OpenStreetMap
Recently, Microsoft released 125 million US building footprints as open data across 50 states. The data is freely available for download and use. You can read about previous release of 9.8 million buildings here.
With the help of tippecanoe and Mapbox Studio, I have visualized Hawaii dataset to know how data looks like.
Mapbox recently rolled out new satellite imagery for many places around the globe. I’m happy to share that some of the Indian cities also got new imagery with this update and the community can use this for mapping in OpenStreetMap. I always prefer best imagery to add highways and buildings the most.
Bengaluru, Karnataka
Hello all, Namasthe! 🙏 We had an amazing HOT Mapathon on July 21st at Mapbox India office. We had the local OSM community along with folks who were mapping for the first time adding approximately 3000 buildings in Cambodia for Eliminate Malaria task.
ಕನ್ನಡ ನಾಡು ಕಂಡ ಮೇರು ನಟ, ನಟಸಾರ್ವಭೌಮ ಡಾ. ರಾಜ್ ಕುಮಾರ್ https://en.wikipedia.org/wiki/Rajkumar_(actor) ಅವರ ಸ್ಮಾರಕವನ್ನು ಈಗ ಎಲ್ಲರೂ ಮ್ಯಾಪಿಲರಿಯ ಮೂಲಕ ಕುಂತಲ್ಲೆ ವಿಕ್ಷಿಸಬಹುದು. ಕನ್ನಡ ನಾಡು ನುಡಿ ಮತ್ತು ಚಿತ್ರರಂಗಕ್ಕೆ ಅವರ ಕೊಡುಗೆ ಅಪಾರ. ಚಿತ್ರರಂಗದಲ್ಲಿನ ಜೀವಮಾನದ ಸಾಧನೆಗಾಗಿ ಭಾರತ ಸರ್ಕಾರವು ಚಿತ್ರರಂಗದ ಅತಿ ದೊಡ್ಡ ದಾದಾಸಾಹೇಬ್ ಫಾಲ್ಕೆ ಪ್ರಶಸ್ತಿ ಯನ್ನು ನೀಡಿತು. ಇತ್ತೀಚೆಗೆ ಗೂಗಲ್ ಇಂಡಿಯಾ ಅವರನ್ನು ಗೂಗಲ್ ಡೂಡಲ್ ಮೂಲಕ ಗೌರವಿಸಿತು.
Microsoft recently released 9.8 million building footprint data of 102 cities covering 44 US states to the OpenStreetMap community. This is a huge boost to improve the building data in many parts of the United States. Right now, we have ~ 19 million buildings already added by the community through imagery tracing and imports.
The most exciting part of this data is that all the footprints have height information. That means we can generate simple 3D buildings. I downloaded all the data and created a Mapbox style with 3D extrusion:
Philadelphia (click here see the web map)
Boston (click here see the web map)
Baltimore (click here see the web map)
In general, the data is of good quality and will improve the building coverage in the US by 150%. But the quality may vary from city to city. Local mappers should evaluate each city before deciding to import.
Feel free to play with data, post your findings or screenshots of the data evaluation for the city you are interested in and let the community know how valuable this data is going to be for OpenStreetMap.
Code and step is available in Github repo: https://github.com/osmlab/ms-building-import/
* California not included in the tileset since OSM has fairly good coverage
Last weekend, I tried modelling San Francisco City Hall in S3DB. The public building has 100 years of glorious history. The diameter of the central dome is around 34 m and total height of the building is 93 m.
From Wikipedia
The co-ordinates of the building is 37.77910°N/122.41937°W. Edited this model first through OSM Sandbox and copied all the geometries and tags to main OSM database. I used JOSM current version and Kendzi3D plugin to visualise locally.
In 2016, San Francisco city Government published LiDAR-derived building footprints that include both geometry and height information. One of the main goals of the San Francisco OpenStreetMap community was to import this height data to the existing buildings in OpenStreetMap. The project was initiated by SF community in November 2016, recently Brandon and Daniel lead a great Mapathon at Mapbox SF office.
Together with the community, Mapbox data team remotely joined and imported nearly 140,000 building heights to OpenStreetMap. Now we can get a real world like experience using popular 3D renderers like OSM Buildings and Mapbox GL JS or create realistic city using Blender or style buildings using Unity. Cheers to the all of them who made this project successful!
Maptime SF/MaptimeOAK and Mapbox SF are hosting a Mapathon on March 14th, Tuesday at 6:30 pm PST to import building heights. Please RSVP to SF OpenStreetMap Community to be a part of this awesome project.
Image from Wikipedia
San Francisco has building footprints, Points of Interest, and traffic signals for the entire city in OpenStreetMap. All these map features makes San Francisco as one of the well mapped cities on OpenStreetMap. In 2016, the San Francisco city Government published LiDAR-derived building footprints that include both geometry and height information. One of the goals of the SF OpenStreetMap community is to add height information to existing buildings in OpenStreetMap.
