climate protection & adaptation

In this session of the Global Mixer, we discovered how Smart City Mannheim uses artificial intelligence and sensor data to create a real-time microclimate model — producing a living digital picture of the city’s climate.

Key takeaways

• Urban climate intelligence: AI and sensor networks enable a detailed, real-time understanding of microclimatic conditions across the city.
• High-resolution modelling: Combining sensor data with simulations allows climate analysis at street-level precision.
• Decision support for adaptation: Real-time models help cities test and prioritise climate resilience measures before implementation.
• Health and risk awareness: Identifying heat islands supports targeted protection of vulnerable populations.
• Operational integration: Living climate models can be embedded into everyday municipal planning and governance.

The Smart City Mannheim is demonstrating how artificial intelligence and dense sensor networks can support climate protection and adaptation at the urban scale. Dr. Robert Thomann presented an AI-powered real-time microclimate model that creates a living digital picture of the city’s climate, enabling highly granular analysis and data-driven, climate-resilient urban planning.

The model integrates data from more than 500 sensors across Mannheim with high-resolution simulations, producing climate insights at a spatial resolution of up to 5 x 5 metres. This level of detail makes it possible to detect urban heat islands, analyse temperature differences between neighbourhoods, and understand how urban morphology, surface materials, vegetation, and shading influence local climate conditions throughout the day.

Beyond mapping and monitoring, the system functions as a practical decision-support tool for municipal action. Real-time and predictive analyses allow planners to assess heat exposure, identify climate risks for vulnerable populations, and evaluate the potential impact of adaptation measures such as tree planting, unsealing surfaces, or redesigning public spaces. By simulating different scenarios, the model supports evidence-based prioritisation and helps align climate strategies with concrete spatial interventions.

By embedding AI-driven climate intelligence into everyday urban governance, Smart City Mannheim demonstrates how digital tools can translate complex environmental data into actionable knowledge. The project illustrates a shift from reactive heat mitigation toward proactive, anticipatory climate adaptation, strengthening both urban resilience and public health in the face of increasing climate extremes.

This event is part of the ISCN Global Mixer, a series of events organized by the International Smart Cities Network. The presentations cover a wide range of topics related to international smart city approaches and provide exciting insights into urban digitalization worldwide - in just 30 minutes.

The Smart City Mannheim approach is designed to be scalable and easy to adapt to different urban contexts. Municipalities interested in applying similar climate intelligence solutions are warmly invited to get in touch with us to explore collaboration and transfer opportunities. Please contact iscn@giz.de for further information and exchange.

The KLIPS project in Dresden demonstrates how AI and real-time environmental data can support climate adaptation in cities. Using over 250 temperature sensors and satellite imagery, the project maps and forecasts urban heat islands to inform data-driven, climate-resilient urban planning.

Key takeaways

• AI for climate adaptation: Machine learning models predict and visualise heat distribution to guide mitigation strategies.
• High-resolution data: Over 250 local sensors deliver real-time microclimatic data, enabling precise mapping of temperature patterns.
• Integration of multiple sources: Combining sensor networks, satellite imagery, and urban data layers creates a dynamic picture of heat exposure.
• Decision support for cities: The KLIPS dashboard helps planners evaluate the effects of greening, shading, and material choices before implementation.
• Community and policy relevance: The approach informs local adaptation strategies and engages citizens through open data.
• Scalable model: The Dresden prototype provides a replicable framework for other cities facing increasing urban heat stress.

In Dresden, Germany, the KLIPS project demonstrates how artificial intelligence and real-time environmental data can support climate adaptation in cities. As Dr. Hendrik Herold from the KLIPS project explained, the system combines more than 250 temperature sensors with satellite, cadastral, and weather data to map and simulate urban heat islands on a hyperlocal scale – providing urban planners with precise insights for data-driven, climate-resilient urban development.

As climate change intensifies, cities across Europe are experiencing longer and more frequent heatwaves. Dense urban structures, sealed surfaces, and limited green spaces exacerbate these effects, creating local heat islands that threaten health and well-being. KLIPS addresses this challenge by using AI to identify and simulate temperature variations across the urban fabric.

The system continuously collects and analyses temperature data from a dense network of sensors placed on buildings, streetlights, and public infrastructure. These measurements are complemented by high-resolution satellite imagery and cadastral information, feeding into an AI model that forecasts temperature distribution under different scenarios. This enables planners to test the potential cooling impact of trees, reflective materials, or urban design interventions before they are implemented.

A key feature of KLIPS is its interactive dashboard, which visualises the data in accessible maps and timelines. Users can explore temperature changes at the street or district level, compare day-night variations, and simulate the effects of planned interventions. This not only enhances transparency but also bridges scientific insight and municipal decision-making processes.

