The team at eBird recently released a new mapping portal. The user interface is so, so, so much better, I cannot underestimate this point. It’s slick, well-done, clean, easy to use, modern, and many, many steps above the previous method for mapping eBird data. I love the fact that it’s in a multi-scale, interactive form and that it will zoom to the species extent. The mercator gridding is nice too. The team did a fantastic job with this upgrade.
My issue, of course, has to do with the actual representation of data on the map. Since their new mapping portal uses a REST service to serve pre-generated tiles of gridded data, it was easy to scrape an example tile, pin it to my own Google Maps and tinker with the colors a little (using Adobe Photoshop), to see if I could make something, that was in my opinion, a little bit more readable.
Personally, I have a hard time extracting pattern from the new representation. For starters, I think the purple is okay, but what was wrong with the previously used green? I think it was a good color. In the new version, the “no reports” grey has been darkened and the feature color scheme has been compressed, with a darker low sighting frequency (or pale) color and a lighter high sighting frequency (or dark) color. This gives the impression of a divergent color scheme, with the brightest, saturated purple in the middle being most salient. For me, the palest shade of purple gets lost and confused among the dark grey squares of “no reports.” I can turn off the grey “no reports” grid, but then it’s a little harder to understand where there were no birds and where there were no observations.
What this problem highlights is the use of color gradients for mapping on computer screens. Darker, heavily saturated colors close to black are actually harder to notice because of the nature of additive color on digital screens, whereby as color is added, the result is lighter and tends toward white. So, pale, whitish tints actually can be more visibly salient than dark, saturated, blackish colors. I think this phenomenon helps explain the popularity of heatmap color schemes, where the highest values are the brightest white. Visually, though, a saturated bright red, or green, will stand out. Subdued darkish purple, to me, not as much.
Follows are screenshots of the original (top) with an example I’ve tinkered with (bottom), just one tile, for American Goldfinch in the northwest. Same, exact data.
By using the paler white for “no reports” the image becomes less heavy and allows the observations to stand out more. “No reports” data is slightly less important, so it can be less immediately salient. For the color scheme, the palest color is still very noticeable, but since it’s closer to white (and less color saturated) it fades to the back a little and lets the ramp up to a bright, saturated green show more strongly than the compressed purple scheme.
I’ve also reduced the overall transparency, to allow the figure (the data) and the ground (the map) separate a little bit, which was another problem for the purple original. Ideally, a transparency slider would let the user adjust these transparency levels (for everything, including the map background). Often, thematic maps really need a simple, plain basemap (like ESRI’s new plain gray or rolling your own with TileMill). I understand the use of Google Maps here, because once you zoom in enough, you get individual observation points and want to see, in geographic context, where they are on the map.
So, do you think my tinkering was an improvement? Does it work? What would make reading the patterns in the data easiest?