Tokyo Area Research Articles

Tunnel-induced land subsidence assessment in a densely populated residential area using Sentinel-1 PS-InSAR

Land subsidence detection in residential areas based on advanced remotely sensed data is an effective technique to mitigate catastrophic disasters in time. Synthetic aperture radar (SAR) in spaceborne platforms is a highly sophisticated technique to estimate ground surface subsidence with millimeter accuracy for wide-area observation. SAR is beneficial for large-scale social infrastructure project planning and monitoring in densely populated residential areas. In this study, we applied a permanent scatterer (PS) interferometric SAR (PS-InSAR)-based technique for monitoring land subsidence in a tunnel construction site in the Greater Tokyo Area to investigate tunnel-induced ground surface subsidence. Sentinel-1 repeat-pass SAR data in ascending and descending orbital directions were used for continuous observation. Consecutively estimated interferograms based on repeat-pass SAR data were generated to monitor and detect tunnel-induced land subsidence as well as confirm long-term stability along the tunnel excavation path. A bidirectional displacement of the ground area parallel to the earth’s surface in the east–west direction and perpendicular to the earth’s surface in the up–down direction was estimated at a high-phase consistency location using a PS interferometric stacking technique. The resultant data were then analyzed to detect anomalies in the ground area in the spatiotemporal domains by performing displacement time-series analysis. An area near Higashi-Tsutsujigaoka’s local administrative region in the metropolitan center of Tokyo was observed to have 15-mm subsidence and 30-mm displacement in the east–west direction during August–October 2020. The conventional level survey results in the same ground area showed 15–20-mm subsidence above the tunnel excavation path. The findings of this study offer insights into understanding land subsidence in residential environments.

MobCovid: Confirmed Cases Dynamics Driven Time Series Prediction of Crowd in Urban Hotspot.

Monitoring the crowd in urban hot spot has been an important research topic in the field of urban management and has high social impact. It can allow more flexible allocation of public resources such as public transportation schedule adjustment and arrangement of police force. After 2020, because of the epidemic of COVID-19 virus, the public mobility pattern is deeply affected by the situation of epidemic as the physical close contact is the dominant way of infection. In this study, we propose a confirmed case-driven time-series prediction of crowd in urban hot spot named MobCovid. The model is a deviation of Informer, a popular time-serial prediction model proposed in 2021. The model takes both the number of nighttime staying people in downtown and confirmed cases of COVID-19 as input and predicts both the targets. In the current period of COVID, many areas and countries have relaxed the lockdown measures on public mobility. The outdoor travel of public is based on individual decision. Report of large amount of confirmed cases would restrict the public visitation of crowded downtown. But, still, government would publish some policies to try to intervene in the public mobility and control the spread of virus. For example, in Japan, there are no compulsory measures to force people to stay at home, but measures to persuade people to stay away from downtown area. Therefore, we also merge the encoding of policies on measures of mobility restriction made by government in the model to improve the precision. We use historical data of nighttime staying people in crowded downtown and confirmed cases of Tokyo and Osaka area as study case. Multiple times of comparison with other baselines including the original Informer model prove the effectiveness of our proposed method. We believe our work can make contribution to the current knowledge on forecasting the number of crowd in urban downtown during the Covid epidemic.

Quantifying the vibrancy of streets: Large-scale pedestrian density estimation with dashcam data

This paper proposes a new methodology for measuring street-level pedestrian density that combines the strengths of image-based observations with the scalability of drive-by sensing. Despite its importance, existing methods for measuring pedestrian activity have several limitations, including high costs, limited coverage, and privacy concerns. To overcome these issues, our approach exploits operation logs generated by dashboard cameras of moving vehicles to estimate pedestrian density for each street, which is validated with data from approximately 3,000 taxis operating in central Tokyo. We produce vibrancy maps for 292 station areas in central Tokyo by leveraging machine learning to estimate pedestrian density in streets where measurement data is scarce. We also evaluate the reliability and coverage of the measurement and illustrate how the measured pedestrian density data can be utilized for assessing the validity of walkability measures. The paper concludes that this approach could provide valuable data to inform urban planning and city operations.

