It is always amazing to connect with like-minded people on topics you are interested in and talk about making it better. That’s what State of The Map has always been to me. And this time, thanks to HOT UnSummit, I got a chance to attend one as a student, and understand the use cases of maps from a very fresh perspective.

After more than 5 years of working in the mapping sector, I decided to pursue my Master’s in Cartography and being a student again, both of the conferences of SoTM and FOSS4G proved to be very beneficial to attend and understand the ways the mapping community are branching out in.

I have been a part of the SoTM community for a few years now and have got a chance to even present some of the talks on OSM and validation. However, the whole experience at Florence this time was very different and engaging. The first in person conference after COVID, it was fantastic to meet everyone I knew in person and connect on maps and more.

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When you happen to walk on a street, what usually catches your eye? The street? The trees? Or a cute little shop in the corner having a neon sign board saying pastry? Shop with a pastry sign, mostly! Such shops, stores, restaurants, bakeries, ATMs, etc. are what we call Points of Interest (POI). POIs makes the map well, interesting (pun unintended). It is equally important as streets and buildings to any map for navigation.

Mapping POIs usually requires a mapper to collect GPS traces and take photos on the ground. With Mapillary street-level photos, anyone familiar with the city can look at any Mapillary photo taken by others and use them for mapping POIs.

Here’s how you can map them👇🏻

• Open an area you are interested in JOSM.
• Enable the Mapillary plugin to see the images of that street. If you don’t have the plugin available go to Preferences > Plugin.

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In the last two weeks, as a part of improving the quality of base-map data of Singapore on OpenStreetMap, the Mapbox data team along with the community has completed adding missing streets and buildings in Singapore.

For this task, the team used a combination of Mapbox and Bing satellite imagery to improve the road network and building footprints data. We presently have managed to refresh more than ~1200 kilometers of roads. Additionally, we also have added close to ~40,280 buildings.

Take a look at the visualisation below which shows the buildings added during the last two weeks.

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With an aim of making OpenStreetMap more navigable and accurate in routing, we started mapping turn restrictions and exit-destinations in Canada in its five important cities: Toronto, Ottawa, Montreal, Vancouver and Calgary. The tasks which spread over a month have been completed; we have finished adding and validating both turn restrictions and exit-destinations in the selected cities of Canada with the support from the OpenStreetMap community.

Summary of improvements

Mapping turn restrictions was flagged off on 21 of July with data team and the community working on adding missing turn restrictions and validating the ones that are present.

As the mapping progressed, workflow was getting updated every time the team had some doubts regarding how best to map a particularly different turn restriction that was detected. The questions we had were posted on the mapping ticket we used and the community got back to us almost immediately with clarifications to our questions. We completed both adding and validating turn restrictions in 14 days.

Exit-destination mapping started on August 11. For exit and destinations, a slightly different approach was followed, unlike how we mapped previously using only checkautopista2. Each highway was considered a separate task, which was integrated into tasking manager, with a specific link to checkautopista2 that loaded that particular highway that was selected using tasking manager.

Below is the full breakdown of how many turn restrictions and exit-destinations were mapped:

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Exit numbers and destinations on highways are an important aspect of navigation since they guide the user where do they have to exit the freeway in order to reach their destination and which other cities or towns or areas the highway interlinks. Making any map more navigable or any routing machine more accurate includes all the minute details and improvements. In an effort to broaden the reach of OpenStreetMap to the people and make it better in routing and guidance, we are adding exit and destination tags for highways in five priority cities of Canada.

The Approach:

We are concentrating on five major cities of Canada: Toronto, Ottawa, Montreal, Vancouver and Calgary to add the exit and destination tags and the method we intend to follow 👇🏻

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It was two fantastic days of hacking, discovering, sharing and generally having fun. OSM HackWeekend opened a lot of doors in the process of learning new things, sharing new ideas, building new tools, hacking on amazing stuff. It was the first time Mapbox BLR played host to two days of hacking, working on tools that build and escalate OpenStreetMap and the results were anything but ordinary.

Hack weekend (2 & 3 of July) served as a platform for meeting a lot of new and interesting people and the turn out we had for the event was equally diverse and intriguing. We had twenty one people attend the event from different places across India and it was fascinating to hear what their interests are and why they thought OpenStreetMap HackWeekend would broaden their perspective and give a new edge to their work profiles.

Day 1:

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What better ways to spend weekends than mapping? ;)

And it’s like icing on the cake when World Environment Day falls on the end of the week. No better day to kickstart Basaveshwaranagar Mapping Party!

Basaveshwarnagar neighbourhood

This quaint little neighbourhood has been home to us for the past 20 years, and even though we thought we had all its entities etched in our memory, the growth this area has had in the recent years has baffled us, nonetheless. There are so many new things coming up, the neighbourhood has gone through so many changes that it was almost a necessity to keep up with the pace of its growth and have an idea about what is happening in our immediate surroundings. Well, mapping seemed like an answer to all those questions and hence, tada, Basaveshwaranagar Mapping Party has officially been flagged off!

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Imagine you are driving down a highway with your car guidance giving you the instruction “In two miles, take exit number 164A and follow the signs towards Dearborn Street” using OpenStreetMap data. This will soon be possible with upcoming improvements to the OSRM guidance engine that will use destination tags more intelligently from the map data.

Over the last week, the Mapbox data team reviewed freeways in 30 cities across the United States to find gaps, in exit number and destination information that could be improved using Mapillary images and official documents. We want to share our findings here and welcome your feedback on our approach, use of tools, and workflow.

Our Approach

We stuck to reviewing motorways and motorway junctions, as we did during mapping destination signs for 9 US States, and covered 328 motorways in total. As part of the review, we used Mapillary imagery, official Department of Transport data, Crosscountryroads, Aaroads, and Wikipedia for reference. For identification of exit numbers and destination tags, we relied on Checkautopista2 by k1wi.

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Every Mapper knows that nothing beats Field Mapping in terms of perfection and of course, the sheer joy of mapping. Having a notepad, pen, gps and walking along the streets, marking every detail will give you a clear picture of that particular area and about your observation skills in noticing tiny details about what makes that particular street, colony or area, tick! Field mapping gives you first hand insight about the features in that particular place, what kind of streets are there, how the colony is built etc…

This time I had a taste of the first city based field mapping when I got to roam around streets of Indiranagar, trying to see what interests the people in that area, what are the new point of interests, what new restaurants and cafes have popped up, where are the atms and banks, how new buildings are shaping up, are there any important points missing from the maps?

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This time, I tried to do something new and took to improving road network and buildings in two areas that are probably very different from each other in terms of the dynamics or the urban set up. But both had one thing in common, clusters. The settlements were clustered and packed and hence, it proved to be a challenging task editing both Ranchi and Dehradun

Road tracing in Ranchi was tough mainly because of its congested built up.

From the satellite data, it was pretty clear that the capital city of Jharkand is clustered. The settlements were packed. But there was also a lot of open space. It was easy to make out highways and tracks but difficult to decipher where the residential roads were due to the mass build up of residential settlements.

Things that I noticed

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I started mapping the Basaveshwarnagar neighborhood, in Bengaluru, the area where I stay and thought I knew the place pretty well.

Before starting mapping, I was a little apprehensive about how much of Bengaluru has already been mapped. A few areas that are not mapped, might probably be the ones which I don’t know very well. So, I was wondering what was left for me to map.

But to my surprise and a bit of a shock, I discovered so many errors in the data in my area and to say I was overwhelmed would be an understatement.

One grouse would be why hadn’t I done this before.

The area I concentrated on

Things that I edited

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Underway