

MIND THE HEAT
MIND THE HEAT
How can the municipality prioritize locations
to address heat stress in managing public space?
Heat in Cities
Beyond its potential health consequences, heat stress negatively affects economic productivity, environmental quality, and social networks.
Heat stress as a challenge
Global warming is intensifying the frequency and severity of heatwaves. Additionally, the urban heat island (UHI) effect also intensifies, which is driven by configuration of city, impermeable materials, and human activities.
These conditions, along with high population density and median age are heightening the urgency and impact of heat stress in cities.
However, its implementation requires the Municipality to take action effectively through clear policies and good communication. The separatation of city departments and the lack of connection between research and practical actions make this difficult.
Shading
both natural and artificial—
is a feasible and efficient spatial intervention.

The Challenge of Heat
Knowledge and Policy Gaps
in Addressing Urban Heat Stress
There is growing knowledge about the causes, consequences, and solutions for urban heat stress. In response, there are emerging municipal heat plans in the Netherlands, such as the Amsterdam Hitteplan (GGD Amsterdam, 2024) and the Utrecht Heat Plan (Gemeente Utrecht, 2022), which aim to translate research into actionable design strategies.
However, there is still a gap between research and policymaking and challenge in interpreting raw data.
GAP 1
academic findings often fail to align with the immediate and practical needs of municipal policymakers
GAP 2
current models often fails to account for complex factors when interpreting raw climatic or demographic data, such as how often the road is used and the diverse vulnerabilities of urban populations.
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The complexity of these interrelated issues makes urban heat stress a “wicked problem,” where there is no single solution, which makes it difficult for the municipal to prioritize areas and act.
Mind the GAP!


The Hot Spot

Amsterdam as a case study
After experiencing record-breaking temperatures of 40°C in 2019, Amsterdam became more aware of heat-related health risks and introduced policies and strategies to address heat stress.
However, the city still struggles to translate these policies into data-driven decisions due to a lack of reliable heat stress data, neighborhood-level demographics, and building-specific health insights.
This lack restricts the municipality’s ability to identify high-priority areas for interventions and allocate resources effectively.
Therefore, Amsterdam is an ideal city to implement the research.
Our research takes an interdisciplinary approach, focusing on developing a decision support tool for prioritizing location for heat stress intervention, which utilizes data-driven and knowledge driven decision.
Co-Creation to inform the case study
To understand the needs of Amsterdam in more depth and to collect feedback on the final dashboard two co-creation sessions where conducted.
1st Co-creation: Understand the problem in the context of Amsterdam
2nd Co-creation: Collect feedback from potential end-users on usability
Modeling the Heat
Our approach
Through conversations, interviews, and co-creation sessions with municipal employees, a decision support tool was conceptualized to address the complexities of urban heat stress in Amsterdam. Holistically analyzing heat stress through the 5 Ps—Planet, People, Prosperity, Partnership, and Peace—helps highlight which cirteria should be prioritized.
Building on these insights, the decision support tool combines data on heat, shade, and urban flows:
The Heat Criterion
Physiologically Equivalent Temperature (PET) is the primary dataset for assessing heat, although its reliability is debated, it is more reliable than other sources such as warm nights and urban heat island effect. This criterion joins the PET temperatures to the sidewalk polygons with exact extract to represent the average felt temperature for street segments in the road network.
This approach provides a useful baseline but requires shade data to more accurately model pedestrian heat exposure.


The Shade Criterion
It is important to account for temporal variations in heat intensity throughout the day. A weighted curve, based on the sun’s position and air temperature, was developed to represent peak heat stress periods in Amsterdam. The co-creation sessions emphasized that roads with over 40% shade coverage during the day are considered low-priority for heat interventions. Building on these, the model uses sidewalk polygons and exact extract to join shade raster data with street segments in the road network, calculating the percentage of shade coverage over time.



Pedestrian intensity is modeled by simulating essential trips, where individuals are assumed to prioritize the shortest routes with minimal turns. To reflect this, the model applies a turn penalty of 30 meters for each change in direction. Essential service clusters, including grocery stores and pharmacies—key destinations even on hot days—serve as the focal points of these trips.
Pedestrians are prioritized in this model because they are more affected by heat stress compared to cyclists, who experience shorter exposure times. Additionally, the model focuses on residential flows, tracing routes from home buildings to the nearest service clusters. Detailed vulnerability building-level data is not available, so specific vulnerabilities are not modeled.


The Pedestrian Intensity
The Heat Map
By integrating the three dimensions mentioned above, the heat stress risk at the street level can be calculated, thereby helping to identify the areas requiring the highest priority for intervention. This data output is also presented through a tangible decision support tool.
In this process, direct feedback from end-users was gathered through interviews and co-creation sessions. The collaborative efforts also highlighted key needs, including a simple, user-friendly interface, the integration of vulnerable groups, scalability through standardized outputs, and dual-level functionality catering to both broad climate advisories and detailed project planning.
The tool is currently limited to Amsterdam, but by including an extensive “read me” manual, it can be adapted to other Dutch municipalities.



Meet the Team
This research, a collaboration between the MIT Senseable City Lab and the Municipality of Amsterdam, is part of the living lab project “Mind the Heat,” and it involves six MSc MADE students addressing urban heat challenges in Amsterdam.

Carlotta Marie Henning

Max Olzheim

Julian Fitzpatrick

Romane Sanchez

Layne Perry

Yifan Yang

Special thanks to:
Lukas Beuster,
Jelte Hermans,
Maryam Ghodsvali,
Jessica Wreyford,
and Umbra!
If you want to learn more about my journey, click here!

Umbra





