Urban Currents

Who Moved? Ecological Estimates of Turnout & Coalition Support by Ethnicity and Age in Johor, Malaysia, 2022-2026

The study uses ecological inference to estimate voter turnout and coalition support by ethnicity and age across three elections in Johor, Malaysia, from 2022 to 2026. Leveraging geographic variation in polling station ethnic makeup and administrative age sorting in polling streams, the analysis reveals that a 26-percentage-point swing in ethnic turnout drove outcomes, Perikatan Nasional's Malay support collapsed directly to Barisan Nasional (BN), and Pakatan Harapan's decline among Chinese voters was primarily driven by lower turnout rather than crossover voting.

Why it matters — It provides the first open, fully reproducible ecological estimates of voting behavior for a Malaysian election, complete with validation errors against held-out data, correcting misinterpretations about youth voting gradients by showing that age-based support was actually flat once ethnic composition was controlled for.

Caveat: The findings rely on ecological inference from polling-station and polling-stream aggregates rather than individual-level survey or ballot data.

arXiv · pdf

MOBILIZING SUCCESS AND FAILURE: Strategic Ambivalence in Policy Mobility—Brasília and Argentina's Capital Relocation Debate

This study analyzes the mid-1980s proposal to relocate Argentina's federal capital from Buenos Aires to Viedma–Carmen de Patagones, focusing on how proponents used the example of Braslia. It demonstrates that state elites simultaneously framed Braslia as a successful model of territorial integration and a cautionary tale of fiscal and planning failure depending on the audience and scale of contestation.

Why it matters — The research introduces the concept of 'strategic ambivalence' to show that conflicting evaluations of a policy model are not just debates between opposing coalitions, but can be deliberately co-opted and managed by the same powerful actors to navigate political resistance.

Caveat: The findings are based on a single historical case study of a capital relocation project that was ultimately never realized.

International Journal of Urban and Regional Research · doi

The impact of a new transit infrastructure on the economic fabric of Rome

Using a difference-in-differences approach within a multiplicative framework, this study measures how the expansion of Rome's Metro C line affected local businesses. The analysis reveals a statistically significant increase in the total number of economic activities near the new stations, accompanied by a mild decline in economic diversity that points to spatial clustering. A focused analysis of microenterprises, which make up the majority of the dataset, tracks the associated shifts in local employment and GDP.

Why it matters — It provides empirical evidence that major transit investments generate positive economic spillovers at the neighborhood level, establishing a quantifiable correlation between accessibility gains and microenterprise growth that can help project the economic impacts of future transit lines.

Caveat: The study relies on zone-level correlations from a single transit line expansion to suggest broader generalizability.

Discover Cities · pdf · doi

Assessing the influence of urban expansion on land surface temperature in the Gazipur industrial zone of Bangladesh

This study analyzed the impact of urban expansion on land surface temperature (LST) in the Gazipur industrial zone of Bangladesh from 1995 to 2024 using satellite imagery and machine learning in Google Earth Engine. The built-up area expanded 4.4-fold from 60.46 square kilometers (3.33%) to 266.36 square kilometers (14.66%), which was associated with a mean LST increase of 1.64 °C in summer and 2.85 °C in winter. The land use classification achieved an overall accuracy between 0.92 and 0.98, with the highest temperature increases concentrated in industrialized zones like Gazipur Sadar.

Why it matters — It quantifies the direct thermal consequences of rapid, unregulated industrialization in a major South Asian manufacturing hub over a 30-year period, demonstrating a semi-automated monitoring workflow that can be scaled to other rapidly developing regions.

Caveat: The temperature estimates may contain uncertainties stemming from sensor calibration and the estimation of land surface emissivity.

Discover Cities · pdf · doi

From participation to relational infrastructuring: Rethinking inclusion in contemporary placemaking

This study introduces the Relational Placemaking for Inclusion (RPI) framework, which analyzes inclusive urban development across three dimensions: temporality, institutional resonance, and design agency. The framework is applied to three European case studies to examine how civic relationships, institutional adaptation, and participatory mediation shape public space co-production.

Why it matters — It shifts the focus of placemaking evaluation from temporary participatory events and physical outputs to long-term relational capabilities. This provides a structured way to understand how civic initiatives can permanently transform municipal institutions and sustain inclusive practices beyond individual project lifecycles.

Caveat: The findings are based on qualitative analysis of three European case studies, which may limit their direct applicability to highly different governance and planning systems elsewhere.

