OpenStreetMap

OpenStreetMap Data Analysis: Entry 1

Posted by Jennings Anderson on 20 June 2016 in English (English)

Howdy OpenStreetMap, I am excited to share that I am working as a Research Fellow with Mapbox this summer! As a research fellow, I am looking to better understand contributions to OSM.

For my first project, I have been using the tile-reduce framework to summarize per-tile visible edits from the Historical OSM-QA-Tiles. These historical tiles are a snapshot of what the map looked like at the time listed on the link.

With this annual resolution, we can visualize the edits (those edits that were visible at the end of that year) that happened on each tile. So far, I’ve summarized them as a) number of editors, b) number of objects, and c) recency of the latest edit (relative to that year).

The OSM-QA-Tiles are all generated at Zoom level 12, which separates the world into 5Million+ tiles. Some tiles have few objects while others have ten-thousand plus.

So far I have created two interactive maps to investigate OpenStreetMap editing behavior at this tile-level analysis:

1. Editor Density (Number of editors active on a tile)

### 2. Edit Recency (Time since last edit on the tile)

Editor Density

This map highlights tiles where multiple editors have been active. The most active editors in most cases are automated bots, especially in the more recent years. For best results, moving the slider in the bottom left for Minimum Users Per Tile to 2 or 3 will exclude most of these automated edits.

Examples

#### 2007: European Hotspots By increasing the minimum object and minimum user thresholds, areas of heavy editing activity pop out: 2007 european hotspots

2007: US Tiger Import - Automated Edits

This image of the activity in the US in 2007 has no threshold on the limited number of objects or users per tile, so you can see all of the tiles affected by the 2007 import. If you increase the threshold, it changes dramatically tiger import

Edit Recency

This map shows the recency of edits to a tile, relative to the year of analysis. It looks surprising at first how many tiles are edited at the end of the year, but that is most likely a function of automated bots. Again, if you move the threshold for number of editors or objects per tile, interesting patterns pop out across the world where users may have been active early in the year and then are less active later. The 2010 Haiti Earthquake is a good example, as it occurred in January of 2010.

2007: The stages of the Tiger Import

If we view by latest edit date, relative to the year, we see the state-by-state import in the US:

2008: North Eastern Hemisphere

2008 recency

More to come! -Jennings

Location: Logan Circle/Shaw, Chinatown, Washington, Washington, D.C., 2005, United States of America

Comment from TheDutchMan13 on 11 July 2016 at 00:12

This is awesome! Thanks!

Comment from joost schouppe on 25 November 2016 at 17:43

I’m a little surprised by how little attention there has been to these very very cool tools.

One thing I wondered about though: it looks like a single edit to a country outline can colour every tile within that outline. I don’t know exactly how vector tiles work, but would it not be an idea to exclude polygons which have no nodes within the tile?

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