2026-09-29

7 arXiv categories· 96 journals· 3888 candidates — 8 worth your time· 75 without an open abstract

Headline

An urban collective-risk dilemma dataset on air pollution mitigation, from Barcelona

Today, together

tag shift
no tag ran above its 30-day average
shares references
no items share references today counted over the 8 papers published above
on the same shoulders
no foundation work was cited by four of the day's papers counted over the 77 of this day's 83 named papers whose reference lists we have — standing on the same older work is not the same as being about the same thing
first appearance
Roskilde University none of them on a paper we published in the 109 days before this issue

Two counts, not one counted twice: every row here but “on the same shoulders” counts the papers published above, and that one counts every paper this day named — those and the ones under Also published today, whose abstracts we could not read.

A citizen science behavioural dataset captures 4,620 individual contribution decisions made by 462 participants during a ten-round collective-risk dilemma experiment on air pollution mitigation in Barcelona, Spain. Another study investigates how municipalities in Denmark and Sweden attempt to integrate 3D models and urban digital twins into their planning workflows. Finally, a multimodal AI-assisted analysis examines approximately 2,700 Instagram posts spanning a three-year period following the July 2021 extreme flooding in western Germany to understand visual narratives of disaster.

datapreprint

Marc Sadurní, Martín F. Díaz, Julián Vicens, et al.
arXiv physics.soc-ph

survey · Barcelona

A citizen science behavioural dataset of an urban collective-risk dilemma on air pollution mitigation under resource inequality

This dataset captures 4,620 individual contribution decisions made by 462 participants across 77 six-player games during a ten-round collective-risk dilemma experiment in Barcelona, Spain. The experiment tested three wealth endowment treatments (one equal and two unequal) to observe how resource disparity affects contributions toward a shared public goods target. Each participant's decision trajectory is linked to their local district's nitrogen dioxide levels, socio-demographic survey responses, and environmental-justice beliefs.

Why it matters — The dataset provides a rare empirical link between controlled behavioral experiment decisions on public goods and the real-world environmental conditions, air pollution levels, and socio-demographic backgrounds of the participants.

Caveat: The behavioral data is derived from a gamified lab-in-the-field experiment using monetary endowments, which may not fully capture how individuals respond to real-world air pollution mitigation costs.

arXiv · pdf

published: Computational Urban Science

Emil Nørager Kruse, Thomas Theis Nielsen, Maja de Neergaard
Computational Urban Science

Roskilde University

3D Modeling in Geospatial Applications · Smart Cities and Technologies · BIM and Construction Integration · interview · Roskilde University

From epistemic promises to real world practices: the ongoing becoming of 3D models and urban digital twins in municipal planning

This study investigates how municipalities in Denmark and Sweden attempt to integrate 3D models and urban digital twins into their planning workflows. Using data from municipal pilot projects, 3D workshops, and interviews with urban planners, architects, GIS specialists, and technology vendors, the research documents the friction between high-level technological promises and daily municipal operations.

Why it matters — It reveals that the widespread adoption of urban digital twins is hindered by practical barriers like fragmented data infrastructures, mismatches between national frameworks and local needs, limited organizational capacity, and conflicting expectations of the technology's purpose.

Caveat: The findings are based on qualitative case studies of municipal pilots in Denmark and Sweden, which may reflect specific Scandinavian institutional contexts and governance structures.

Computational Urban Science · pdf · doi

published: Computational Urban Science

Manal Ginzarly
Computational Urban Science

University of Liège

Public Relations and Crisis Communication · Disaster Management and Resilience · Misinformation and Its Impacts · University of Liège

Visual narratives of disaster on Instagram: a multimodal AI-assisted analysis

The study analyzed approximately 2,700 Instagram posts spanning a three-year period following the July 2021 extreme flooding in western Germany. Using ChatGPT-4 supervised by humans to classify images into six visual themes, the method achieved an 80.73% agreement rate and a Cohen's kappa of 0.74 compared to manual coding. The analysis mapped how visual themes shifted from immediate damage to long-term recovery, alongside a corresponding emotional transition from anxiety to hope.

Why it matters — It demonstrates that AI-assisted visual classification can reliably scale up the analysis of social media imagery during crises, revealing nuanced emotional and narrative shifts that traditional hashtag-only analyses fail to capture.

Caveat: The findings are based on a single extreme flooding event in Germany, which may limit how well these specific narrative and emotional trajectories generalize to other disaster types or cultural contexts.