Source identification of carbon monoxide over the greater Tokyo area: Tower measurement network and evaluation of global/regional model simulations at different resolutions

Because of its relatively long lifetime among short-lived climate forcers in the atmosphere, carbon monoxide (CO) is utilized as a tracer, and is expected to be simulated at coarse resolution. To better grasp the behavior of CO in the atmosphere, multi-altitude measurement is required because the main sources of CO emissions are automobiles (surface) and industry (aloft). In this work, using CO measurements obtained at remote sites and through a tower measurement network in Japan (37 m and 250 m above ground level (AGL) in an urban area, and 32 m AGL at a rural site in the greater Tokyo area), the performances of a global model (2° × 2.5°) and a regional model at various resolutions (12, 4, and 1.3 km) were comprehensively evaluated. The global model successfully simulated CO at remote sites but not for high-concentration peaks at rural and urban sites, whereas the regional model increasingly improved its performance in capturing CO peaks at urban sites with resolutions up to 4 km. Therefore, we concluded that a 4 km resolution was suitable for capturing CO at urban sites, and furthermore estimated the source contributions. The regions surrounding the greater Tokyo area were dominated by the concentration from the lateral boundaries (approximately 180 ppbv), while the higher CO in central Tokyo was attributed to local sources. These local sources accounted for up to 80% of the annual average at the surface level and just 10% aloft (corresponding to the 250 m AGL site). Sensitivity simulations assessing CO sources (automobiles, industry, and others) demonstrated the important role of automobiles, while higher altitudes had more sources attributed to industry. Local sources were found to make more prominent contributions at higher concentration ranges. The appropriate modeling resolution for CO behavior can be drawn from our findings and the usefulness of simultaneous measurements at the surface level and using a tower for capturing the three-dimensional CO structure can be demonstrated as an important approach.

Mortality, Analgesic Use, and Care Requirements After Vertebral Compression Fractures: A Retrospective Cohort Study of 18,392 Older Adult Patients.

Vertebral compression fractures (VCFs) in older adults cause considerable health and socioeconomic burdens due to worsening ability to perform activities of daily living. The long-term effects of VCFs on patient outcomes, particularly prolonged analgesic use and functional decline, remain unknown. The aims of this study were to examine long-term clinical outcomes and to determine the risk factors for persistent pain and functional disability after VCFs. This retrospective cohort study evaluated mortality, duration of analgesic use, and changes in care requirements in older adults with VCFs using claims data from a suburban prefecture in the Greater Tokyo Area. Patients were included if they were ≥65 years of age and had been diagnosed with a VCF between June 2014 and February 2019, as determined on the basis of International Classification of Diseases, Tenth Revision (ICD-10) codes; we also used claims data that could determine whether the patients underwent imaging examinations. Patients who discontinued outpatient visits within 1 month after the VCF diagnosis were excluded. We included 18,392 patients with VCFs and a mean age of 80 years. Seventy-six percent of patients were women, and the median follow-up period was 670 days. At the index VCF diagnosis, 3,631 patients (19.7%) were care-dependent. Overall, 968 patients (5.3%) died within 1 year. Among the 8,375 patients who received analgesics, 22% required analgesics for >4 months. Factors associated with prolonged analgesic use for >1 year were female sex (odds ratio [OR], 1.39 [95% confidence interval (CI), 1.16 to 1.65]) and VCFs in the thoracolumbar region (OR, 1.95 [95% CI, 1.50 to 2.55]) or lumbar region (OR, 1.59 [95% CI, 1.23 to 2.04]) (the reference was the thoracic region). The care needs of 1,510 patients (8.2%) increased within 1 year. Patients with a preexisting care dependency had a 10 times higher risk of increased care need (30.2% [1,060 of 3,509]) than those who had been independent at the time of the index diagnosis (3.0% [450 of 14,761]) (p < 0.001). Individuals with preexisting care dependency were more likely to experience functional decline following VCFs than those who were independent, which underscores the need for intensive and appropriate allocation of health-care resources to care-dependent patients. Therapeutic Level III . See Instructions for Authors for a complete description of levels of evidence.

