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A Carrying Capacity Calculator for Pedestrians Using OpenStreetMap Data: Application to Urban Tourism and Public Spaces

Duarte Sampaio de Almeida, Rodrigo Simões, Fernando Brito e Abreu, Adriano Lopes, Inês Boavida-Portugal

TL;DR

The paper tackles the challenge of quantifying pedestrian carrying capacity in urban spaces to support sustainable tourism and public-space management. It introduces an online calculator that leverages OpenStreetMap data, the Turf.js geospatial toolkit, and Web Workers to compute walkable area and three carrying-capacity levels: $PCC$, $RCC$, and $ECC$, using parameters such as area per pedestrian, rotation factor, corrective factors, and management capacity. Key contributions include a detailed algorithm to derive the available area, a practical web-based implementation (extending geojson.io), and a case study in Lisbon's Santa Maria Maior to demonstrate applicability for urban planning, event management, and crowd safety. The tool enables data-driven decision-making for crowd management and sustainable infrastructure, with broad potential use across tourism destinations, public spaces, and city-wide events, and is available online for public use.

Abstract

Determining the carrying capacity of urban tourism destinations and public spaces is essential for sustainable management. This paper presents an online tool that calculates pedestrian carrying capacities for user-defined areas based on OpenStreetMap (OSM) data. The tool considers physical, real, and effective carrying capacities by incorporating parameters such as area per pedestrian, rotation factor, corrective factors, and management capacity. The carrying capacity calculator aids in balancing environmental, economic, social, and experiential factors to prevent overcrowding and preserve the quality of life for residents and visitors. This tool is particularly useful for tourism destination management, urban planning, and event management, ensuring positive visitor experiences and sustainable infrastructure development. We detail the implementation of the calculator, its underlying algorithm, and its application to the Santa Maria Maior parish in Lisbon, highlighting its effectiveness in managing urban tourism and public spaces.

A Carrying Capacity Calculator for Pedestrians Using OpenStreetMap Data: Application to Urban Tourism and Public Spaces

TL;DR

The paper tackles the challenge of quantifying pedestrian carrying capacity in urban spaces to support sustainable tourism and public-space management. It introduces an online calculator that leverages OpenStreetMap data, the Turf.js geospatial toolkit, and Web Workers to compute walkable area and three carrying-capacity levels: , , and , using parameters such as area per pedestrian, rotation factor, corrective factors, and management capacity. Key contributions include a detailed algorithm to derive the available area, a practical web-based implementation (extending geojson.io), and a case study in Lisbon's Santa Maria Maior to demonstrate applicability for urban planning, event management, and crowd safety. The tool enables data-driven decision-making for crowd management and sustainable infrastructure, with broad potential use across tourism destinations, public spaces, and city-wide events, and is available online for public use.

Abstract

Determining the carrying capacity of urban tourism destinations and public spaces is essential for sustainable management. This paper presents an online tool that calculates pedestrian carrying capacities for user-defined areas based on OpenStreetMap (OSM) data. The tool considers physical, real, and effective carrying capacities by incorporating parameters such as area per pedestrian, rotation factor, corrective factors, and management capacity. The carrying capacity calculator aids in balancing environmental, economic, social, and experiential factors to prevent overcrowding and preserve the quality of life for residents and visitors. This tool is particularly useful for tourism destination management, urban planning, and event management, ensuring positive visitor experiences and sustainable infrastructure development. We detail the implementation of the calculator, its underlying algorithm, and its application to the Santa Maria Maior parish in Lisbon, highlighting its effectiveness in managing urban tourism and public spaces.
Paper Structure (15 sections, 4 equations, 8 figures)

This paper contains 15 sections, 4 equations, 8 figures.

Table of Contents

  1. Introduction
  2. Background
  3. The OpenStreetMap initiative
  4. Carrying capacity
  5. Tourism proxemics
  6. Requirements specification
  7. Functional user stories
  8. Non-functional user stories
  9. Algorithm for the available area for tourism activity
  10. The carrying capacity calculator tool
  11. Area per Pedestrian
  12. Rotation Factor
  13. Corrective Factors
  14. Management Capacity
  15. Conclusion

Figures (8)

  • Figure 1: An page with its tag-value mapping
  • Figure 2: Influence of urban fabric on carrying capacity (two examples from Lisbon, Portugal)
  • Figure 3: All Lisbon parishes: the GeoJSON code provided by the https://lisboaaberta.cm-lisboa.pt/index.php/pt/informacao-de-base-e-cartografia initiative was pasted in the right panel
  • Figure 4: User-selected areas in Santa Maria Maior parish, using the shape tools on the vertical toolbar
  • Figure 5: Available options before triggering calculation
  • ...and 3 more figures