To jump in quickly into the project, do check the OpenStreetMap wiki to know more and talk to the community on Gitter to get involved. Also, make sure to create a dedicated OSM import account before jumping into the task and post it here.
This changeset look suspicious where a user added lot of point’s of interest like amenity=coffee, and amenity=beauty shops in Mexico city, Mexico. The user used Maps.me editor to add data.
My colleague @upendrakarukonda has left a comment on the changeset 3 months ago and removed only coffee shops. Again, I’ve commented for the second time on another changeset. We didn’t observe any reply from the mapper since. So sharing here with the community to examine beauty care places and take necessary actions.
Thank you
The SF Bay area community is trying to import height data for buildings in the city of San Francisco.
Adding height to existing buildings will enhance the data especially when used with popular renderers like OSM Buildings and Mapbox GL JS.
We are using raw LIDAR derived building height data released by SF local government under a CC0 (Creative Commons) license (data download here).
For each building in OSM, we compare the footprint from SF goverment buildings, if there is 70% overlap, we add the height. Buildings with existing height tag won’t be touched.
The task is hosted in OSM-US. The importing has begun at http://tasks.openstreetmap.us/project/71
Note: Before jumping into the task, please read all the instructions carefully.
To know more about the project, or if you have ideas please post them here:
Here are the few OSM edits we have noticed in the last week. Observed that many experienced mappers need to think of a good changeset comments while they upload their changes to main database.
If you come across any unexplained mapping from an OSM user, let them know through your changeset comments and send them related resources, wikis, tagging system to new mappers, and encourage them to map in good way.
Thank you!!
Observations of mapping behaviour on OSM can give an insight into recognizing recurrent mapping problems our mappers are facing. Here are few of the issues observed between 18th July - 28 nd July on OSM:
House numbers were given in name=* tag: 1. Community responded with a comment and provided building wiki resource to the user.
‘casa’ spanish for ‘Home’ were given to residential buildings:1. Community responded with a comment.
Buildings were given name=* tag with key values such as ‘Cra’, ‘Calle’, ‘Betos’, and house numbers: [1] (osm.org/changeset/38657218#map=17/11.00815/-74.79661). Community responded with a comment.
Classification of highways were changed in Moscow: 1. The Russian community responded with a comment.
Lots of untagged nodes, market place was deleted: 1, 2. Community member reverted 1st changeset and commented on the 2nd one.
Retraced highway over previously existing one creating crossings: 1. Community responded with a comment.
Deleted highway: 1. Community responded with a comment.
Castles added: 1. Community member responded with a comment.
Failed import: 1
A ton of tourism = attraction, tourism = camp_site tags added:
If you come across any unexplained mapping from an OSM user, let them know through changeset comments. It starts a constructive discussion we can learn from and creates a positive environment for the OSM community to work together.
Look forward to seeing more of this next week.
From last week I’m noticing lot data coming to OpenStreetMap using DigitalGlobe imagery. Some users are adding residential roads and overlapping the primary roads.
Augmented changeset viewer: https://overpass-api.de/achavi/?changeset=40938983
Throwing here a small post to let know the community.
I noticed buildings imports back in February 2016 which were having building=yes tag for all building nodes. Have captured the details here.
OSM user: geopeppe imported all these buildings and after my message, he cleaned unnecessary tags on nodes but now only exists are:
I’d like to inform the community of Italy about this import and take next actions towards clean up or right documentations.
Data quality is as important a function for any contributor to know as is adding large quantities of detailed data to OpenStreetMap. If we were talking one or two individuals editing, quality assurance would be straightforward, but what about with 2.4+ million registered users adding 2,000,000+ nodes a day?
Luckily, the tireless vigilence of active contributors is a source of some consolation but nearly not sufficient by itself. The important question then becomes, how can we detect and remedy mistakes and acts of vandalism as and when they happen? In trying to find answers we’ve put together a “Validating OpenStreetMap Guide” which aims share our learnings to working with OpenStretMap. The guide covers the basics of handling data validation in OpenStreetMap by defining problematic data, tools for detection, methods for investigation, and avenues for resolution for individual and community mapping efforts.
History panel showing different details about users and versions
The union territory of India, Chandigarh has been mapped well with neat buildings, highways. There are so many OSM contributors to this city. OSM India community is thankful to all the mappers who have contributed to mapping the city in a detailed manner. Oberaffe and chandusekharreddy have made mentionable number of edits . : )
If you are a beginner to OpenStreetMap then you can look into Mapbox mapping guides to fix common mapping errors that beginner’s usually do.
Link - https://labs.mapbox.com/mapping/becoming-a-power-mapper/
ನೀವು ಓಪನ್ ಸ್ಟ್ರೀಟ್ ಮ್ಯಾಪ್ ಗೆ ಹೊಸಬರಿದ್ದರೆ, ಸಹಜವಾಗಿ ತಪ್ಪು ಮಾಡಬೇಕಾಗುತ್ತದೆ. ಕೆಳಕಂಡ ಕೊಂಡಿಯಲ್ಲಿ ಸಾಮನ್ಯವಾದ ಮ್ಯಾಪ್ ತಪ್ಪುಗಳು ಹಾಗು ಅವುಗಳನ್ನು ಹೇಗೆ ಸುದಾರಿಸಬಹುದು ಎಂದು ನೋಡಬಹುದು.