Computational Urban Science · pdf · doi

published: Discover Cities

Yvette Nana Birago Antwi, Stephen Appiah Takyi, Cyril Djangmah Nartey, et al.
Discover Cities

Kwame Nkrumah University of Science and Technology

Urban Green Space and Health · Land Use and Ecosystem Services · Urban and Rural Development Challenges · survey · interview · Kwame Nkrumah University of Science and Technology

The fading Garden City: environmental change, public awareness and the quest for urban sustainability in Greater Kumasi

This study analyzed environmental degradation in the Greater Kumasi Metropolis using Landsat imagery from 2015 to 2025, alongside a survey of 183 residents and interviews with planning and environmental officials. The spatial analysis revealed that natural areas shrank by 31.1%, dropping from 50.7 square kilometers to 34.8 square kilometers, while built-up areas expanded by 8.5%. Although 74.2% of surveyed residents are aware of local environmental sustainability programs, 70.7% view the city as unsustainable, and institutional fragmentation and political interference hinder policy enforcement.

Why it matters — The study quantifies the rapid loss of green infrastructure in a major West African urban center and demonstrates a stark disconnect where high public awareness of environmental programs does not translate into urban sustainability due to systemic governance and enforcement failures.

Caveat: The resident survey relies on a relatively small sample size of 183 participants to represent the diverse socio-economic communities of the Greater Kumasi Metropolis.

Discover Cities · doi

preprint

Shoichi Otomo
arXiv cs.CY

The Potential of Nighttime Light Imagery for Detailed Local Economic Analysis

This study details a raster processing technique for satellite nighttime light intensity imagery and applies it to Yuzawa Town in Niigata Prefecture, Japan. It analyzes the spatio-temporal relationships between tourist arrivals, local sports and tourist attractions, and various local statistical datasets.

Why it matters — The method demonstrates that nighttime light data can capture fine-grained, intra-municipal economic dynamics and tourism activity that standard macroeconomic indicators fail to detect.

Caveat: The empirical analysis is limited to a single small town focused on sports and tourism, which may limit the direct generalizability of the specific spatio-temporal relationships to other municipal contexts.

arXiv · pdf · doi

preprint

Mohammad Farhan, Dorota Kuziak, Iztok Peterin, et al.
arXiv physics.soc-ph

Transportation and Mobility Innovations · Urban Transport and Accessibility · Transportation Planning and Optimization

Vertices that belong to every minimum dominating set of a graph and their connection with transportation sharing systems with study cases in Campo de Gibraltar area

This study models shared transportation station placement by identifying 'dominating forced vertices'—nodes that must appear in every minimum dominating set of a graph to guarantee coverage. The researchers proved that identifying these vertices is co-NP-hard, established a theoretical upper bound showing their count cannot exceed one-third of a graph's vertices, and developed an iterated greedy metaheuristic to approximate these critical locations. The approach was validated on strong grid graphs and applied to the road networks of Algeciras and La Línea de la Concepción, Spain, to identify optimal scooter-sharing station locations.

Why it matters — It establishes the mathematical limits of optimizing micro-mobility networks, proving the computational hardness of finding absolute critical stations while providing a practical heuristic to bypass this limitation in real-world municipal planning.

Caveat: The proposed station locations are based purely on graph-theoretic road network topology and do not incorporate empirical travel demand, land use, or demographic data.

arXiv · pdf

preprint

Shoichi Otomo
arXiv cs.CY

Correlation Between Nighttime Light and Various Statistical Indicators in Japan

This study establishes a methodology for calculating regional nightlight intensity across Japanese prefectures and municipalities, evaluating its correlation with local socio-economic metrics. The analysis demonstrates that city-level nighttime light intensity serves as a reliable proxy for public indicators such as gross domestic product, employment rates, population density, and educational attainment.

Why it matters — It validates the use of satellite-observed nightlight data as a rapid, alternative measurement tool for socio-economic conditions in Japan, particularly for conducting real-time economic impact assessments during sudden disruptions like the COVID-19 pandemic.

arXiv · pdf · doi

preprint

Zhoufu Wang, Baoshen Guo, Zhiqing Hong, et al.
arXiv cs.SI

Human Mobility and Location-Based Analysis · Transportation and Mobility Innovations · Data Management and Algorithms

Plan-to-Synthesis: Cross-City Human Mobility Generation via Semantic Latent Flow Matching

The researchers developed SeMoFlow, a hierarchical human mobility generation framework that uses semantic latent flow matching to synthesize realistic point-of-interest (POI) trajectories across different cities. The model maps heterogeneous POIs into a shared cross-city representation space using hierarchical Semantic IDs, combining an autoregressive planner for coarse-grained patterns with a flow matching realizer for fine-grained POI suffix latents. The framework was evaluated on large-scale, multi-city datasets, demonstrating higher trajectory fidelity and better preservation of city-specific mobility motifs than existing baselines.

Why it matters — It provides a scalable, cross-city transferable mobility generation method that avoids both the high computational costs of large language models and the city-specific retraining limitations of traditional diffusion-based models.

arXiv · pdf

Still cited

Sara Meerow, Joshua Newell (2015), Defining urban resilience: A review 1 of today's items cite it · 46 of 3240 in the archive stand on it

Also published today

These appeared today in journals we track. Their abstracts are not openly available, so we cannot summarise them.