Urban Currents

GeoPandas: Fundamental data structures for vector spatial data in Python

This paper documents GeoPandas, an open-source Python package that extends pandas data structures to support vector geometries through three core structures: GeometryArray, GeoSeries, and GeoDataFrame. The library wraps compiled C/C++ libraries to execute geometry operations, coordinate transformations, and file input/output behind a high-level, user-friendly API.

Why it matters — It establishes a standardized, Pythonic interface that unifies geometric operations with tabular data management, serving as a foundational infrastructure that democratizes spatial analysis and enables reproducibility across diverse fields like urban analytics and climate modeling.

Computers Environment and Urban Systems · doi

Public support, firm upgrading and spatial heterogeneity: Do financial instruments matter more than grants?

The study analyzed the relationship between public business support and firm employment growth across 206 micro-regions in Czechia between 2020 and 2025. Using administrative data, it compared the effects of grant-based support versus financial instruments on the share of firms moving to higher employment size categories. The analysis employed global ordinary least squares models, geographically weighted regression, and spatial decomposition to capture regional variations.

Why it matters — It demonstrates that financial instruments have a more stable and consistently positive association with firm growth than grants, which exhibit high spatial instability and local sign reversals. This reveals that the effectiveness of business support policies is highly dependent on both the instrument type and the specific territorial context, challenging the utility of national-average evaluations.

Caveat: The study measures firm growth using categorical transitions between employment size brackets rather than continuous employment numbers, which may miss smaller-scale staffing changes.

GeoJournal · pdf · doi

Homeowners’ barriers and motivations in decisions to adopt government-led energy efficiency renovation in China’s Northern Heating Region

This study identifies the barriers and motivations influencing homeowners' decisions to participate in government-led energy efficiency renovations in China's Northern Heating Region. Using a questionnaire survey and semi-structured interviews, it compares the perceptions of homeowners with and without prior renovation experience, finding that experienced homeowners perceive lower levels of both barriers and motivations.

Why it matters — It establishes that prior renovation experience significantly alters how homeowners perceive the costs, process, and benefits of energy retrofits, suggesting that government outreach strategies must be segmented based on residents' past housing experiences rather than treated as a uniform population.

Caveat: The findings are based on self-reported survey and interview data from a specific heating region in China, which may limit their applicability to areas with different climate policies or housing governance structures.

Journal of Housing and the Built Environment · pdf · doi

Local land-use policy interventions and housing supply elasticity: the case of Finland

Using quarterly data from 1988 to 2020 across 22 Finnish cities, this study estimates that long-run housing supply stock elasticity ranges from 0.3 to 2.2. By constructing novel city-level indices of land-use policy restrictiveness, the analysis shows that cities with more restrictive planning interventions, particularly those imposing higher indirect development costs, exhibit lower supply elasticities. Together with city size and geographic constraints, these policy factors explain approximately 70% of the variation in housing supply elasticity across the studied municipalities.

Why it matters — The study provides empirical evidence linking specific local planning delays and indirect development costs to reduced housing supply responsiveness, demonstrating that municipal land-use policies directly shape market elasticity even within a single national regulatory framework.

Caveat: The second-stage analysis of policy determinants relies on a cross-sectional design across 22 cities, which limits the ability to establish strict causal relationships.

Journal of Housing and the Built Environment · pdf · doi

Eco-communities as socio-spatial laboratories: Lessons for retrofitting low-density housing settlements

This study analyzes how socio-spatial practices from three Danish eco-villages (Andelssamfundet i Hjortshøj, Karise Permatopia, and Svanholm) can inform retrofitting strategies for low-density suburban and peri-urban settlements. Using semi-structured interviews, spatial observations, and GIS-based geo-surveys, the research examines how different governance models—ranging from informal collaboration to structured collectivism—link collective agency with resource stewardship.

Why it matters — It demonstrates that retrofitting low-density suburbs requires translating governance routines and participation infrastructures rather than merely replicating physical spatial typologies, showing how social organization and spatial form must be adapted together.

