence and a loss of system robustness. We find water supply security to be high and current response to shocks to be resilient thanks to past shock experiences. However, we identify a number of risks and vulnerability issues that, if unaddressed, might significantly impact the city’s water services in the mid-term future. Our findings have relevance to cities around the world, and raise questions for research about how security and resilience can and should be maintained in the future. 

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