Shotgun metagenomic sequencing of swab samples from Japanese university campuses.

We obtained shotgun metagenome sequences from swab samples obtained through 3-minute swabbing of different surfaces and the air within buildings at three university campuses in part of the Greater Tokyo Area in Japan. These data aid in understanding built environment microbial communities and elucidate various microbial profiles across different locations.

Electromagnetic field exposure monitoring of commercial 28-GHz band 5G base stations in Tokyo, Japan.

Fifth generation (5G) wireless communication is being rolled out around the world. In this work, the latest radio frequency electromagnetic field (EMF) exposure measurement results on commercial 28-GHz band 5G base stations (BSs) deployed in the urban area of Tokyo, Japan, are presented. The measurements were conducted under realistic traffic conditions with a 5G smartphone and using both omnidirectional and horn antennas. First and foremost, in all cases, the electric-field (E-field) intensity is much lower (<-38 dB) than the exposure limits. The E-field intensities for traffic-off cases do not show any significant difference between the two antennas with the maximum being 3.6 dB. For traffic-on cases, the omnidirectional antenna can undesirably capture the radio wave from the smartphone in some cases, resulting in a 7-13 dB higher E-field intensity than that using the horn antenna. We also present comparative results between 4G long term evolution BSs and sub-6-GHz band and 28-GHz band 5G BSs and provide recommendations on acquiring meaningful EMF exposure data. This work is a further step towardthe standardization of the measurement method regarding quasi-millimeter/millimeter wave 5G BSs.

A participatory foresight approach to envisioning post-pandemic urban development pathways in Tokyo

Ensuring sustainable urban futures demands varied approaches, particularly with the advent of the COVID-19 pandemic, which presents a unique situation and experience for reimagining urban futures. A considerable number of scientific inquiries have adopted participatory foresight approaches to imagining sustainable urban development pathways. However, not many have used a similar approach to envision urban development pathways in a post-COVID-19 era. Based on available evidence on the impacts of COVID-19 on urban forms and lifestyles and citizens’ experiences during the pandemic, such a study is imperative to better understand how people from different demographic groups envision an ideal post-pandemic city. Using the Greater Tokyo Area as a case study, we adopted the Q methodology to determine post-pandemic urban development pathways from the subjective viewpoints of diverse stakeholders. We identified four development pathways for an ideal post-pandemic city. The first pathway is a resilient city with good neighborhood accessibility and sustainable urban regeneration. The second and third pathways, shared by younger people, focus on pro-environmental climate change mitigation (city compactness, shared mobility) and pro-urban resilience, respectively. The final pathway imagines a post-pandemic city that is accessible, safe, and smart. We found that different age groups perceive their ideal cities differently, especially when emphasizing the nexus between pandemics and cities. The study illustrates the need to adopt more participatory approaches in designing future urban development pathways since varied perspectives of an ideal city exist among different age demographics. These approaches promote equitable, inclusive, and transparent urban planning, advancing community support for policymaking and implementation.

Multi-Objective Evcuation Planning Model Considering Post-Earthquake Fire Spread: A Tokyo Case Study

As an integral part of the 2030 Agenda for Sustainable Development, Disaster Risk Reduction (DRR) is essential for human safety and city sustainability. In recent years, natural disasters, which have had a tremendous negative impact on economic and social development, have frequently occurred in cities. As one of these devastating disasters, earthquakes can severely damage the achievements of urban development and impact the sustainable development of cities. To prepare for potential large earthquakes in the future, efficient evacuation plans need to be developed to enhance evacuation efficiency and minimize casualties. Most previous research focuses on minimization of distance or cost while ignoring risk factors. We propose a multi-objective optimization model with the goal of reducing the risk during the evacuation process, which is called the risk reduction model (RRM). Problem-specific indicators for screening optimal solutions are introduced. The research selects the Ogu area in Tokyo as a case study, where there is a relatively high density of wooden structures, increasing the risks of building collapse and fire spread after an earthquake, and is based on a two-phase evacuation flow that considers secondary evacuation for fire response. The results indicate that, in this case, RRM can, in most situations, reduce the risk level during the evacuation process and improve evacuation efficiency and success rate without significantly increasing the total evacuation distance. It proves to be superior to the traditional distance minimization model (DMM), which prioritizes minimizing the total distance as the objective function.

