<< Activity Density Infoscape >>
Created By: Scott Pobiner (spobiner at gsd dot harvard dot edu) & Tripti Gore Chandorkar (tripti at mit dot edu)
This is a project done as part of the “Urban Infoscapes” class during the Spring 2004 semester. The project sought to map the density of activity within a given public space in order to learn about the potential unseen ways that space and organization affect peoples’ physical activity. Above is a resulting animated GIF produced from an analysis of the footage on the right. The darker (more purple) areas indicate portions of the camera’s view that were consistently occupied for a longer amount of time. The lighter (more yellow or white) the shading is, the less time the space was occupied. This method of spatial analysis is particularly interesting for a variety of purposes. For example, facilities management researchers might use it to get a more clear idea of post-occupancy use of a space. Another example is the potential for public space designers to use the information to redesign pedestrian traffic models that can provide more quality space for people to sit, away from high-traffic areas. Finally, activity density maps may be used to provide researchers with spatial use information that hasnÕt been previously understood as suggested by the “hidden dimension” research of Hall & Hall (Hall 1990) and in the tradition of the action research of William Whyte and his significant findings in understanding human organizational activity. In order to produce this map, the initial footage was exported as a series of frames using a digital movie capture program (such as Premiere form Adobe or iMovie form Apple). Then, each frame was stripped of its background, leaving only the occupants (with a white background) and the images of occupants were filled to make silhouettes. To do this we had to manually crop each frame, although future iterations could be developed to do this automatically. To process the resultant frames, a density over time algorithm was produced and was used in an image processing and analysis application called imageJ ( http://rsb.info.nih.gov/ij/ ). The algorithm functioned as follows : Step 1: IMGn/2 + IMG(n+1)/2 = R(n-1) Step n: R(n-1)*n/(n+1) + IMG(n+1)/(n+1) = Rn The first step provides an initial result, which each additional frame is added to. Because each pixel of every frame will have certain darkness values with reference to the total number of frames analyzed, it is relatively easy to see how density changed over time. Each time a result is produced, the color lookup table is changed to give the images the purple and yellow colors, making it easier to determine what density levels were like. The colors are analogous to those one might see in a thermo-graphic map (in this case density replaces heat). The result is a series of frames that are compiled in order to create the final activity flow movie. To push this methodology onward applications might be produced that visualize the density of activity for spaces in different ways, which might provide graphs and numerical analysis of the resultant images. Of course, the image is the easiest to understand visually making this project an interesting addition as an installation in any public space as well. Most importantly, this project is an example of how digital media might be used to evaluate and understand spatial activity without an intrusive amount of equipment or exorbitant expense. It is also an example of how the design profession might develop tools to examine the use of physical space using new digital tools. References Hall, Edward Twitchell. The hidden dimension. New York : Anchor Books, Doubleday, 1990. Whyte, William Foote. Organizational behavior: theory and application. Homewood, Ill., R. D. Irwin, 1969. William Foote Whyte, editor. Participatory action research. Newbury Park, Calif. : Sage Publications, c1991.