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As a place to live, work and play, urban spaces are the nerve centers of human activity. The urban spaces, which are becoming increasingly extensive and dense, are particularly sensitive to the effects of climate change. Greening cities has been identified as one of the most effective ways to mitigate one of these effects, the urban heat island. In this context, the city of Liège, Belgium, has adopted a greening plan, called “Plan canopée”, to increase the tree canopy area at city level. The aim of this study is to present the methodology used to objectivize and prioritize the selection of potential planting sites. This research proposes the production of a series of spatial indicators allowing, on the one hand, the precise mapping of urban surfaces ready for planting, and on the other hand, the objective prioritization of city districts to be vegetated. The research integrates airborne image classification, urban heat island modeling and a series of reference geodata combinations. The set of data produced provides a transparent decision support tool to the authorities for the operational planning of tree plantations. These results contribute to the development of a planting strategy that maximizes the chances of ownership by the citizens, and consequently the sustainable and effective impact of the achievements.

This document is the deliverable D3.4 of the CURE (Copernicus for Urban Resilience in Europe) Project. The goal of this deliverable is to fully describe the development process of the 11 CURE Cross-Cutting Applications, including the list of Copernicus and non-Copernicus data used as input, the algorithms and methods adapted for the needs of CURE, example of resulting products for the CURE front-runner and follower cities and the methods evaluation and the dockerization process.

The aim of this deliverable is to access the CURE services against its real impact for the stakeholders considered. The work builds upon the data collection and results of Task 6.1 the Scenario Development (D6.1) complemented by further data collection and literature research.

This document constitutes a digital collection of all sample products from the developed cross-cutting applications. The complete Urban Cross-cutting Applications Sample Dataset can be found in https://doi.org/10.5281/zenodo.5812049. The purpose of this document is to describe the database of sample products from the cross-cutting applications developed in CURE and to define the data specifications.

This document aims to describe the final updated methodology of the CURE Cross-Cutting Applications (after their first description in Deliverable D3.1) and to describe and explain in more detail the sample results for the front-runner and follower cities that are submitted in Deliverable D3.3.

This document focuses on the aspects of the services that are relevant to a potential uptake of the CURE System in the Copernicus architecture. In the context of this Deliverable, a) the structure of Copernicus is analysed, aiming at elements defining a typical Copernicus service; b) the current status of the CURE applications is assessed in light of the elements required for uptake as a Copernicus service; and c) a pathway is presented towards a mature CURE service portfolio that would fit perfectly in the Copernicus program through 3 alternative scenarios.

This document aims to describe in more detail the CURE cross-cutting applications and to summarize the preparatory activities for the individual applications development, following the first description in Methodology Review and Selection Deliverable (D1.3). The purpose of each CURE application, the data and methodology used, as well as the output features and characteristics are presented. Preliminary results of some applications for the front-runner cities are demonstrated, where possible, and feedback is provided on the stakeholder needs, as identified in Summary of User Requirements Deliverable (D1.1).

EEA assessment report presenting the status quo of adaptation to climate change at the local government level, with particular focus on cities. The assessment presents the overview of climate risks to cities, types of adaptation responses, extent of adaptation planning and actions at the [loal (SIC)] level in Europe and opportunities to scale up and speed up implementation of adaptation to climate change at the local level.

Heat waves are projected to become more frequent, longer-lasting, and intense. At the same time, urban areas are confronted with the urban heat island (UHI) phenomenon, which adds to the thermal stress experienced during hot spells. Focusing on the Paris area during the hot summer of 2003, we investigated the influence of heat waves on UHI intensity, i.e., the urban-rural temperature contrast. In a first step, this was done based on observed temperatures from an urban and a rural site, showing that per degrees C increase in the daytime temperature, the nighttime UHI intensity increased by 0.086 degrees C. Recognizing the limited spatial representativeness of the urban experimental site, located in a park, we then performed simulations with an urban climate model, covering the wider Paris area for the summer of 2003. First, a validation was done using the aforementioned temperature measurements to do so. Subsequently, we estimated the sensitivity of the nighttime UHI intensity with respect to the daytime temperature, this time using simulated temperatures of the densely built-up areas in the center of Paris, yielding an increase of UHI intensity of 0.19 degrees C per degrees C increase in the daytime temperature. While these results only apply to the domain and period studied, they do confirm recent reports that the UHI intensity increases during heat waves. The results also show that for the cooler parts of the urban fabric (e.g., parks), the UHI intensification during heat waves is around half of that of the dense urban fabric, thus providing some insights into possible mitigation strategies for the future.