Cities · doi

Associations of school neighbourhood built environment profiles with active commuting behaviour in Spanish adolescents

This study analyzed self-reported active commuting to school (ACS) and related psychosocial outcomes for 311 Spanish adolescents aged 13 to 15. The researchers classified school neighborhoods using principal component analysis and hierarchical clustering across macro- and micro-scale built environment features. While individual environmental scales showed no significant independent associations with commuting behavior, the combination of a green, walkable macro-scale environment and a highly supportive micro-scale environment was associated with a 7.31 times higher odds of active commuting to school and lower perceived planning or psychosocial barriers.

Why it matters — It demonstrates that urban design interventions to promote active school travel cannot rely on macro-scale walkability or micro-scale streetscape improvements in isolation; rather, both scales must be improved simultaneously to significantly influence adolescent behavior and motivation.

Caveat: The study relies on self-reported behavioral and psychosocial data from a relatively small sample of 311 adolescents, which may introduce reporting bias.

Cities · doi

Cross-scale collaborative planning approach for sustainable water management: A blue-green infrastructure vision for the Huangyan–Taizhou Region, China

This study develops and tests a cross-scale collaborative planning framework for blue-green infrastructure (BGI) in the rapidly urbanizing Huangyan–Taizhou Region of China, spanning the years 2019 to 2024. The approach combines regional-scale visioning workshops, transect-scale co-mapping of agricultural and industrial transition zones, and site-level co-design sessions with local stakeholders and interviews. The resulting framework successfully links regional water management goals to localized, community-supported spatial interventions.

Why it matters — It provides a practical, spatially explicit method to translate abstract Integrated Water Resources Management (IWRM) principles into actionable local designs, overcoming the typical fragmentation between top-down regional water strategies and bottom-up community needs.

Caveat: The framework's success was demonstrated within a specific, highly structured six-year international research project (Sino–German Urban–Rural Assembly), which may possess resources and institutional access not typically available to standard municipal planning departments.

Cities · doi

Trade-linked maritime emissions and ammonia fuel transition in the UAE

This study quantifies the UAE's maritime energy demand and CO2 emissions through 2070 using historical bilateral trade data and Multi-Regional Input-Output modeling from the Global Energy and Climate Outlook 2024. It estimates that UAE trade-linked shipping emissions were 7.94 Mt CO2 in 2022, representing roughly 0.9% of the global international shipping total. Scenario analysis reveals that the nation's target of 75% ammonia fuel use by 2050 is unlikely to be met under current trends due to slow fleet turnover, high fuel costs, and lagging bunkering infrastructure.

Why it matters — It establishes a replicable national-level framework to test the feasibility of alternative fuel targets in international shipping, demonstrating that official decarbonization timelines are misaligned with actual fleet and infrastructure transition rates.

Case Studies on Transport Policy · doi

Expressway development and income inequality: Nonlinear and spatially differentiated effects

This study analyzed panel data from 30 Chinese provinces between 2010 and 2023 to evaluate how expressway development affects the urban-rural income gap. Using threshold regression and Geographically and Temporally Weighted Regression (GTWR), the analysis measures how regional factor-carrying capacity, represented by population density and economic development, alters this relationship. The findings show that while expressway expansion generally reduces income inequality through improved logistics and labor mobility, it actually widens the income gap in regions with low factor-carrying capacity by concentrating production factors in core areas.

Why it matters — It demonstrates that the economic distribution effects of transport infrastructure are non-linear and highly dependent on local development levels, reconciling previous contradictory findings by showing that infrastructure expansion only reduces inequality after a region passes a specific development threshold.

Caveat: The study relies on province-level panel data, which may mask finer sub-provincial or municipal variations in income distribution and expressway accessibility.

Journal of Transport Geography · doi

Price regulation, market dynamics, and judicial reasoning: Assessing the dissenting opinion in the Supreme Court's taxi fare decision

This study evaluates Japan's taxi fare regulation using long-term market data from the Tokyo Special Wards and Musashino Area to estimate taxi demand price elasticity. Using direct demand regression, revenue-based proxies, and unit-demand analysis, the study finds a conservative price elasticity of -0.27, indicating inelastic demand, while hire car services show statistically insignificant elasticity. Counterfactual modeling reveals that realistic cross-price elasticity parameters result in only modest market-share shifts under low-price strategies.

Why it matters — It provides empirical evidence supporting a dissenting Supreme Court opinion, demonstrating that low-fare, reservation-based operators do not necessarily trigger destructive market competition or destabilize the transit sector.

Caveat: The empirical findings are based on market data from a single metropolitan region in Japan, which may limit generalizability to areas with different transit structures or regulatory frameworks.

Research in Transportation Economics · pdf · doi

Risk dynamics in performance-based road maintenance: Empirical evidence from Saudi Arabia

This study analyzed the risks of implementing Performance-Based Contracting (PBC) for road maintenance in Saudi Arabia using survey data from 93 government, contracting, and consulting professionals. Through Structural Equation Modelling and Spearman's rank correlation, the research evaluated 23 risk factors, identifying weak contractor performance, unexpected traffic growth, skill gaps, infrastructure deterioration, and early contract termination as the top five threats.

