Cartography, a critical instrument in participatory urban planning

Participatory Urban Planning and Cartography

Maps have always been a fundamental tool for urban planners to understand and shape urban environments. Initially, they served practical purposes, helping to lay out cities and guide their development. Over time, they evolved into tools for statistical analysis and communication of urban realities. However, it wasn’t until the 1950s that urban planning underwent significant transformations, with cartography taking on an increasingly pivotal role. The rise of PUP marked a shift toward including community voices in the decision-making process.

In this context, maps became essential for fostering dialogue and integrating citizen knowledge— both qualitative and experiential — into spatial formats. Cartography allowed for the mapping, analysis, and visualization of diverse perspectives on the same issues, helping to bridge the gap between experts (such as researchers) and participants (such as community members). This shift made urban planning, and cartography, more inclusive, embracing the lived experiences of communities in shaping their cities.

The map “Malleshwaram Memoirs” vividly exemplifies the use of citizen knowledge data to capture the intricate nuances of urban life, shedding light on emotional landscapes, temporal rhythms, and social dynamics within the cityscape. The map visualizes the rhythmicity of the city by representing human perceptions and experiences of its urban fabric. Each geographical location show their use: religious, cultural, etc. and the perceptions and experiences of individuals in these locations: emotional feeling of the place («calm and harmonious» or «stressed and restless»), sense of pace and temporality («intermittent» or «continuous» and «slow» or «fast»), and social rhythm («societal» or «cultural»).

This map is one of the biggest challenges of participatory mapping, which is translating the intangible and fleeting nature of personal experiences and perceptions into a tangible form.

Integrating Citizen Knowledge with Objective Data

In recent years, the concept of smart cities has further revolutionized urban planning, and therefore the cartographic practices. Cities now generate unprecedented volumes of data, enabling a wide range of spatial analyses and visualizations. This data is obtained from sensors, GPS receivers and smartphones among other sources, and encompasses various aspects of urban life — ranging from environmental factors, such as pollution levels and traffic conditions, to detailed population distribution at the building level. Such objective data, based on verifiable facts and figures, provides a detailed, data-driven understanding of urban spaces and their dynamics.

However, as the volume of data grows and technology develops, urban planners are recognizing that relying solely on objective data paints an incomplete picture of urban life. Representing multiple types of data can improve interpretations of the world and encourage diverse views of reality.

• Firstly, different data types can complement each other to fill information gaps and enrich insights.

• Secondly, multiple interpretations can coexist, even when they appear contradictory, each offering a valid perspective. These discrepancies can represent new areas for exploration.

When it comes to PUP and make visualizations that not only can reveal patterns and correlations, but also can provide deep insights from the experiences of real people living in specific conditions, the combination of objective data and citizen knowledge is essential. Relying solely on objective data or citizen knowledge in isolation may result in an incomplete understanding of the urban environment.

The schematic map illustrates the work of Samuel F. Dennis, “Prospects for Qualitative GIS at the Intersection of Youth Development and Participatory Urban Planning” (2006). He requested local youths to generate sketches depicting their perceptions of the qualitative aspects of the environment, including how problematic intersections affected their intended routes within the neighborhood. When this information was combined with official police data about the spatial distribution of crimes, it revealed a striking discrepancy: the actual locations where crimes were occurring did not correspond to the places where youth felt unsafe. This combination of objective data and citizen knowledge provided a more comprehensive and accurate analysis. Had these maps been created based solely on authoritative data, they would have missed crucial insights from the community.

Incorporating citizen knowledge into objective data ensures that the voices and experiences of residents and community members are considered. This inclusive approach leads to more equitable and people-centered decision-making processes, addressing the needs and concerns of the urban population.

For example, the Anti-Eviction Mapping maps the housing crisis in the San Francisco Bay Area, and documents the landscapes, lives, and sites of resistance and dispossession. The map goes beyond statistical data by incorporating real stories from people in audio and pop-up formats, offering a more profound understanding of the human experience of eviction. This combination of visual and narrative elements provides a more accurate and empathetic portrayal of the impact and implications of being evicted. It directly connects society and space, showing that a urban phenomenon, such as segregation, is not only a product of social structures but also of urban configurations.

This project is described in a chapter in the book This is not an atlas (free download) published by the Orangotango+ collective at Transcript, pages 38 to 45.

This combination of visual and narrative elements gives a more accurate and empathetic picture of the impact and implications of eviction. It establishes a direct link between society and space, showing that a urban phenomenon such as segregation is not only the product of social structures but also of urban configurations.

