ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume VI-4/W2-2020
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., VI-4/W2-2020, 181–188, 2020
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., VI-4/W2-2020, 181–188, 2020

  15 Sep 2020

15 Sep 2020


N. Walravens1, B. Van de Vyvere2, M. Van Compernolle3, E. Vlassenroot3, and P. Colpaert2 N. Walravens et al.
  • 1imec–SMIT, Vrije Universiteit Brussel, Brussels, Belgium
  • 2imec–IDLab, Ghent University, Ghent, Belgium
  • 3imec–MICT, Ghent University, Ghent, Belgium

Keywords: Open Data, Semantic Sensor Network, Smart Cities, Urban Bustle

Abstract. One of the promises of the smart city concept is using real-time data to enhance policy making. In practice, such promises can turn out to be either very limited in what is actually possible or quickly trigger dystopian scenarios of tracking and monitoring. Today, many cities around the world already measure forms of urban bustle, i.e. how busy it is during specific periods of time. They do this for all kinds of purposes like optimising mobility flows, attracting tourism, monitoring safety during events or stimulating the local economy, and they employ divergent technologies: from analogue counting, over surveys, to more advanced near real-time tracking using mobile operator data. This fragmentation of approaches to measuring urban bustle creates some challenges for cities related to privacy, vendor lock-in, comparability of data, data quality and accuracy, historical and predictive analysis of data and so on. To tackle these challenges and formulate a standardised approach to measuring urban bustle, the thirteen largest cities in Flanders (Belgium), together with local technology vendors, co-created a “definition manual”; a document outlining indicators and relevant technologies for measuring urban bustle, as well as shared profile descriptions of residents and visitors of the city. This paper outlines the process and presents the results, an agreed-upon framework of standard profiles and indicators, which are useful to academics, public servants and technology companies involved in this topic.