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How do you see your city in 2050?

And how can AI support in climate change adaptation?

What was UC1-UC4 seminar about?

Both Use Cases developed several ideas during the last months about potential outcomes of their work. After an introduction of Stefan on FAIRiCUBE, the UCs presented their possible product options. Presentations were followed by an interactive session, during which feedback has been collected from stakeholders in European cities. Participants included, for example, Ville de Luxembourg, European Environment Agency, Wageningen Environmental Research, Epsilon Italia and Natural History Museum Vienna.

Did you miss the seminar and are you curious about the possible products? Do you think these potential products would support tackling climate change challenges in your city? Feel free to contact us if you like to brainstorm further!

UC1 and UC4 are planning to have another seminar on specific EU cities, so remain up do date!

Read more on the focus of the use cases and the results options here


The primary goal of UC1 is to furnish stakeholders from European institutions (policy makers, urban planners and NGOs) with a comprehensive “toolkit,” to make well-informed decisions to address the multifaceted impacts of climate change. These impacts are interrelated with multiple factors such as land use activities around cities and the local socio-economic setting. Large datasets on these factors are available, but they are complex to integrate and analyse due to their different sources, formats and quality. Data cubes and the integration of data therein allow to assess their relationship. UC1 will perform a cluster analysis of EU cities using data from the climate, land cover/land use and socio-economic domains. This initiative will be executed on dual fronts: at the European level, encompassing approximately 800 cities, and at the local level, involving a focused approach on selected few test cities.  

UC1 product options

Option 1: Impact of higher temperatures due to climate change (and the Urban Heat Island effect)

The temperature in cities is oftentimes higher than in their surrounding rural environments due to the large area of sealed surfaces that emit heat. This effect is called Urban Heat Island and is often more pronounced at night-time. Together with the warming climate this can cause many problems for citizens, in particular for vulnerable groups, such as elderly people. To identify cities with a higher impact of heat waves and temperature related phenomena, we aim at clustering cities based on land-related, climatic and socio-economic parameters. This will enable us to identify groups of cities with lower and higher impacts and analyse the parameters that have the highest relevance for this situation. This could then be a means for further evaluating possible reasons, take measures and, possibly, look at best practice examples, i.e., the cities with the best situation, to identify parameters that could be influenced and changed to improve the situation. 

Option 2: Planning of green urban areas (EGD)

According to the European Green Deal, cities need to increase their area of green spaces. However, they have oftentimes restrictions where new green areas can be planned and developed, at the same time, there is a lack of knowledge on where is the best place to develop them (in terms of bringing the most benefit to citizens). This product aims at helping cities to identify the best places based on their location as a starting point for the final decision.

Option 3: Flood protection

In addition to warming temperatures, the changing climate also leads to heavier rainfall events which then cause heavier flooding, both river flooding as well as flash floods. To adapt to this situation, it will be necessary for cities to identify areas where construction should be avoided or where other protective measures need to be put in place. Thus, this product aims at identifying those areas based their location, the population at risk and precipitation and flooding events.

Option 4: Identification of ecological factors for Drosophila melanogaster variations in cities

This product option stems from the possible synergy with another UC that landscape genomics of the fruitfly Drosophila melanogaster. The main objective of Use Case 3 is to establish and test an analytic workflow to intersect genomic data of Drosophila melanogaster with quantitative rasterized environmental and climate data. Linking earth observation and genomic data of organisms living in heterogenous environments allows exploring how the environment influences evolutionary processes that shape genetic variation in natural population and can be used to study the mechanisms of adaptation to specific environmental conditions.

One aim of the use case is to look into cities and complement the existing sampling collection network by own collections of samples and their sequencing to study the genomic variability and possibly trace back travel routes. Geospatial environmental, climatic as well as socio-economic data can help on the one hand to plan the sampling and on the other hand to support the analysis and interpretation of the sequencing results. A big data cube that integrates the different data sets would be a very good basis for that.


The aim of UC4 is to improve understanding of energy saving in buildings. Buildings contribute significantly to energy use (40%) and greenhouse gas emissions (36%). The EU aims to improve building energy performance to achieve carbon neutrality by 2050 through initiatives like the “Renovation wave” and “Fit for 55”. Yet, the current rate of energy retrofitting is insufficient, hindering progress towards EU climate goals. To improve energy retrofitting rates, a comprehensive approach is essential, considering both broad city/country strategies and detailed building-level analysis. This involves a bottom-up approach, assessing individual buildings to prioritize renovation efforts effectively. UC4 facilitates this process by evaluating residential building energy performance and determining renovation priorities through multi-objective optimization. In addition, UC4 uses and evaluates the power of machine learning in birding the gaps in data and finding new model to extract new information from the existing data. Some of these activities are data gap filling, classification, and semantic segmentation that UC 4 is testing.

UC4 product options

Option 1: Planning for environmentally sound energy retrofitting in residential buildings

Buildings are the cornerstone of our civilization as they provide shelter to protect us from the local environment. Despite their importance, they are responsible for more than 40% and 36% of final energy use and GHG emissions, respectively. Most of the today’s buildings were built decades ago without having sustainability in mind which makes them energy inefficient compared with today’s energy standard. At the same time, it is expected that many of the building that are in use today, will be in use by 2050. Improving energy performance of buildings is one of the EU’s priorities to secure its carbon neutrality goal by 2050. “Renovation wave” and “Fit for 55” are a set of policies introduced by the EU with the aim to pave the way to achieve net zero carbon emissions. However, this is a challenging task to fulfil as the current rate of the energy retrofitting is the EU is not at a satisfactory level. The low rate of energy retrofitting combined with different shocks (e.g., the invasion of Ukraine and COVID-19 pandemic) have slowed down the EU to be on its climate goal.

Changin the current rate of energy retrofitting requires a holistic approach (at a city/country level) while maintaining a high level of detail is needed to ensure its effectiveness. This implies that there is a need to take a bottom-up approach, quantifying information for individual buildings, and later identified buildings that need to be prioritized for renovation. This product aims at providing such an assistance where it estimates energy performance of residential buildings and later quantifies renovation priorities by means of a multi-objective optimization approach.

Option 2: In-use building materials

Buildings require immense amount of natural resources to be built, and it is expected that the demand for additional buildings will continue to increase due to the constant growth in population and need for new settlement. At the same time, buildings go through a range of maintenance and rehabilitation during their lifetimes in order to keep/improve their service level.

On the global scale, the building and construction sector annually consumes half of the extracted construction minerals (i.e., 43 Gt)[1]. The sector is extremely dependent on the inflow of virgin materials, as the large quantity of materials are lost at the end of their life cycle. The loss from the construction and demolition is about 40% of the original mass when extracted. Such a needs a circular solution approach to make use of building materials at the end of their lifetimes. However, our knowledge is limited when it comes to mapping the availability of construction materials, and their availability in the future. This product aims at estimating the availability of building materials in the residential buildings in a way that it presents the stocks of building materials in a city.

Option 3: 2.5D model of buildings

Currently, little information is available on 3D representation of buildings. The 3D model of buildings gives research and planners the possibility to carry out various investigations, like noise propagations, pollutant transport, and possibility of solar thermal/PV as well as green roof installation. For some big cities, the 3D representation of buildings might be available; however, not all cities have alike coverage. This product aims at providing a 2.5D model for cities to assist researchers and planners to be able to tap into new findings.

[1] Global Status Report, Towards a zero-emission, efficient and resilient buildings and construction sector, 2018. URL:;jsessionid=686B0E237D0219EA209DE3B4C4CCD5DB