The AGILE Parklet joined the diverse array of parklets on Park(ing) Day 2015 as they popped up in parking spaces all across the country. While it was set up in the heart of Downtown Nashville adjacent to a local restaurant and coffeehouse, sensors embedded in the parklet’s chairs successfully gathered over six hours of data about the parklet’s use. This automated data collection effort was a continuation of the experimentation The AGILE Landscape Project has been conducting since publishing The Future of Public Space Analytics earlier this year. The post made the case why automated data collection through embedded sensors could provide unique and valuable insight into the use of public space. The AGILE Parklet has been deployed during events and self initiated pop-ups to demonstrate the real world application and potential of this approach. This initial proof-of-concept has focused on collecting information about the number of people sitting in the parklet, the utilization of its capacity, and the length of stay of individual visitors. These metrics and the ability to efficiently capture them over extended periods of time have shown great promise for developing public space analytics that enable designers and managers to make more informed decisions rather than anecdotal observations and/or assumptions. What follows is an examination of the data collected during Park(ing) Day and and exploration of its application.
Why focus on the seating? Seating is a key component of successful public spaces and the act of sitting represents a relevant and measurable means of quantifying users engagement with a space. In addition, this action can be accurately, and anonymously captured to create long-term longitudinal datasets. By capturing the total number of people sitting in chairs and how long they stay, one can quickly surmise a level of engagement, the capacity of the seating utilized, and turnover of users within the space. This information offers meaningful metrics that provide new insights into the dynamics of a space’s use. A device embedded in each of the AGILE Parklet’s chairs enables them to easily capture this data and transmit it wirelessly to an on-line database for analysis. The captured data is simultaneously plotted in real-time on a companion website.
The current analysis of the collected data and the development of tools to facilitate the application of it has centered around the following three metrics; Total Visits, Utilized Capacity, and Median Length of Stay.
Capturing the total number of people occupying seating throughout the day gives a quick overview of the space’s daily use patterns. It serves as an initial level of understanding of the effectiveness of the space and answers the basic question if a space is even being used and if so to what extent. Managers of the space can immediately comprehend which areas may need further level of study and/or when and if they need to add additional programming or initiate potential design changes.
Like a website’s daily traffic statistics, plotting the daily use pattern over an extended time period will indicate the space’s use trends over the days of the week, months, years, and seasons. This ebb and flow can offer decision makers early indicators of growth or decline in use, thereby providing the opportunity to react.
A closer look at the daily data collection points and slope of the pedestrian counts can offer additional insight. Steep trajectories in use through the day illustrates burst of activity where groups are sitting down at once over short period of time. The length of this upsurge in the plot can signal time when there is higher turnover within the space. Overlaying this data with various programming strategies such as time of events or addition of vendors can help evaluate their level effectiveness for attracting people to the space. Additionally, decisionmakers can observe how moving the location of seating can alter the shape of the trajectory and counts can help calibrate the best placement of furniture.
Utilization of capacity depicts peak demand throughout the day and pinpoints times where there is excess capacity that could be utilized. Managers can use this data to experiment with various programming changes to exploit these periods and increase the demand when use is low. This ability to specifically target times can facilitate the efficient use of limited resources. Conversely, times of peak demand where full capacity is utilized during prime hours (i.e. lunch, dinner) signals the need for additional seating options within the space and/or new spaces within a district or neighborhood. This metric can arm public space advocates with concrete data that demonstrate the need for new spaces and/or intervention within existing spaces.
MEDIAN LENGTH OF STAY
The median length of stay is a factor that is of particular interest because it signifies a level of connection with the space. The more someone is enjoying the space the longer they will stay and the more likely they are engaging or will engage with other users. This “stickiness of space” borrows heavily from the website analytics industry stickiness metrics where the length of stay on a website and its pages are measured as means of evaluating a users interest and the site’s effectiveness for maintaining the visitors attention.
By recording the length of stay and calculating its median time for the the day, managers can understand how effectively a space retains visitors and the impacts programming and design efforts have on retention. In addition, either short or extremely long median times can raise questions about the health of the space such as “Do users feel safe?” or “Are there homeless individuals that may need social services?”. Furthermore, the median length of stay can be compared to the number of users sitting to see how capacity can affect the length of stay.
JUST THE BEGINNING
These metrics and their visualization hold considerable promise as helpful tools for achieving more clarity to the dynamics and use of public spaces. The ability to efficiently scale up the data collection offers the opportunity to cost-effectively study a number of sites over long periods of time. New insights and discovery will emerge as larger and longer data sets from a wide array of locations are amassed. These new building blocks can also be combined with contextual, environmental, and qualitative data sets to create an even richer picture and deeper insights. It will be interesting to see where this information leads and how it is used. As we strive to make it easy for anyone to collect and visualize this information on a larger scale, The AGILE Landscape Project will continue to refine these metrics and methodologies as well as add new meaningful ones. It is just the beginning of a boundless future for public space analytics.