Supported by the European MAtchUP programme and Germany’s mFUND initiative, KLIPS illustrates how data-driven tools can make urban adaptation tangible and actionable. By linking AI technology with local expertise and open data principles, the project sets a strong 

This event is part of the ISCN Global Mixer, a series of events organized by the International Smart Cities Network. The presentations cover a wide range of topics related to international smart city approaches and provide exciting insights into urban digitalization worldwide - in just 30 minutes.

BerlinTXL, the transformation of a former airport into a pioneering sustainble and digitally-driven urban quarter remains one of Germany's few and exciting "greenfield developments" in the Smart City space. With this session we want to update the International Smart Cities Network on the progress since the last time BerlinTXL visited the "ISCN Global Mixer" as a speaker and thus offer a close-up to the rythm of this major and inspiring project.

Key takeaways

• Transforming an airport into a city of tomorrow: Berlin TXL turns the former Tegel site into a model for sustainable and innovative urban development.
• Building the Urban Tech Republic and Schumacher Quartier: A new hub for research, startups, and housing brings together technology, community, and livability.
• Driving innovation through data and design: Digital twins, open-source platforms, and green, climate-adaptive planning shape the district’s smart infrastructure.
• Creating real-world impact through collaboration: Over 40 companies and international partners are already contributing to Berlin TXL’s transformation.

This Global Mixer offered an inspiring look at the ongoing transformation of the former Berlin Tegel Airport into Berlin TXL – the city of tomorrow in the making. Building on a first part of the presentation from March 2024, Stefan Höffken showcases how one of Berlin’s most iconic sites is evolving into a multifunctional urban district where innovation, sustainability, and livability come together. 

The area will be home to the Urban Tech Republic – a hub for research, startups, and industry focused on future urban technologies – and the Schumacher Quartier, a residential neighborhood with over 6,000 housing units and space for more than 10,000 residents. The project is ambitious in scope, with a planning horizon of two decades.

The focus areas: 

• Promoting innovation in mobility, energy, water, and construction
• Creating a digital infrastructure with open-source platforms and digital twins to manage water, land, and buildings
• Building a data marketplace to enable secure sharing of urban data
• Integrating green spaces and climate-adaptive design

Over 40 startups and companies are already active on site, supported by international partnerships (e.g. with Mitsubishi and Incheon Startup Park).

The project serves as a model for future cities, combining sustainability, digitalization, and innovation in a real-world setting.

This event is part of the ISCN Global Mixer, a series of events organized by the International Smart Cities Network. The presentations cover a wide range of topics related to international smart city approaches and provide exciting insights into urban digitalization worldwide - in just 30 minutes.

Year of publication: 2025

In this episode of the ISCN Global Mixer, Thomas Terstiege from the City of Münster presented Leezenflow, an innovative green phase assistant designed to enhance the cycling experience in Münster. The tool helps cyclists navigate city streets more smoothly by allowing them to anticipate traffic light changes, making their journeys more efficient and enjoyable.

"Leezenflow" is a green wave assistant for cyclists, implemented by the German Model Project Smart City Münster. The solution utilizes strategically placed LED displays, positioned 100 to 200 meters before traffic lights, to indicate whether the upcoming light will be green upon arrival. The system operates at key points along several cycling routes. 

The primary goal of Leezenflow is to make cycling in Münster even more appealing, contributing to a better urban quality of life with fewer red light offences, reduced noise, and improved air quality along the equipped routes. By promoting cycling as a sustainable mode of transport, Leezenflow plays a vital role in the mobility transition and fosters sustainable urban development. 

In his Global Mixer presentation, Thomas Terstiege from the City of Münster explained how the devices works. By calculating the average speed of cyclists, the distance to the traffic lights, and the duration of the green phase, Leezenflow enables real-time communication between traffic lights and the displays, significantly improving cyclist comfort and safety. 

In addition, the talk covered the development of the solution, from its starting point in 2019, when students developed the first prototype during a hackathon, through further development by the city, to the installation of nine devices in the summer of 2024. 

As with all solutions funded by the German Model Project Smart City (MPSC) programme, Leezenflow’s source code is open for anyone to use, test and further develop. Mr. Terstiege strongly advocated the open source approach, as it is necessary, especially in times of climate crisis, to share and disseminate knowledge for solutions that support sustainable urban development projects. The project has already been replicated in other German cities. 

Leezenflow is an open-source solution that can be implemented independently with the necessary hardware, without proprietary restrictions. All project data is accessible in a GitHub repository. 

