Data and data collection for pedestrian planning

Data is essential for effective urban planning and management. This chapter provides a comprehensive overview of data and data collection techniques for pedestrian planning, aiming to provide researchers and practitioners insights into selecting suitable data and data collection techniques based on their specific pedestrian planning needs. This chapter begins by outlining the taxonomy of data for pedestrian planning, identifying the types of pedestrian behaviour, data types, and data features that are important for pedestrian planning considerations. It specifically identifies four types of data that are essential for pedestrian planning, namely environmental and infrastructure data, traffic data, personal characteristics, and physiological data. This chapter provides a comprehensive overview of each type of data used in pedestrian planning and where these data can be sourced. Moreover, this chapter provides an in-depth overview of different data collection techniques used in pedestrian planning, including sensors, crowd sourcing, and eXtended Reality. The advantages and limitations of each technique are also discussed, offering practical insights for employing them for data collection purposes. In summary, this chapter serves as a comprehensive guide to understanding the why, what, where, and how of using data to enhance pedestrian planning. It offers the readers the knowledge to collect and use data effectively, which ultimately supports the designing, planning, and management of pedestrian-friendly urban environments.