We've long talked about integrating our labeling efforts with satellite imagery. Put simply, there are cases where labeling features in streetscape imagery is advantageous and there are also cases where labeling top-down imagery is better. We have a related discussion about this here: https://github.com/ProjectSidewalk/SidewalkWebpage/issues/1129 — which talks about using sat imagery for labeling missing sidewalks and mapping sidewalk locations.
Recently, Chicago folks have asked us to think about ways to mark bike lanes in Project Sidewalk. This provoked a renewed discussion about the best way to do this with our toolset.
So, @misaugstad and I started mocking up examples of what this might be like with sat imagery. This could either be a mission inside Project Sidewalk or a standalone tool itself. Here's a random intersection in DC that I just loaded and you can clearly see: crosswalks, curb ramps, and a marked bike lane. This is from their open 3" resolution sat dataset: https://opendata.dc.gov/datasets/2cb9fe0f4b444ebbae359b8889f39dda/explore?location=38.901360%2C-76.988242%2C20.31
For example, you could use shape tools to label things like:
Or @misaugstad suggested doing polylines instead with large stroke width.
In addition, @misaugstad suggested that labeling curb ramps with arrows might be sufficient to show direction of travel (and their location):
We've long talked about integrating our labeling efforts with satellite imagery. Put simply, there are cases where labeling features in streetscape imagery is advantageous and there are also cases where labeling top-down imagery is better. We have a related discussion about this here: https://github.com/ProjectSidewalk/SidewalkWebpage/issues/1129 — which talks about using sat imagery for labeling missing sidewalks and mapping sidewalk locations.
Recently, Chicago folks have asked us to think about ways to mark bike lanes in Project Sidewalk. This provoked a renewed discussion about the best way to do this with our toolset.
So, @misaugstad and I started mocking up examples of what this might be like with sat imagery. This could either be a mission inside Project Sidewalk or a standalone tool itself. Here's a random intersection in DC that I just loaded and you can clearly see: crosswalks, curb ramps, and a marked bike lane. This is from their open 3" resolution sat dataset: https://opendata.dc.gov/datasets/2cb9fe0f4b444ebbae359b8889f39dda/explore?location=38.901360%2C-76.988242%2C20.31
For example, you could use shape tools to label things like:
Or @misaugstad suggested doing polylines instead with large stroke width.
In addition, @misaugstad suggested that labeling curb ramps with arrows might be sufficient to show direction of travel (and their location):