ಕೊಂಡಿ - https://labs.mapbox.com/mapping/becoming-a-power-mapper/
ಇಲ್ಲಿ ಮ್ಯಾಪ್ ಮಾಡಲು ಎಲ್ಲರಿಗೂ ಸ್ವತಂತ್ರವಿದೆ. ನಿಮಗೆ ಸ್ವಾಗತ. : )
ನಮ್ಮೂರು ಹಾಸನ ಜಿಲ್ಲೆಯಿಂದ ಸುಮಾರು 12 ಕಿಲೋ ಮೀಟರ್ ದೂರದಲ್ಲಿ ಉಂಟು. ಹೆಸರು ಕೌಶಿಕ ಹಿರಿಹಳ್ಳಿ ಎಂದು. ಸುಮಾರು 70-80 ಮನೆಗಳಿರಬಹುದು. ಹಳ್ಳಿಗೆ ಬೇಕಾದ ಎಲ್ಲ ಸೌಕರ್ಯಗಳು ಇಲ್ಲಿ ಲಬ್ಯ.
ಊರಿನ ಆಚೆ ಓಂದು ಪ್ರೌಡಶಾಲೆ, ಆರೋಗ್ಯ ಕೇಂದ್ರ, ಪಶು ಆಸ್ಪತ್ರೆ ಕಾಣಬಹುದು. ಒಪನ್ ಸ್ತ್ರೀಟ್ ಮ್ಯಾಪ್ ನಿಂದ ನಮ್ಮ ಊರಿನ ಏಲ್ಲಾ ತರಹದ ಅಂಶಗಳನ್ನು ಗಮನಿಸಬಹುದು. ಯಾವ ಯಾವ ಪ್ರದೇಶಗಳಲ್ಲಿ ಹೊಲಗಳು, ಕೆರೆ ಬಾವಿಗಳು, ಬಸ್ ನಿಲ್ದಾಣಗಳು, ಮನೆಗಳು, ದೇವಸ್ಥಾನಗಳು ಹಾಗೂ ಮರಗಳು ಇದ್ದಾವೆ ಎಂದು ಪರಿಪೂಣರ್ ವಾಗಿ ನೋಡಬಹುದು.
ಎಲ್ಲ ಮನೆಗಳನ್ನು 3D ಯಲ್ಲೂ ಸಹ ಕಾಣಬಹುದು.
ರೆಫ್ ಟ್ಯಾಗ್ ಅನ್ನು ಭಾರತದ ಎಲ್ಲ ರಾಜ್ಯಗಳಿಗು ಹಾಗೂ ಕೇಂದ್ರಾಡಳಿತ ಪ್ರದೇಶಗಳಿಗು ಇಂಪ್ಲಿಮೆಂಟ್ ಮಾಡಿದ್ದೇನೆ. ಸುಮಾರು 15 ದಿನಗಳ ಹಿಂದೆ ಹಾಕಿದ್ದೆ, ಈಗ ಅದನ್ನು ಜೂಮ್ ಲೆವೆಲ್ (zoom=4) ರಲ್ಲಿ ಕಾಣಬಹುದು. ಚಿಕ್ಕ ರಾಜ್ಯಗಳಾದ ಕೇರಳ, ಗೋವ, ಪಂಜಾಬ್, ದೆಹಲಿ, ಕೇಂದ್ರಾಡಳಿತ ಪ್ರದೇಶಗಳಲ್ಲಿ ಮತ್ತು ಪೂರ್ವ ಭಾಗದ ರಾಜ್ಯಗಳಲ್ಲಿ ನೋಡಲು ಸಾದ್ಯವಿಲ್ಲ. ಎಕೆಂದರೆ ಟ್ಯಾಗ್ ಗೆ ಸರಿಸಮನಾದ ಜಾಗವಿಲ್ಲದುದರಿಂದ.
ಬನ್ನಿ ಭಾರತದ ನಕ್ಷೆಯನ್ನು ಉತ್ತಮಗೊಳಿಸೋಣ. 🌏 🙏
Mysore Palace ( Kannada: ಮೈಸೂರು ಅರಮನೆ ) also called as Amba Vilas Palace located in the city Mysuru, Karnataka, India.
Started this small project a week ago, looking into Palace photos and OSM wiki on Simple 3D buildings, Kendzi JOSM plugin developed this simple geometry building.
The whole building is marked as building = yes on top of it everything is building:part = yes. Texturing is another important thing in 3D development. Used Hexadecimal colour codes to building facade and roofs.
Kendzi3d is a useful plugin for JOSM for 3D mapping. It renders the building parts immediately as soon you change the height, min_height, building:colour… etc tags with out uploading the data to the OSM.
Screen shots from F4 Map