Caveat: The findings are based on self-selected, highly motivated eco-communities, which may limit their direct translation to mainstream suburban populations that lack similar volunteer capacity or shared values.

Journal of Housing and the Built Environment · pdf · doi

How useful can travel time be? Modelling relationships between travel-based and out-of-trip activities

The study calibrated an extended multiple discrete continuous (eMDC) model using revealed-preference data from a representative sample of adults in Greater Melbourne and Geelong, Australia, to analyze how travel-based activities interact with out-of-trip activities. The findings show that mandatory and maintenance activities performed during travel complement their out-of-trip counterparts, whereas discretionary activities during travel substitute for out-of-trip leisure. The phenomenon of 'activity transfer'—using travel time to free up time later—was found to weaken these complementary relationships and intensify substitution effects.

Why it matters — It demonstrates that travel time is not merely wasted transit but functions as a critical space-time buffer that absorbs excess demand for high-priority tasks and accommodates leisure for time-scarce individuals, shifting how researchers must model the utility of travel time.

Caveat: The study relies on data from a single metropolitan region in Australia, which may limit how well these specific activity-substitution dynamics generalize to cities with different transit systems or cultural time-use patterns.

Transportation · pdf · doi

Urban sustainability through multiple pathways: insights from the European Green Leaf Award winning cities

This study analyzed the environmental characteristics of 18 European Green Leaf Award (EGLA) winning cities from 2015 to 2026 using Multiple Factor Analysis and k-means clustering. The analysis evaluated environmental indicators across key domains to identify patterns of similarity and divergence among these recognized municipalities.

Why it matters — The findings demonstrate that award-winning sustainable cities do not follow a single, uniform environmental model but instead pursue diverse pathways shaped by local conditions and policy priorities, offering varied templates for small and medium-sized cities planning their green transitions.

Caveat: The study is limited to a small sample of 18 European cities that have won a specific regional award, which may not represent sustainability pathways in other global contexts or larger metropolitan areas.

Computational Urban Science · pdf · doi

Bridging digital divides: User-generated data and volunteered urban sensing for inclusive smart city governance

The paper presents a framework combining the Wishes, Interests, and Needs (WIN) co-design methodology with an Urban Living Lab approach to integrate user-generated data and volunteered urban sensing into local planning. The combined method structures how diverse residents contribute local knowledge and everyday experiences to shape smart-city technologies.

Why it matters — It establishes a structured, participatory pathway to prevent technocratic smart-city deployments from reinforcing existing digital divides, ensuring marginalized groups can actively influence urban digital infrastructure.

Caveat: The abstract does not provide empirical results, quantitative metrics, or details on a specific physical deployment of the framework.

Cities · pdf · doi

Deprivation and access to discount food supermarkets in England: A cross-sectional analysis

This study analyzed spatial access to discount food supermarkets across England using Geographic Information Systems (GIS) and quantile regression. The model controlled for population density, conventional supermarkets, urbanization levels, public transport availability, and north-south regional differences to measure how deprivation relates to physical proximity. The analysis revealed that more deprived areas generally have higher physical accessibility to discount food supermarkets, though this relationship varies significantly between urban and rural areas as well as between the north and south of the country.

Why it matters — It establishes that discount supermarkets are physically closer to deprived populations who need them most, shifting the policy focus from simple physical availability to how regional and urban-rural disparities affect food security strategies.

Caveat: The study relies on a cross-sectional design, which captures spatial correlation at a single point in time rather than the causal dynamics of supermarket placement or changing neighborhood demographics.

Cities · doi

Aesthetic preferences for traditional versus contemporary architecture: Cross-national evidence from real-world buildings

A survey of 2,997 respondents across Norway and Greece evaluated aesthetic preferences using four pairs of building facades, where each pair contrasted a traditional design with a contemporary design located in Norway. Traditional facades were preferred over contemporary ones in seven out of eight individual comparisons, a preference that held true even when the contemporary buildings had received professional architectural awards or nominations. The study also found that women and residents of denser urban areas showed a stronger preference for traditional architectural styles.