Year of publication: 2024

In this episode of the ISCN Global Mixer, Serena Mombelli and Patricio Reyes from vCity, a platform led by the Data Analytics and Visualization Group at the Barcelona Supercomputing Center, shared insights on how data-driven analysis can support human-centred urban planning and policy-making. In this session they present a use case approximating in greater detail whether high-risk groups have adequate access to Barcelona's climate shelters during heatwaves.

Currently, vCity is looking for new cities to collaborate! 

If you are interested to implement a study or a use case in your municipality, feel free to reach out to vCity:

 hello@vcity-tech
www.vcity.tech

vCity works in the following areas:

• Proximity: Accessibility of facilities, for example Climate Shelters Barcelona study
• Air Quality: Democratizing the access to models for air quality forecasting (models are trained with the capabilities of the BSC, but can be used without supercomputers by cities)
• Cycling: Efficient planning and implementation of networks of bike lanes
• Mobility: Creating a multi modal model
• Sustainability: Developing indicatiors to measure the preparedness of cities for circular economy and green transition. 

The costs are covered by the current public funding of the vCity projects. Interested cities thus only need to share access to data sources and local knowledge for their use cases or studies, for example through urban planners, policy-makers or project managers, to benefit from a great cooperation and leverage expert knowledge and supercomputing resources!

Agreements can be formalized through a Memorandum of Understanding (MoU), if needed, with 2-3 months preparation time.

In this episode of the ISCN Global Mixer, Serena Mombelli and Patricio Reyes, researchers at the Barcelona Supercomputing Centre (BSC) presented the project vCity, which provides Cities a human centric platform for urban data twins. 

The platform offers solutions for cities in different areas, and demonstrates the capabilities of digitalisation in cities. The projects so far works in the areas of proximity, air quality, cycling, mobility and sustainability.

The presentation focused on the analysis of Climate Shelter Accessibility in Barcelona, a result of a collaboration between Barcelona City Council and vCity. The study is one of the use cases in the Urban Lab for Proximity. 

Cities globally are increasingly affected by heatwaves, and many municipalities are seeking solutions to protect vulnerable groups. Barcelona has over 360 climate shelters in public spaces such as schools, libraries, and parks, providing protection during high temperatures

But do high-risk groups have adequate access to shelters during heat-waves? Serena Mombelli answered this question and gave many more valuable insights into the approach and methodology of the study in her presentation.  

For more information and an interactive map,  visit the project’s website. 

For any further questions, project ideas or matching requirements, feel also free to reach out to us, the International Smart Cities Network (ISCN), via iscn@giz.de 

Year of publication: 2024

Urban mining is a circular economy approach that aims for systematically reusing waste as a resource, instead of disposing it. In this ISCN Global Mixer, Tanya Tsui from the MIT Senseable Amsterdam Lab illustrates how AI can be used to close material cycles in cities and invites discussion which potential applications the approach offers.

Key takeaways

• From circular to linear: Urban Mining can shift cities’ role from sole consumers of the world’s extracted materials to providers of it as well.
• From nominal to real values: Tanya Tsui’s research approach aspires to train algorithmic models in order to more closely estimate real values of the prevalence of materials in buildings over their lifetime, rather than nominal values emerging at demolition.
• Who wants to compete with the Netherlands? While data availability in the Netherlands for building materials is already quite strong and in high spatial resolution, the presented research project would be interested to know and source from other regions as well and thus widen the scope.

Global materials demand is estimated to more than double from 79 billion tons to 167 billion tons till 2060 (OECD, 2019) and global urbanization is a main driver. At the same time, the immense negative environmental and socioeconomic consequences of virgin mining and material extraction render a shift to approaches of circular economy more and more urgent. Cities can thereby assume not only the role of absorbers of material demand, but also as providers of it – some of the biggest mines in the world are arguably big metropolises!

Against this background, Tanya Tsui, Postdoc researcher at the MIT Senseable City Lab in Amsterdam presented her project on facilitating urban mining with Big Data and AI models.

She set the scene with referencing three examples of AI-supported urban data science: 

• With “Treepedia”, streetview images are algorithmically analysed to estimate green coverage in streets and urban quarters.
• “Skyview” uses streetview images facing the sky from among buildings, to estimate radiation on areas and thus provide proxies for urban heat islands.
• In order to assess the prevalence of secondary building materials, the approach has been so far to work with “archetypes” of buildings to be found in the city. Their extrapolation on the whole building stock returns an estimate of volumes to be expected. 