Insights from Lichtental district in Vienna, Austria

During my work on the Superblock project in Lichtental, I collected and analyzed citizen knowledge data, combining it with objective data to identify and fill informational gaps. This approach allowed for a deeper understanding of the urban environment and informed more inclusive planning decisions. Below, I present two key cases where this combination of data revealed important insights.

A clear and direct connection exists between green infrastructure and temperature in cities. Urban trees and green spaces contribute to lowering urban temperatures by shading and transpiration. Shading prevents direct shortwave radiation, reducing the surface temperature, and transpiration cools the air with evaporated water. When these layers are overlapped, a discernible pattern emerges: areas with green infrastructure correlate with a perception of cool temperatures, while the absence of trees or vegetation is associated with a perception of hotter temperatures.

Is it really necessary to conduct 200 interviews to reach this conclusion? Couldn’t it be effectively demonstrated through weather data, remote sensing, and similar tools? Initially, I would have answered yes, before realizing the following:

• Area 1: The climate analysis map categorizes this as a “moderate warming” zone. However, the perception map shows that residents consistently describe this area as “cold.”

• Area 2: This area is also classified as “moderate warming” on the climate analysis map, identical to Area 1. Surprisingly, on the perception map, residents overwhelmingly report this area as feeling “warm” or even “hot.”

If we look at the streetview of these locations, we might find that Area 1 is a tree-lined square with ample shade and no traffic, while Area 2 is a bustling commercial central area of the district with heat-absorbing concrete and limited greenery. This discrepancy between objective data and lived experience underscores the importance of integrating citizen knowledge with scientific measurements. While the climate analysis provides valuable information about overall urban heat patterns, the perception map reveals crucial insights about how people actually experience these environments in their daily lives.

Let’s see the second map:

Studying pedestrians’ movement frequency and activity patterns helps to understand how and where individuals move and which are the activity hotspots. This aids in optimizing infrastructure design, such as the placement of pedestrian crossings, public transportation stops, and amenities. When the pedestrians’ movement frequency and activity layers are overlapped, a discernible pattern emerges: high movement frequency aligns with areas featuring major transportation infrastructure and a dense concentration of activities.

Where else can we gather pedestrian data if not through participatory mapping? While technological methods such as sensors, cameras, and mobile data tracking provide detailed information on pedestrian movement, they have limitations. These tools can capture quantitative data—such as how many people pass through an area and at what times—but they miss the human dimension. They don’t tell us why people move the way they do, what challenges they face, or what motivates their choices.

More importantly, these methods often exclude vulnerable populations who don’t use digital tools, such as children, the elderly, or those without access to smartphones. These groups are often underrepresented in automated data collection, yet they are the ones most affected by urban design decisions. By relying solely on technology, we risk designing cities that cater primarily to the tech-savvy, neglecting the very people for whom urban spaces should be more accessible and welcoming.

This brings us to the core of cartography’s potential in PUP: it’s not just a tool for data collection, but a medium for human connection.

Participatory mapping allows planners and researchers to engage directly with communities, giving voice to those who may not participate in online surveys or public meetings. It provides a platform for listening to those who experience the city differently — the elderly who need safe crossings, the children who seek play areas, or those who rely on public transport but don’t use smartphones. Through participatory mapping, urban planners can collect not just data but stories, experiences and insights that enrich our understanding of how spaces are lived in and navigated.

Ultimately, this human connection is crucial for creating inclusive cities that reflect the needs and aspirations of all their inhabitants, not just the data points collected by machines.

↬ Camila Narbaitz Sarsur.

References

• Dennis, S. F.(2006). Prospects for Qualitative GIS at the Intersection of Youth Development and Participatory Urban Planning. Environment and Planning A: Economy and Space, 38(11), 2039–2054.

• Denwood, T. E. N.(2022). Pitfalls and Progress in Participatory Mapping, University of Manchester.

• Hemmersam, P., Martin, N., Westvang, E., Aspen, J., & Morrison, A. (2016). Exploring Urban Data Visualization and Public Participation in Planning. Journal of Urban Technology, 22, 1–20.

• International Fund for Agricultural Development. (2009). Good practices in participatory mapping.

• Godwin, A., & Stasko, J. T.(2017). Nodes, Paths, and Edges: Using Mental Maps to Augment Crime Data Analysis in Urban Spaces. EuroVis 2017 - Short Papers, 5 pages.

• Sayegh, A., Andreani, S., Kapelonis, C., Polozenko, N., & Stanojevic, S. (2016). Experiencing the built environment: Strategies to measure objective and subjective qualities of places. Open Geospatial Data, Software and Standards, 1(1), 11.