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Which package to use?

  • leaflet is best for datasets with <50,000 features…my tree canopy dataset had 193,418 multipolygons
  • leafgl is recommended in concert with leaflet (spoiler: it didn’t work for me)
  • settled on mapview

Plotting with mapview

Map of Philadelphia overlaid with tree canopy data, some of which is missing in distinct vertical bands

  • Vertical strips of data missing
  • Non-functional interactivity
  • RStudio would crash
  • VSCode was hit-or-miss

Tweet with text: #RSpatial friends, do you have any tips for working with datasets that have 200k+ features (e.g. multipolygons)? I tried using the #mapview package and it struggled. It couldn't render the full map 👇and I wasn't able to use the zoom controls. What am I missing? #RStats. Tweet fig alt: Map of Philadelphia overlaid with tree canopy data, some of which is missing in distinct vertical bands

Suggestion

Open in QGIS


Tweet text: In such situations I usually export the layer, and explore it in QGIS




Tweet text: recently i've counted the number of points in a feature (esp super complicated multipolygons) and simplified the geometry based on that (next tweet!). Next tweet text: e.g. pts <- mapview::npts(feature) if (pts > 10000) {rmapshaper::ms_simplify(feature, keep = 0.1, keep_shapes = TRUE)} else if (pts > 5000) {ms_simplify(feature, keep = 0.3, keep_shapes = TRUE)} else {feature}

Suggestion

Simplify geometry with rmapshaper

  • super complicated multipolygons
  • simplifying eliminating features
    • but it could!

I use the package tmap, it works great. You have 2 viewing options the static one and the one you can zoom in and out.

Suggestion

Try the tmap package

Try {rdeck}. Handles datasets of that size and orders of magnitude larger without hassles. Can also use vector tiles if you need to larger.

Suggestion (WIP)

Try the rdeck package

Thank you #RStats!

Tweet quoting the original tweet asking for help. Text reads: Update: I’ve got a functional map! Many thanks to all the lovely people that contributed to this thread ✨ I simplified the geometries from 193k features to 149k using #rmapshaper and created the map using #tmap #RStats #RSpatial

Bonus slide!

This slide was added after the presentation to include feedback from talk attendees

  • Rendering issues might come from maxing out the RAM
  • To reduce the size of the dataset, one could adjust the precision because sometimes the features contain more digits than you need or can meaningfully rely on
  • The mapdeck package might be another one to try. It’s powerful and sits on Mapbox which lets you pull in nice basemaps as well