More Difference From The Same uses visually similar aerial imagery to construct a sequence of transitional spaces, always between one place and the next.
This map is part of a series exploring the role of context in recognizing similarity. As the aerial imagery of one place is slowly replaced by the imagery of another, the two places are compared but also merge together. What do these places have in common? Are tennis courts always surrounded by a tree line? Would the transitional places function in a similar way?
Using Terrapattern — a machine learning model for finding visual similarity in aerial imagery — a dataset of similar places was compiled. The second place is similar to the first, the third place is similar to the second, and so on.
Technicals
To display each place as a random sequence of tiles, three canvas HTML elements were used: a hidden webGL canvas used Mapbox to render the aerial tiles and jump to a different location every 5 seconds; a hidden 2D canvas onto which the webGL canvas is drawn as an image every 6.75 seconds; and finally, a display 2D canvas onto which subdivisions of the hidden canvas are drawn every 0.75 seconds. WebGL aerial tiles were drawn to a separate hidden canvas to account for the incremental loading of the tiles. If the aerial tiles were copied immediately to the display canvas, they wouldn’t be fully rendered. Having the location change at a different interval than the copy rate ensures each tile is fully rendered.
Previous blog posts (Back and Forth 036 and A Different Similar Center 030) discuss the Terrapattern model in more detail.
Compare To
- Back and Forth (036), which replaced the center tile but also the surrounding context.
- A Different Similar Center (030), which replaced only the center image and maintained the original context.