Association between maternal dissatisfaction with oneself at birth and shaking and smothering toward the offspring up to 18 months old

BackgroundA mother who feels dissatisfaction with herself may resort to abusive behavior such as shaking or smothering toward their offspring. Understanding this association can inform effective prevention strategies. ObjectiveThis study aimed to investigate the associations between maternal feelings of dissatisfaction with oneself and infant physical abuse. Participants and settingThe study included 434 mothers who had recently given birth in two obstetric wards in a relatively wealthy area in Tokyo, Japan. MethodsAdopting a longitudinal design, the study used questionnaires post-childbirth to measure mothers' dissatisfaction with themselves. This involved evaluating perceptions of failing to meet personal standards or self-image. Physical abuse (specifically shaking or smothering) in infants was tracked at 3, 6, 12, and 18 months. Data analysis comprised multilevel analysis, group-based trajectory modeling, and multivariable logistic regression to explore the association between maternal dissatisfaction and child physical abuse. ResultsMultilevel analysis showed that mothers with middle or high dissatisfaction with themselves were more likely to abuse their infant compared to mothers with low dissatisfaction with themselves (adjusted odds ratios [aOR] 5.71, 95 % confidence interval [CI], 1.06–30.78 and aOR 12.47, 95 % CI: 2.11–73.69, respectively). Trajectory analyses indicated that mothers with middle or high dissatisfaction with themselves were consistently more likely to abuse their infants up to 18 months (aOR 8.08, 95 % CI 1.61–40.53 and aOR 6.42, 95 % CI 1.27–32.43, respectively). ConclusionsOur findings highlight a robust association between mother's dissatisfaction with themselves and a higher risk of infant physical abuse. These insights call for a comprehensive review of preventive measures for childhood physical abuse.

Spatial system perspective of understanding “fuel-sensitive routes” using regional-scale case studies

Eco-routing is widely researched as a promising way to reduce traffic-related environmental externalities. Past studies indicate that fuel-sensitive eco-routing trades the fastest routes with shorter, slower urban roads to take advantage of the “optimal fuel economy”. However, past studies focusing on individual routes often fail to depict the spatial redistribution of traffic being closer to the residential areas when eco-routing is adopted at a large scale. This research conducts city-scale fuel-sensitive routing simulations for two large metropolitan areas: the San Francisco Bay Area case and the Tokyo Area case. Combining agent-based simulations with data-driven fuel model, it is revealed that fuel-sensitive routing exerts heavier traffic on the local streets and increases residents’ direct exposure to traffic. Furthermore, by comparing different sub-areas, the varied degrees of traffic redistribution are found to be mainly dependent on the availability of major roads as alternative routes, and existing traffic congestion levels in an area.

Physical frailty predicts cognitive decline among community-dwelling older Japanese women: A prospective cohort study from the Otassha study

BackgroundPhysical frailty and cognitive decline are common issues in geriatrics within an aging society, yet the association between them remains controversial. This study aims to evaluate the association between physical frailty and cognitive decline among community-dwelling older Japanese women. MethodsA prospective cohort study was conducted in an urban area of Tokyo, Japan, involving community-dwelling older adults 65 years or older. Physical frailty was evaluated using the Japanese version of the Cardiovascular Health Study criteria, consisting of five components: shrinking, weakness, exhaustion, slowness, and low activity. Participants were classified as robust, pre-frail, or frail based on the presence of one or more criteria. Cognitive decline was defined as at least a three-point decrease in the Mini-Mental State Examination score from baseline. The association between physical frailty and cognitive decline was examined using binomial logistic regression, adjusting for potential confounders. The analysis yielded multivariable odds ratios (ORs) and 95 % confidence intervals (CIs), with robust participants using as the reference group. ResultsA total of 2,122 individuals participated in the baseline survey, with 805 included in the analysis (mean age: 72.9 ± 5.1 years). At baseline, 363 participants were classified as pre-frail, while 32 were classified as frail. During the two-year follow-up period, 68 participants experienced cognitive decline. The multivariable OR (95 % CI) for frailty, using robust as the reference, was 3.50 (1.13, 10.80). Furthermore, a linear relationship was observed between physical frailty and cognitive decline. ConclusionAmong older Japanese women, there exists a dose-response relationship between physical frailty status and cognitive decline.