Why it matters — The findings demonstrate that public aesthetic preferences for traditional architecture are consistent across different national cultures, challenging the criteria used by professional architectural bodies to award contemporary designs.

Caveat: The study relies on a small stimulus set of only four building pairs, all of which are physically located in a single country.

Cities · doi

Integrated urban resilience strategies for water management and climate adaptation in Africa: A systematic review aligned with the SDGs

This systematic review synthesizes African urban resilience research from 2015 to 2024 using the PRISMA methodology to analyze strategies across water security, climate risks, green infrastructure, and community-based water management. The analysis maps regional variations across the continent, showing that North Africa prioritizes water scarcity solutions, Sub-Saharan Africa focuses on flood resilience, and Southern Africa combines technical and participatory approaches.

Why it matters — It establishes how regional governance, resource constraints, and informal settlement exclusion shape adaptation choices across Africa, providing a structured framework that links localized water management strategies directly to specific Sustainable Development Goals.

Caveat: The synthesized findings are constrained by data limitations and weak governance documented in the underlying literature, which may affect the scalability of the identified hybrid solutions.

Cities · pdf · doi

Smartwashing mobility: Governing smart mobility through urban imaginaries

This study conceptualizes the term 'smartwashing' to describe how urban initiatives selectively use narratives of smartness to gain legitimacy and political support. The researchers analyzed four smart mobility projects in Stavanger, Norway, and Gothenburg, Sweden, demonstrating how these projects align themselves with existing policy goals and local governance frameworks even when their actual impacts are incomplete or uncertain.

Why it matters — It provides a new analytical framework for understanding how smart city projects secure funding and political viability through performative framing rather than proven performance, revealing how 'smartness' functions as a powerful tool of contemporary urban governance.

Caveat: The findings are based on a qualitative analysis of four specific projects across only two Scandinavian cities, which may limit their applicability to different political and governance contexts.

Cities · pdf · doi

Do States develop geopolitical leverage through the international activities of State-Owned Enterprises (SOEs) in ports and maritime logistics?

This study establishes an analytical framework to evaluate how home countries gain geopolitical leverage through state-owned enterprise (SOE) investments in foreign shipping, terminal operations, and port management. The framework is applied to a case study of the Chinese SOE COSCO and its operations in the Port of Piraeus, Greece, to determine the conditions under which these maritime investments translate into political influence.

Why it matters — It provides a structured method to assess the geopolitical risks of foreign state-backed infrastructure investments, demonstrating empirically that COSCO's presence in Piraeus yields tangible leverage for China over Greece.

Caveat: The empirical evidence of leverage is derived from a single case study of one Chinese SOE in a Greek port, which may not fully represent how other state-owned enterprises operate in different national contexts.

Journal of Transport Geography · pdf · doi

Beyond the buffer: an activity-based approach to heat exposure assessment

This study develops an activity-based heat exposure metric that calculates the microclimate along routes from residences to daily destinations, comparing it against traditional residence-based buffer and neighborhood metrics. The analysis reveals that neighborhood-level microclimate is only moderately correlated with actual route-based exposure. It also shows that higher green infrastructure within a residential buffer leads to an underestimation of activity-based heat exposure.

Why it matters — It demonstrates that standard area-based exposure metrics fail to capture actual human heat exposure because residents rarely traverse the green spaces located within their neighborhood buffers on their daily trips. This allows planners to shift cooling interventions from underutilized green zones to the specific transit corridors and pathways that people actually walk.

Caveat: The study's findings rely on simulated or modeled routes to daily destinations rather than observed GPS tracking of actual resident movements.

Landscape and Urban Planning · doi

Sensitivity analysis of multi-element probabilistic collocation methods in stochastic Lighthill-Whitham-Richards traffic flow modeling

This paper introduces a computational framework that combines the multi-element probabilistic collocation method (ME-PCM) with an implicit gradient computation technique to optimize road design under uncertainty. Using the Lighthill-Whitham-Richards traffic flow model with random inputs, the framework treats road geometry parameters as decision variables to minimize a robust objective based on the 97.5th percentile of total travel time. Numerical experiments show the method achieves approximately second-order convergence in uncertainty quantification and produces accurate discrete gradients.

