Urban Risks

URiS - ISSN 2516-1857 - © ISTE Ltd

Journal issues

Recent articles

This article examines forms of territorialized climate expertise emerging from collaborations between researchers and urban stakeholders (municipalities, urban planning agencies). By mobilizing the notion of intermediary objects, it analyzes how concrete tools—such as data, maps, geographic information systems, or climate services—function as intermediary objects in the co-production of knowledge to integrate adaptation into urban public action. Based on three case studies (Toulouse, Dijon, Tunis), the article highlights the diversity of collaboration configurations, ranging from simple consultation to action research and the co-construction of climate expertise. These intermediary objects contribute to the emergence of hybrid expertise, fostering mutual learning and reciprocal acculturation between scientists and practitioners. The article emphasizes the importance of relational, temporal, and interdisciplinary conditions in placing climate issues on the agenda and embedding climate change adaptation within urban public action.

The shape of a city, along with the layout of its streets, buildings, and green spaces, can significantly influence the flow of wind through open spaces and the amount of solar radiation received by various surfaces. Wind patterns and solar radiation directly impact urban overheating and the dispersion of pollutants, thereby affecting the quality of the urban environment and the comfort of its residents. The development of geomatics-based models that directly correlate characteristics of the built environment with wind and sunlight fields can aid in informing political decision-making. The aim of this article is to highlight the relationships between the calculation of specific physical variables and geomatics methods, to describe experiments in modeling the radiative and aeraulic physics of urban areas within the context of GIS, and to identify some of the scientific and technical challenges that remain in this field.

Cartographic representation approaches and standards of usual GIS tools may be very different from the tools used by different types of users studying or having to take into account urban climate phenomena (urban planners, meteorologists, climatologists, etc.). They may be insufficient to represent the complexity of the phenomena, characterized by three-dimensional spatial and temporal variability. Through the results of different research projects, this chapter focuses on new approaches to represent and explore climate data at the urban scale. The first part addresses the question of the uses and standards for representing climate and meteorological data in densely populated urban and intra-urban areas, addressing both operational needs and public communication. The second part focuses on visualization approaches for the analysis of simulated data in a scientific context, and addresses approaches to represent the different components of this complex data, notably through 3D environments. Finally, the chapter discusses the value of including users in the design of graphical representations of climate and meteorological data.

Processed data are considered as data obtained by processing raw geospatial data for a specific purpose. This article aims to present elements relating to these objects, which are widely used in the fields of urban climatology and territorial analysis. Several concepts related to processed data are first defined, including the notion of reference spatial unit. A non-exhaustive list of processed data is presented, notably morphological and physical indicators. A selection of typologies and classifications for urban fabric at different spatial scales are also introduced. Applications and uses of processed data are detailed, especially concerning the creation of input data for climate simulation models, climate analysis and territorial diagnosis. The article ends by pointing out the limitations of processed data, and their repercussions on the quality of the information produced.

Climate change is shaking up research agendas and urban planning priorities. A number of events, including floods and heatwaves, are disrupting metropolitan areas. Urban redevelopment to meet these challenges is costly and takes time. Numerical simulation is a great tool for studying urban development scenarios and the effectiveness of development solutions. Numerical models of the urban climate exist and are gradually being improved by the scientific community. These models are parameterised, among other things, by geographical data describing mineral surfaces (buildings, asphalt floors), non-mineral surfaces (water surfaces, herbaceous soils, bare permeable soils) and tree canopies. In this article we study the suitability of existing topographic data for parameterising climate models. We begin by recalling the importance of database specifications for understanding the gap between the real world and the content of databases. We then describe strategies for constructing land cover data suitable for studying the urban climate using national reference systems and in the absence of such data. Finally, we consider the potential contribution of very large-scale data, such as BIM, to the study of urban climates. In conclusion, we propose an improvement in the specifications of national geodatabases to better meet the needs of urban planning in the context of climate change.

Several studies have been carried out on the germination of seeds defecated by lemurs, but the seasonal variation in germination rates and the latent period of seeds of species consumed by Eulemur coronatus have not yet been studied. Two groups of E. coronatus were therefore monitored in order to carry out ex situ germination tests, with the aim of assessing the seasonal variation in the germination rate and the latency period of the seeds of two species consumed (Treculia madagascariensis and Xanthocercis madagascariensis). The focal animal sampling method (Altmann, 1974) was used to collect behavioural data during 2021-2022. The results showed that seed germination rates from fecal matter during the dry season were higher (72.5% and 57.5%) than during the wet season (32.5% and 42.5%) for both species. According to the Cox hazard model, the latent period of fecal seeds is shorter during the dry season for the Treculia madagascariensis species, while for the Xanthocercis madagascariensis species, the latent period of fecal seeds is similar between the dry and wet seasons. The variation in the germination rate and the latent period between the two seasons depends on the species.