What’s trending on OpenStreetMap?
Ever wanted to know what’s trending on OpenStreetMap? Looks like there is an easy way to find out the answer to that question! Researchers at the Geometa lab at the HSR University of Applied Sciences have an experimental bot project “Trending Places in OpenStreetMap” that is analysing the views on OSM tiles and verifying which ones are gaining in popularity due to a hike in interest, thereby determining the “Trending Places”.
What is a Trending Place?
Places that have unusually higher views than their normal views, implying that places like tourist hot spots are not trending unless there is an increase in the number of views from the average. – Geometa Lab Webpage
The bot also tweets out the most trending places (with a two day delay). The top 10 most trending place on 26th June –
— Trending Places (@trending_places) June 28, 2016
Trending Place in OpenStreetMap is definitely a #GeoGeek’s project but what is interesting is that already they have been able to link trends on the map to actual events on ground e.g. 04th May this year, Fort McMurray, Canada was trending on OSM and was the victim of wildfire in the beginning of May 2016.
— Trending Places (@trending_places) May 6, 2016
P.S: The Matlab style plots are perhaps too geeky for the general public… and considering all the awesome work behind the project, it would be really cool if the community can help, with maybe creating a heat map of the trending places 😉 The entire project is licensed under MIT License.
If you are interested in taking a look at the code behind the project – here’s the link to the GitHub page. If you’d rather first read more about the terminology and the current challenges of the project – here’s the link to the project website.
“Trending Places on OpenStreetMap” #Geoawesomeness 🙂
#Mapped: The most dangerous places to drive in the world
We are in the midst of a revolution in the transportation sector and one of the main aspects of that future is increased safety. Every single time autonomous vehicles are mentioned in an article, it also mentions how many road fatalities occur due to human error and how machines can help improve this situation.
Telegraph decided to map data from the World Health Organisation showing the number of fatalities per 100,000 inhabitants using CartoDB (could have used a better scale gradient). Collectively, there is a lot of room for improvement in our safety records across the world (San Marino had 0 for the year 2010! awesome!).
Autonomous vehicles are probably a few years, if not decades away but hopefully in the meantime, assisted driving features will help bring this figure down!