Why it matters — It provides a computationally efficient pathway for stochastic traffic flow optimization, allowing gradient-based optimizers to converge to optimal road geometry designs in fewer iterations and less time than Monte Carlo or gradient-free methods.

Caveat: The performance and convergence of the framework are demonstrated through numerical experiments rather than real-world deployment or empirical traffic datasets.

Transportation Research Part C Emerging Technologies · pdf · doi

Beyond Binary Rooftop Mapping: A Four-Class Deep Learning Framework for Green Roof Potential Assessment from Open Swiss Geospatial Data

The study developed a modified deep convolutional neural network framework based on Roofpedia to classify rooftops into four distinct categories: existing green roofs, potential green roofs, solar-paneled roofs, and unsuitable flat roofs. The model was applied to Bern, Switzerland, using open-source Swisstopo datasets, including SWISSIMAGE orthophotos, swissSURFACE3D elevation data, and swissTLM3D building footprints.

Why it matters — It replaces binary rooftop mapping with a multi-class classification system that simultaneously identifies existing green infrastructure and realistic expansion opportunities, allowing planners to target urban heat island mitigation more precisely.

Caveat: The framework was tested and validated only in the city of Bern, Switzerland.

arXiv · pdf

Gridnberg: A Topography-Aware Pedestrian Routing Dataset for New York City

The Gridnberg dataset enriches the NYCWalks pedestrian network with vertex-level elevations derived from the New York City Planimetric Database, retaining 313,184 of 315,577 source segments (99.24%). By averaging elevation observations within a 50-meter radius of each vertex, the workflow calculates direction-specific cumulative ascent and descent to produce three distinct routing costs: horizontal distance, a comfort-oriented slope score, and an accessibility-sensitive slope score.

Why it matters — It provides a reproducible, topography-aware routing dataset that moves beyond flat, planar graph representations of urban streets, allowing planners to model how slope and grade variations affect pedestrian impedance and route choice.

Caveat: The dataset is currently limited to New York City and relies on a 50-meter radius averaging method to smooth elevation observations.

arXiv · pdf

A Knowledge-Grounded Behavioral Reasoning Framework for Training-Free Urban Healthcare OD Prediction

This paper introduces a training-free urban healthcare origin-destination (OD) prediction framework that replaces deep learning models with collaborative Large Language Model (LLM) reasoning over a structured urban knowledge graph. Tested on a real-world dataset from Shenzhen, China, covering 137 hospitals and 6,341 prediction tasks, the framework achieved a Common Part of Commuters (CPC) score of 0.5449 and a Top-1 accuracy of 66.19%, outperforming conventional Multi-Layer Perceptron baselines by 22.1% on Top-5 accuracy.

Why it matters — It demonstrates that structured, knowledge-grounded behavioral reasoning can outperform traditional supervised deep learning models for spatial interaction modeling without requiring expensive model training or sacrificing interpretability.

Caveat: The framework's performance was evaluated using a dataset from a single city, Shenzhen, which may limit immediate generalizability to other urban contexts with different healthcare systems and mobility patterns.

arXiv · pdf

Cross-country structure of a sexual contact network derived from a commercial-sex review platform

The study analyzed a bipartite commercial-sex contact network of 1,436,738 client-sex worker links spanning 1999 to 2024, extracted from reviews on The Erotic Review across 97 countries and territories. The network formed a giant connected component characterized by short average path lengths, high bipartite clustering, and disassortative degree correlations. A small fraction of clients who reviewed sex workers in multiple countries acted as spatial bridges, while long-term users created temporal bridges that compacted the network over time.

Why it matters — It reveals the specific structural roles that highly active, mobile clients play in linking geographically and demographically distinct sexual networks, providing empirical parameters for modeling global STI transmission pathways.

Caveat: The network structure is derived from self-reported digital traces on a commercial review platform, which may introduce reporting biases and overrepresent clients who actively post reviews.

arXiv · pdf