Thibaud Chassin

Citizen contributions from online participatory mapping platforms surface local knowledge and lived experiences that can inform urban decision-making. However, as these initiatives scale, practitioners increasingly struggle to extract meaningful information. While frameworks and methods to analyse the spatial dimension of these contributions exist, there is a lack of approaches leveraging their free-text content. This paper investigates whether small local Large Language Models (LLMs) can help in structuring this data via (i) sentiment polarity analysis and (ii) thematic classification. Our case study is based on an openly available dataset from 2021 for the city of Prague (N≈30000), where residents’ emotional and perceptual relationships to the city were collected. We evaluated the performance of three models across two languages (Czech and translated English text) on 732 randomly sampled and manually annotated citizen comments, using five repeated runs to account for output variability. Our results revealed that OpenEuroLLM-Czech:12b achieved the highest weighted F1 score for sentiment analysis and Gemma3:12b for thematic classification (85.2% and 70.4%, respectively). All LLMs also exceeded a RoBERTa sentiment classification baseline (weighted F1 score 72.1%) on the sentiment task. Overall, this study suggests a potential for using LLMs in participatory mapping, with implications for more engaging and inclusive participation. We also call for the development of ethical guardrails for the responsible use of LLMs in participatory mapping.

Rapid urban expansion in transitional regions intensifies interactions between human activities and ecological systems, yet quantitatively capturing the spatial balance between anthropogenic pressure and ecological capacity remains a major scientific challenge. Existing approaches often conceptualize human–environment interactions or focus on land-change outcomes without explicitly measuring coupling strength, direction, and spatial dynamics. This study introduces a quantitative geospatial analytics framework to assess human–environment coupling across space and time, using Prishtina (Kosovo) as a representative transitional urban system.The framework conceptualizes the urban system through two spatially explicit and normalized gradients: an anthropogenic forcing gradient, representing cumulative human pressure, and a geo-ecological capacity gradient, capturing the environment’s ability to regulate and respond to that pressure. These gradients are derived from harmonized multi-source geospatial indicators, including satellite-based environmental proxies and complementary spatial datasets, and are integrated through standardized preprocessing, normalization, and data-driven weighting procedures to ensure spatial comparability and analytical robustness.Human–environment coupling is quantified using a normalized spatial index ranging from 0 to 1, where higher values indicate balanced interactions and lower values signal increasing imbalance between anthropogenic forcing and ecological capacity. Spatial statistical techniques, including spatial autocorrelation and hotspot analysis, are applied to examine clustering patterns, transition zones, and emerging disequilibrium, while temporal analysis supports the exploration of coupling trajectories under rapid urban transformation.The proposed framework enables spatially explicit investigation of human–environment coupling heterogeneity within Prishtina and supports the identification of zones characterized by balance, dominance, or transition. By integrating multi-source geospatial data with advanced geospatial analytics, the study offers a transferable quantitative approach for diagnosing human–environment interactions and informing sustainability-oriented spatial planning in transitional urban regions.

Interactive 3D e-participatory methods have the potential to improve the efficiency and inclusivity of current participatory processes. Through examples and hands-on activities, this introductory lecture aims at familiarizing the students with the complexity of these methods, helping them to better identify their use, their design components, and the context of their applications.

The opportunities provided by adopting digitally-generated visual tools in urban participatory planning are compelling. These visual tools can promote interactions between authorities and citizens and among citizens. However, the urban participatory practices of these tools are often described from an academic perspective, which leads to a lack of knowledge from the practitioner's outlook. This study investigates practices of 3D visual tools in applied urban projects. The applied projects were recovered from media coverage. The objective is to describe participatory projects and their adopted 3D tools with a contextual and technical lens. The findings demonstrate that 3D visuals are mostly adopted for communication with a realistic representation and limited interaction in the later stage of the project where negotiation margins are insufficient at a small and medium urban scale. A better understanding of applied practices can help to introduce guidelines that support practitioners in designing approaches that benefit from the full potential of 3D visual tools.

Typical urban participatory approaches engage citizens through lengthy sessions far from the area under transformation by an urban project. Several issues result from these settings of involvement including the mobilization of similar individuals, overwhelming participatory codes, or a gap between the affected urban landscape and the location of the session. This study introduces a modern approach that leverages the use of 3D web applications to address some of the critical challenges of popular participatory sessions. The developed approach, named e-guerrilla 3D participation, is based on five dimensions: immediate participation, ease of use, flexibility, place-based engagement, and immersivity. A prototype complying with these five dimensions was implemented in this study. The prototype promotes an in situ engagement where all the users (without distinction) of a public area can explore a future urban project and get involved within minutes. A usability study conducted with 26 expert and non-expert participants investigated the prototype through a fictive scenario. The findings demonstrate a positive outcome in terms of participatory results that are identifiable with the prototype (highlighting the controversial elements of the projects) and encourage feedback collected during a survey and interview. The usability study suggests key aspects that should be considered to improve the design of participatory sessions and their interactive mediums (or tools), such as realism, affordance, incentive, and purpose. The promising participatory approach (and prototype), which was unpacked step-by-step in this study, does not replace typical practices but could help to complement them by reaching a non-selected and broader public; hence leading to the design of more inclusive participatory approaches.

The gradual institutionalization of public participation increasingly compels local authorities to partially share their power over the transformation of urban areas. The smooth running of a participatory session is based on selecting the appropriate type of interaction, or medium, which supports the local authorities to reach and interact with a targeted public. However, local authorities often appear unfamiliar with the organization of interactive sessions with the population. This article introduces an evaluation framework that focuses on the access conditions of participants to the sessions of interaction. This novel perspective aspires to assist the local authorities in their decision to adopt a participatory medium (or method of interaction). Seven dimensions are investigated to this aim, namely accessibility, availability, adequacy, affordability, acceptability, awareness, and attractiveness (the last dimension is introduced in this article). In light of two real case scenarios that occurred in Western Switzerland, the use of the access framework is investigated for two potential purposes: (1) supporting the choice of a medium for an interactive session according to the urban project’s context and the targeted public; and (2) improving future participatory approaches by assessing the representativeness of participants attending a past session in comparison to the originally targeted public.

Data quality is the primary concern for researchers working on citizen science projects. The collected data by citizen science participants are heterogeneous and therefore must be validated. There are several validation approaches depending on the theme and objective of the citizen science project, but the most common approach is the expert review. While expert validation is essential in citizen science projects, considering it as the only validation approach can be very difficult and complicated for the experts. In addition, volunteers can get demotivated to contribute if they do not receive any feedback regarding their submissions. This project aims at introducing an automatic filtering mechanism for a biodiversity citizen science project. The goals of this project are to first use an available historical database of the local species to filter out the unusual ones, and second to use machine learning and image recognition techniques to verify if the observation image corresponds with the right species type. The submissions that does not successfully pass the automatic filtering will be flagged as unusual and goes through expert review. The objective is on the one hand to simplify validation task by the experts, and on the other hand to increase participants’ motivation by giving them real-time feedback on their submissions. Finally, the flagged observations will be classified as valid, valid but uncommon, and invalid, and the observation outliers (rare species) can be identified for each specific region.