Why it matters — It provides a data-driven risk-allocation framework that addresses differing stakeholder perceptions, enabling more balanced risk-sharing strategies and targeted capacity building in a region transitioning its infrastructure management models.

Caveat: The findings are based on subjective expert survey responses and perceptions rather than empirical project cost or performance data.

Transport Policy · pdf · doi

T-STAR: A context-aware transformer framework for short-term probabilistic demand forecasting in dock-based shared micro-mobility

The researchers developed T-STAR, a two-stage transformer-based framework that forecasts station-level bike-sharing demand at a 15-minute resolution. Tested on Washington D.C.’s Capital Bikeshare system, the model separates coarse hourly patterns from high-frequency fluctuations by integrating real-time metro demand variations and localized inputs to generate probabilistic predictions.

Why it matters — The framework improves both deterministic and probabilistic forecasting accuracy over existing baselines and demonstrates zero-shot transferability, allowing operators to predict demand in entirely new service areas without retraining the model.

Caveat: The model's performance and transferability were validated using data from a single micro-mobility system in Washington D.C.

Transportation Research Part C Emerging Technologies · doi

Sustainability evaluation of a water-bound bring collection system for recyclable waste: optimization strategies and real-world application

This study models a water-bound recyclable waste collection system using a mobile barge and temporary quay assembly points, testing it with real-world pilot data from Stockholm. A two-stage mixed-integer linear programming model was developed to maximize service coverage while minimizing routing emissions across water transport, transshipment points, and road transport to recycling centers. The analysis evaluates how visit spacing policies and increased barge storage capacities affect the trade-offs between road and water emissions and social accessibility.

Why it matters — It establishes a quantitative framework for evaluating the environmental and social trade-offs of urban waterway logistics, demonstrating that while transshipment points increase water-based emissions, they can reduce overall negative externalities by cutting down road transport trips.

Caveat: The optimization model and trade-off analyses are evaluated using data from a single pilot study in Stockholm, which may limit direct applicability to cities with different waterway geographies or waste infrastructure.

Transportation Research Interdisciplinary Perspectives · doi

Transport and visually impaired people

This review synthesizes literature across transport planning, disability studies, urban design, psychology, policy, and assistive technology to analyze how legal frameworks, built environments, and emerging technologies affect the travel experiences of visually impaired people. Drawing primarily on UK evidence, it maps legacy and contemporary barriers in infrastructure, information systems, and evolving street designs that restrict independent mobility.

Why it matters — It establishes a multi-disciplinary research and design agenda by connecting physical infrastructure failures to overlooked psychological and emotional dimensions of travel, such as spatial cognition and social participation.

Caveat: The findings and synthesized evidence are heavily concentrated on the UK context, which may limit their direct applicability to countries with different transport policies and urban designs.

Transport Reviews · doi

Space2Ground 2.0: A Multi-Source Dataset and Framework for Agricultural Monitoring through Fusion of Street-Level and Satellite Imagery

The Space2Ground 2.0 framework integrates Sentinel-1 SAR and Sentinel-2 multispectral satellite time series with crowdsourced, geo-tagged street-level imagery from Mapillary. An automated pipeline filtered over 900,000 raw images down to a curated dataset of 46,050 annotated street-level images linked to 8,581 agricultural parcels in Cyprus during the 2022 growing season. Crop classification experiments using this fused dataset demonstrated that ground-level visual data improves classification accuracy when combined with overhead satellite observations.

Why it matters — It establishes a reproducible method and open benchmark dataset that overcomes the limitations of cloud cover and overhead-only perspectives in satellite monitoring, reducing the need for expensive physical field inspections.

Caveat: The pipeline and dataset were evaluated using data from a single island nation, Cyprus, during a single growing season.

arXiv · pdf

Predictability of Human Movements across Industry Sectors using Multilayer Networks

This study evaluates ten statistical and machine learning models to predict human movement flows across different industry sectors, such as grocery stores, schools, and hospitals, using demographic, socioeconomic, and infrastructure data. Random forest regression consistently outperformed other models, revealing that population size is the key predictor for outward flows, while industry-specific infrastructure is crucial for inward flows. Additionally, incorporating time-encoding features allowed nonlinear models to predict weekly movements more accurately than time-averaged flows.

Why it matters — It demonstrates that human mobility is highly sector-dependent and that temporal dynamics can be predicted more accurately than static, time-averaged patterns when using nonlinear machine learning models.

arXiv · pdf