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Mike Pelletier

2,122 post(s)
#27-Mar-20 17:59

Check out this timeline mapand interesting commentary on the art of mapping point data.

The COVID issue as really brought the issue to the forefront. I've been trying to replicate ESRI's tool that automatically labels the number of points as the density gets past the ability to visualize. Have a look at the attached map file.

It has a query that counts the number of points with the same geom and creates a label. I used our County address layer for the points. I used the normalize topology transform to group address points to have the same geom. The preview makes this easy to try different groupings.

It works pretty well but it would be nice if this were all done with a slick SQL update statement. Better yet if this was incorporated into the labeling options so it would scale automatically as the map is zoomed in/out.

One of the problems with what I've done is if the address points are also shown, it is impossible to tell what points are included in the grouping.

Curious what people think of this issue.

Attachments:
point number label.mxb

Dimitri


7,413 post(s)
#28-Mar-20 02:29

Very interesting project, definitely something to drill into...

Better yet if this was incorporated into the labeling options so it would scale automatically as the map is zoomed in/out.

I don't quite understand, do you mean something like zoom ranges, where layers turn on/off depending on scale (also would be useful to have)?

Mike Pelletier

2,122 post(s)
#28-Mar-20 13:51

Zoom ranges is useful for sure, but I was thinking that when this point cluster labeling is turn on and as you zoom in/out the software recalculates what points should be considered as part of visual clusters and thus changes the label accordingly.

joebocop
514 post(s)
#28-Mar-20 15:02

The web mapping frameworks have all had to tackle this problem. Here's an example from Bing

https://docs.microsoft.com/en-us/bingmaps/v8-web-control/map-control-concepts/clustering-module-examples/basic-clustering-example

Mike Pelletier

2,122 post(s)
#28-Mar-20 16:34

That's good and Manifold can do better!

A random grid of points doesn't work well with data like in the map example above. It would be great if we had the option to continue to display the original points. Perhaps allow them to be transparent to deemphasize clusters and in a different color to show they contribute to the count label, while allowing outlier points that are not in a cluster to still show unchanged.

Sergio40 post(s)
#29-Mar-20 02:12

I like the idea of the areas being somehow proportional to the variable.

When two (or more) circles intersect we loose some visual effect ...

Neither darker coulour on the intersection nor numbers representing the actual value of the (sum of) the variable offer, in my opinion, a neat solution.

Kriging may help in some cases just as redistributing points at random within a finite surface: but neither of the two are totally satisfactory, as they tend to assume continuity of data that is not necessarily in there to be seen; both fail to render a true visual image of concentrations occurring in small areas.

I had been thinking about circle coalescence: drops of a viscous liquid getting that bean-shape as they touch each other and progressively merge as you add more drops.

If only I could find the additional quantity r to buffer each circle of radius R so that the additional area of the enlarged circle (now of a radius= R+r) would compensate for the area lost by that circle due to the intersection...

At panned zooms, all would merge into a single circle, which would then acquire bean-shaped forms before individual circles/points would start appearing as you zoom in.

But my skills don' allo to do that myself Unfortunately in geometry and in Manifold Scripting do not enable me to grasp how to achieve that...

FWIW here is the source of COVID-19 data I use for my work:

https://opendata.ecdc.europa.eu/covid19/casedistribution/csv


s

bdg63 post(s)
#28-Mar-20 23:42

Craigslist does a neat thing showing rental properties.

Attachments:
zomedin.PNG
zomedout.PNG

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