Modification of Hybrid Receptor Model for Atmospheric Fine Particles (PM2.5) in 2020 Daejeon, Korea, Using an ACERWT Model

Hybrid receptor models overestimate the contribution of background areas (no specific emission sources), like the Yellow Sea in Korea. This study aimed to improve model performances using Advanced Concentration Emission and Retention Time Weighted Trajectory (ACERWT). ACERWT was combined with a positive matrix factorization (PMF), back trajectory, and Regional Emission Inventory in Asia (REAS). The PMF receptor model used one year of data from Korea’s Central Air Environment Research Center. In the PMF receptor model, eight sources (dust/soil, secondary nitrate, biomass burning, vehicles, secondary sulfate, industry, coal combustion and sea salt) influenced PM2.5 pollution at the receptor site (Daejeon, Korea). Secondary sulfate was the most dominant source, followed by secondary nitrate and vehicle sources. ACERWT results showed high contributions from China, Japan, and Korean regions, while the contribution from the Yellow Sea was significantly lower. Several regions, such as the eastern and south-eastern areas of China, the southern area of Taiwan, the western area of Tokyo, and the central area of Korea, showed high contributions due to large-scale emission facilities and industrial complexes. In this study, the ACERWT model significantly improved its performance regarding regional contributions to PM2.5 pollution at the receptor site.

Air quality and urban climate improvements in the world’s most populated region during the COVID-19 pandemic

In this study, we assessed air quality (AQ) and urban climate during the mobility restrictions implemented in the Greater Tokyo Area, Japan, the world’s most populated region, in response to the COVID-19 pandemic. Observations from dense surface networks were analyzed using an interpretable machine learning approach. In parallel with a ∼50% reduction in mobility and an altered lifestyle of the population, we found limited reductions in nitrogen dioxide; decreases in fine particulate matter not entirely driven by local mobility; minor variations in ozone, with a positive (negative) tendency in areas with high (low) emissions; a decrease in air temperature consistent with mobility; and pollution levels and air temperature changes with well-defined, common spatiotemporal patterns. Specifically, cooling mainly occurred in urbanized areas with an improved AQ. Overall, although reductions in mobility were moderately effective in improving the typical indicators of urban AQ, including those known to negatively impact human health, the reductions in waste heat had a stronger impact on Tokyo’s urban heat island, suggestive of a strategy to minimize exposure to heat stress. These findings can help guide urban planning strategies and policies aimed at addressing climate change.

Evaluating transit-oriented new town development: Insights from Seoul and Tokyo

This study evaluates 7Ds (density, diversity, design, distance to transit, destination accessibility, demand management, and demography) from a transit-oriented development (TOD) perspective for four large-scale new towns (NTs) in the suburban areas of Seoul, South Korea, and Tokyo, Japan. The analysis revealed variations in self-sufficiency and travel behavior based on these differences, leading to four main policy implications. First, Seoul’s NTs demonstrated high-density mixed-use development, promoting localized short-distance travel within these areas. This highlights the importance of encouraging high-density mixed-use development to foster commuting self-sufficiency. Second, Tokyo’s NTs feature housing development centered on rail transit, resulting in a greater utilization of rail transit modes. This emphasizes the positive impact of rail-transit-oriented development on sustainable mode choice. Third, demand management strategies such as firm-based subsidies and an integrated transit system were identified in the Tokyo and Seoul NTs, respectively. These strategies aimed to provide incentives for choosing public transit over private cars. Additionally, it is crucial to consider the relationship between NTs and their neighboring areas to prevent wasteful commuting resulting from continuous decentralization trends in jobs and housing. This study offers valuable insights for policymakers and planners by highlighting the significance of integrating TOD principles into NT planning and development.

