Chika Ichimiya (p), Kazunari Tanaka

Francesca Rubiconto

In Japan, there has been a noticeable increase in urban migration following the COVID-19 Pandemic. The concentration of people in metropolitan areas has revitalized local activities, bringing life back to the streets. However, this concentration of people significantly impacts pedestrian movement and influences the surrounding urban spaces. Additionally, with the increasing likelihood of seismic events, it is crucial to understand pedestrian movement for effective evacuation planning. Furthermore, the rise in cycling due to factors such as aging populations and tourism has contributed to a higher incidence of pedestrian-cyclist collisions, particularly on sidewalks. This trend underscores the importance of addressing pedestrian-cyclist coexistence in urban planning.
The primary objective of this study is to visualize the impact of pedestrian movement on other modes of transportation, as an essential consideration in the design of safe and comfortable urban spaces. During peak times, pedestrians often exhibit movements distinct from their actions when alone, resulting in more complex patterns of movement within crowded public spaces. This phenomenon, referred to as "small-scale crowd flow," has the potential to increase the risk of accidents, particularly as pedestrians inadvertently encroach on bicycle lanes.
The study focuses on the analysis of small-scale crowd flow, specifically examining pedestrian movement through the extraction of coordinates. The results indicated that as pedestrian density increased, movement patterns became linear, while lower densities led to a dispersal of pedestrians. This suggests that spatial density plays a significant role in shaping pedestrian movement. At densities exceeding 0.6, it was observed that pedestrians tended to alter their paths to circumvent one another, further emphasizing the relationship between pedestrian density and movement patterns. We report differences in the shape of pedestrian space and their movements in urban spaces.

Francesca Rubiconto (p), Sol Maria Halleck Vega, Eveline S. van Leeuwen

Michał Künstler

Due to the length and complexity of supply chains, changes in food consumption patterns in one metropolitan region can transform production patterns in other sectors and countries. Therefore, they cause complex synergies and trade-offs between environmental and socioeconomic goals at the local and global level. We argue that the dissemination of cross-scale consumption-based simulation models is crucial to investigate these complex multilevel effects and promote sustainable food systems.

Michał Künstler (p)

Andrea Omizzolo

Satellite imagery has become a valuable tool for estimating regional economic prosperity, with nighttime light intensity (NTL) and daytime satellite images being two widely used data sources. This study compares the predictive performance of machine learning models trained on NTL and daytime imagery for estimating economic well-being at different regional levels. Using data from European countries at LAU2, LAU1, NUTS3, and NUTS2 levels, we construct separate models for each data type and an ensemble model that integrates both sources to assess the potential performance gains.

Advanced machine learning techniques are employed , including XGBoost and convolutional neural networks (CNNs), to develop predictive models for economic indicators. The models are evaluated using standard performance metrics and further analyzed with explainable AI (XAI) techniques to interpret the contribution of different features in economic prediction. XAI methods help uncover the relative importance of nighttime lights and daytime image-based features, providing insights into their complementarity.

The findings contribute to the ongoing discussion on the effectiveness of remote sensing data for economic modeling. By comparing models based on individual data sources and their fusion, we determine the extent to which combining NTL and daytime imagery enhances predictive accuracy. The study also explores the scalability of these approaches across different spatial resolutions, offering valuable insights for policymakers and researchers interested in regional economic assessments. The results have practical implications for using satellite-based machine learning models in economic forecasting, especially in regions where traditional economic data collection is limited or delayed.

Andrea Omizzolo (p), Peter Laner , Alessia Pilati, Filippo Favilli

Niklas Rudholm

Functioning ecological corridors between protected areas are fundamental for biodiversity. However, the integration of conservation measures in landscapes outside protected areas in the Alpine spatial planning systems is lacking and pressures of human activities are increasing, such as the recent acceleration in the renewable energy development. Therefore, the Interreg Alpine Space “PlanToConnect” project recently has developed a model for a coherent ecological network of protected areas in the Alps and demonstrated how it can be broken down to regional and local scales.
Based on the existing approach of the Continuum Suitability Index and Strategic Alpine Connectivity Areas, a structural ecological network model to connect protected areas and highly natural areas in the Alps was elaborated by a least-cost-path analysis. The model was used in the study region South Tyrol, and it was cross-checked with a regional GIS model for red deer. First verifications of the linkages were conducted by site visits and tracking snow trails on local level.
Authors aim at presenting the process and the result of the application of the model to the pilot region of South Tyrol, believing that what emerged may stimulate further research steps and serve as blueprints for improving and securing the permeability for wildlife species and the designation of wildlife corridor at different level of spatial planning. The analysis presented could offer concrete tools for planning administrations to facilitate transboundary efforts and enhance ecological networks at both regional and local levels.

Kenneth Carling, Ebba Henrekson, Vijay Paidi, Niklas Rudholm (p), Eliel Stenström

Chika Ichimiya

Remote areas in Sweden are characterized by considerable distances and time delays in the treatment of trauma patients. Thus, having a dense network of emergency treatment centers (ETCs) located in a manner that minimizes travel distance and time-to-treatment seems prudent.

Despite the importance of time-to-treatment, there have recently been several closures of ETCs in Sweden. In Västra Götaland, the ETC in Lidköping closed in 2023. In the regions of Kalmar and Västmanland, the full scale ETCs in Oskarshamn and Köping have been reduced to a form of treatment centers that does not treat severe trauma anymore. Finally, in the region of Västernorrland, a decision is likely to be made on March 11 to restructure the ETC in Sollefteå (19 000 inhabitants), no longer providing surgery at that facility. We have investigated how these closures affected travel distances and time-to-treatment both for the population in the region, but also for the population in the affected cities.

Our results show that the closure in Lidköping increased the average distance to the nearest ETC in the region by 1,13 km. The closure in Oskarshamn increased it by 15.14 km, while the closure in Köping increased it by 8.07 km. Finally, the proposed closure in Sollefteå would increase the average distance by 8.20 km. Even in bad traffic conditions, this likely will not increase travel time by more than 20 minutes. However, also including the time to prepare the trauma victim for transport, it could be that in some cases the time-to-treatment will now exceed the so-called golden hour (Cowley, 1975; 1976).

For the inhabitants of Lidköping, Oskarshamn, Köping and Sollefteå, the direct consequences of the closures on time-to-treatment are much more dire. After the closure in Lidköping, the nearest ETC is in Skövde, 48.20 km away with an estimated travel time of 48 minutes. For the inhabitants in Oskarshamn, the nearest fully equipped ETC is in Västervik which is 70.30 km away (67 minutes), while for the inhabitants of Köping the distance to the nearest fully equipped ETC in the region (in Västerås) is 40.60 km away (35 minutes). After the proposed restructuring of the ETC in Sollefteå, all patients requiring surgery would be transported to either Sundsvall or Örnsköldsvik, journeys of roughly 100 kilometers and with transportation times of approximately 90 minutes. In this case, the time-to-treatment would therefore always exceed the golden hour (Cowley, 1975; 1976).