However, so far these values are nominal and not yet "real". And it estimates largely waste from demolition of buildings but is not granular enough to catch material flows from renovations and the entire lifecycle of buildings. 
For this next step, Tanya tries to link building data and (disaggregated) waste data that exist in cities, always with the necessity of three core data points: material type, amount and location. 

In the Netherlands, building data are organized and provided in already relatively good spatial resolution through the Pdok data base and Register of Buildings and Addresses (BAG). Waste data on the other hand is more difficult to constitute and access. Its tracking usually begins only beyond certain thresholds and often doesn’t entail exact typological and locational breakdowns. In her quest for suitable sources and stakeholders she is thinking about demolition contractors, building material exchange platforms, building or environmental permits but is very open for other suggestions as well.

In the lively discussion after her keynote, Tanya reflected on several questions. One was why she prioritizes building material for urban mining rather than e.g. household wares (refrigerators, washing machines, etc.). To her, this focus is warranted by the sheer scale of the building sector and its climate impact, but also because data is much more accessible for it. Asked about her challenges on an operational level when contacting stakeholders, she stressed that getting relevant and accurate data remains hard to get by. But in order to motivate data provision she also underlined that insights could be properly translated into better allocation and matching of material needs. Especially if the real-time analysis reached down to component levels, quicker and precise market clearance would be a big step towards a circular economy. 

She thus subsumed her input with a call for action to the audience as she is particularly interested in additional data sources for urban building and waste data from Germany and beyond. 

If a cooperation might be of interest to you, you can reach out directly to her or via the International Smart Cities Network at iscn@giz.de 

Further links:

https://senseable.mit.edu/

Year of publication: 2024

The transformation and redevelopment of the former Berlin Tegel airport into the "Urban Tech Republic" and other districts is perhaps the closest one can get to a smart greenfield development in Germany.
In this ISCN Global Mixer, Stefan Höffken, the head of the project, gives an overview on their exciting plans and shares experiences on specific use cases they are developing.

Public money, public code: Berlin TXL is developing many interesting software solutions and provides the code in open license for replication.

The right blend: There is much software development and hardware use, but a crucial complementary to that are the "Entwicklungspartnerschaften" [development partnerships] managed through a moderated stakeholder process and carrying approaches to their full use.

AI enhancing use cases: For several use cases at Berlin TXL, artificial intelligence is a key enabler or crucial additional feature. Monitoring with drones, for example, can be done comprehensively and yet remain compliant with privacy concerns.

Be water, my friend: Water has many more utilities than we usually think of. It is not only part of sanitation and nutrition, but also a key factor and medium for cooling, energy management or damage control. This warrants particular emphasis on water management for smart developments.

The iconic hexagonal terminals of the former Berlin Tegel airport are testimony to past innovation, futuristic ambition and smart spatial planning. Now they are standing a bit isolated in an almost empty area of about 500ha. But not for long, as they witness with Berlin TXL a new big transformational smart district development comprising the “Urban Tech Republic” and the Schumacher Quartier and Cité Pasteur as new modern residential estates.

Stefan Höffken, urban planner with digital focus and head of the project, gave us a short overview on Berlin TXL’s overall plans and shared some experiences on the specific use cases they are developing in the project.

Their approach for smart district development has been to initially set up core digital infrastructures, such as a Data Platform or a 3D modelling of the area. To this are linked and further developed several use cases employing both newly developed software and hardware applications, e.g. LoRaWan sensors or drones. All is bound together by so-called “Entwicklungspartnerschaften” [development partnerships] with various actors and organizations from Berlin and steered through moderated stakeholder processes. 

An illustration thereof is the “Smart nature” monitoring of vegetation and identification of plant species in the area. Through drone flights a comprehensive recording of the area is done regularly and AI enables a detailed modelling of heat structures and growth patterns which then informs action for biodiversity preservation and management of the aerial climate. All this is done in cooperation with Grünberlin, a state-owned company focusing on green infrastructure.

Other use cases Stefan mentioned were a software that automatically blurs and anonymizes through AI sensitive objects in aerial images taken by drones, a more detailed and integrated heat and energy metering, and prediction-based water management. Watch the above recording of the session for more information.

Stefan Höffken also highlighted that their project welcomes further cooperation and exchanges, also with international actors. If you want to reach out to the project, feel free to do so also via the International Smart Cities Network at iscn@giz.de.

• More information on Berlin TXL can be found here: https://urbantechrepublic.de/en/
• A documentation and code of the solution for privacy-compliant blurring of aerial images can be found here on Open CoDE: https://software.opencode.de/project/1197#readme [German]
• The Gitlab online repository including the employed data platform can be found here: https://gitlab.com/berlintxl/futr-hub/