Research on the actual state of shrinking of the high-density wooden housing area in Tokyo

Research on the actual state of shrinking of the high-density wooden housing area in Tokyo

Changing in fire-inextinguishable areas (FIAs) in Tokyo based on Euclidean and road network distances

Changing in fire-inextinguishable areas (FIAs) in Tokyo based on Euclidean and road network distances

Economic impact analysis of developing the JR Haneda Airport Access Line

The East Japan Railway Company is planning a new access railway line to the Tokyo International (Haneda) Airport. This paper proposes an evaluation method for the development of the new airport access line considering the socioeconomic characteristics of the Greater Tokyo Area and indicates what is needed to increase its social value. As the evaluation method, we develop an econometric model that considers commuters’ trip behaviors across prefectures and the relationship between the increased number of Meeting, Incentive Travel, Convention, Exhibition and Event (MICE) visitors and the regional economy. We also conduct a simulation analysis using an empirical econometric model and a cost-effectiveness analysis based on multiple scenarios. The results indicate that a 50% increase in MICE visitors is needed to make the present discounted value of the total increase in the gross regional product larger than the construction cost of the line.

Perception and production of French oral vowels by Japanese-speaking learners: does dialectal variation play a role?

This paper presents a series of studies on the impact of regional variation in L1 (source language) on L2 (target language) pronunciation, focusing on the high back vowel /u/ in French perceived or produced by native speakers of Japanese from the Kanto area (around Tokyo) and the Kansai area (around Osaka). 1) To serve as a base line, the 5 Japanese vowels were pronounced by 11 speakers (5 women and 6 men) from Kansai with no learning experience of French and their first 4 formants were measured to examine their acoustic properties. 2) 25 naïve listeners from Kansai took part in an AXB auditory discrimination task for French vowels including pairs /u/-/y/, /y/-/ø/ and /u/-/ø/; the results were compared with those of Kanto speakers in previous studies. 3) Some Japanese-speaking learners of French (JSL) from Kansai produced the French /u/ with a lower F2 (around 1,000 Hz for men) than typical values observed for learners from the Tokyo area. These results show limited differences for some of the speakers from Kansai compared to the tendency commonly observed with Kanto speakers

What samples are suitable for monitoring antimicrobial-resistant genes? Using NGS technology, a comparison between eDNA and mrDNA analysis from environmental water.

The rise in antimicrobial resistance (AMR) that is affecting humans, animals, and the environment, compromises the human immune system and represents a significant threat to public health. Regarding the impact on water sanitation, the risk that antimicrobial-resistant genes (ARGs) and antimicrobial-resistant bacteria in surface water in cities pose to human health remains unclear. To determine the prevalence of AMR in environmental surface water in Japan, we used DNA sequencing techniques on environmental water DNA (eDNA) and the DNA of multidrug-resistant bacteria (mrDNA). The eDNA was extracted from four surface water samples obtained from the Tokyo area and subjected to high- throughput next-generation DNA sequencing using Illumina-derived shotgun metagenome analysis. The sequence data were analyzed using the AmrPlusPlus pipeline and the MEGARes database. Multidrug-resistant bacteria were isolated using a culture-based method from water samples and were screened by antimicrobial susceptibility testing (for tetracycline, ampicillin-sulbactam, amikacin, levofloxacin, imipenem, and clarithromycin). Of the 284 isolates, 22 were identified as multidrug-resistant bacteria. The mrDNA was sequenced using the Oxford nanopore MinION system and analyzed by NanoARG, a web service for detecting and contextualizing ARGs. The results from eDNA and mrDNA revealed that ARGs encoding beta-lactams and multidrug resistance, including multidrug efflux pump genes, were frequently detected in surface water samples. However, mrDNA also revealed many sequence reads from multidrug-resistant bacteria, as well as nonspecific ARGs, whereas eDNA revealed specific ARGs such as pathogenic OXA-type and New Delhi metallo (NDM)-beta-lactamase ARGs. To estimate potential AMR pollution, our findings suggested that eDNA is preferable for detecting pathogen ARGs.