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Assumptions: - You’re working with a district shapefile having village polygons, and you want to add the village boundaries to OSM. (Find+replace the terms as appropriate for your use case) - Instead of separate polygons, you want each shared boundary between say 2 villages to be loaded on JOSM as a LINE shape, so that you can add it as a Way and then include it in the respective Relations of each village - So this process will help you convert those polygons into these common boundary lines
  • Load shapefile zip (having .shp etc) on mapshaper.org
  • console -> type “innerlines”, press enter. Shape changes to just the inner common boundaries

  • export, choose shapefile format (not geojson, its useless). rename it to “innerlines”

  • open QGIS, load both the original shapefile and this innerlines shapefile there
  • original shapefile : Dissolve (vector -> geoprocessing tools -> dissolve)
  • On the dissolved layer: Processing Toolbox -> Polygons to Lines

  • now you have the external boundary of the district.
  • Processing Toolbox -> Split with lines :: input layer: external boundary, split layer: innerlines

  • Now we have a new layer “split” having the external boundary also cut up wherever internal boundary line hits
  • Processing Toolbox -> Merge vector layer :: choose the split-up external boundary, and the innerlines layer

  • Now you have a new layer having all boundaries in neat segments that you can add directly as Way in JOSM
  • Right-click the new merged layer -> Export :: geojson type, and change the CRS to EPSG:4326 (in case it was in some other CRS originally)




hi everyone I just signed in to the open street map community and I would love to be an active volunteer


Mapping is of paramount importance for a cleaning machine rental service in Toronto, or any urban environment for that matter. Toronto is a bustling metropolis with diverse neighborhoods, commercial districts, and industrial areas. In such a dynamic city, having a well-defined mapping strategy can make or break a cleaning machine rental service. Let’s delve into why mapping is crucial for such a service in Toronto.

Efficient Resource Allocation: Toronto’s vast geographical expanse demands precise mapping to ensure efficient resource allocation. Knowing the exact locations of potential clients, industrial areas, or commercial zones enables rental services to strategically place their machines. This minimizes travel time between clients, reduces fuel costs, and optimizes the use of cleaning equipment.

Service Coverage: Accurate mapping allows cleaning machine rental services to define their service coverage areas effectively. They can ensure that no potential customer is left out, thereby maximizing their market reach. Moreover, they can tailor their services to different neighborhoods, understanding the specific needs and demands of each area.

Traffic and Congestion Management: Toronto’s notorious traffic congestion can significantly affect the efficiency of a cleaning machine rental service. With precise mapping and real-time traffic data, companies can plan routes that avoid traffic bottlenecks, reducing machine downtime and ensuring timely service delivery.

Customer Convenience: Clients renting cleaning machines in Toronto appreciate convenience. Mapping enables services to locate drop-off and pickup points that are convenient for customers. This enhances customer satisfaction and encourages repeat business.

Safety and Compliance: Mapping also plays a critical role in safety and compliance. Knowing the city’s zoning regulations, traffic rules, and other legal requirements ensures that the rental service operates within the confines of the law. Properly mapped routes also minimize the risk of accidents and damage to equipment.

Data Analytics and Improvement: Mapping tools can provide valuable data that can be analyzed to make informed business decisions. For instance, heatmaps of cleaning machine rentals can reveal high-demand areas, allowing companies to consider expanding their presence in those locations. It also helps in assessing machine utilization rates and maintenance needs.

Emergency Response: In case of breakdowns or emergencies, having a well-mapped network of service providers, repair shops, and alternative machines can be a lifesaver. Quick response times are crucial to maintain the reliability of the service.

Environmental Considerations: Mapping can assist in minimizing the carbon footprint of a cleaning machine rental service. By optimizing routes and reducing unnecessary travel, the service can contribute to a cleaner and more sustainable Toronto.

Competitive Advantage: In a competitive market like Toronto, where multiple cleaning machine rental services may be vying for the same customers, efficient mapping can give a competitive edge. Timely service, cost-effectiveness, and convenience are all factors that can set one service apart from the rest.

In conclusion, mapping is not just important but indispensable for a cleaning machine rental service operating in Toronto. It directly impacts efficiency, customer satisfaction, safety, compliance, and the overall success of the business. A well-thought-out mapping strategy can help such services navigate the complexities of the city, ensuring they deliver the best possible service to their clients while optimizing their operations.



I honestly don’t have the words to describe the overwhelming flow of emotions that I am experiencing regarding this project.

*This a whole new experience for me and I feel so blessed to be apart of this program and would honestly recommend anyone in joining and learning about the values and endless opportunities that exist with using (OPEN STREET MAP). From the first hand experiences in my community to mapping specified areas in my country it is such a remarkable experience for the young and young at heart to widen their horizons and try new things.





Teaching comes via OSMs online training session.

OpenStreetMap is a map of the world, created by people like you and free to use under an open license.


Adrian Glover initiates on 9/9/23 based on introduction from Red Cross.🎉 Mapping done on T430.

OpenStreetMap is a map of the world, created by people like you and free to use under an open license.




On the 6th of September 2023, we the members of the committee had a review on the volume of applications submitted by the applicants for SotM Africa which is slated to be held in Cameroun this year 2923. Letters were sent to the applicants whose application was not successful.

On the 8th, we concluded were 15 of the applicants made it to the top. Letters will be sent to them by the 9th of September, 2023.









Being now 67 years of age I have started to think that I should get out and explore my local area. Partly to get fitter but also I have now got my free bus pass and I intend to exploit it. I have lived in Doncaster since 2016 (7 yrs). I have some knowledge of the local area obtained by driving around, but I feel its time I got out on my bicycle and explore.


Revised Script for usage in macOS 12+ with zsh:
#!/bin/zsh
echo "Download"
wget -t0 -c "http://download.geofabrik.de/europe/andorra-latest.osm.pbf"
wget -t0 -c "http://download.geofabrik.de/europe/austria-latest.osm.pbf"
wget -t0 -c "http://download.geofabrik.de/europe/belgium-latest.osm.pbf"
wget -t0 -c "http://download.geofabrik.de/africa/canary-islands-latest.osm.pbf"
wget -t0 -c "http://download.geofabrik.de/europe/czech-republic-latest.osm.pbf"
wget -t0 -c "http://download.geofabrik.de/europe/denmark-latest.osm.pbf"

echo "Convert"
./osmconvert --drop-version andorra-latest.osm.pbf -o=andorra-latest.o5m
rm -rvf andorra-latest.osm.pbf
./osmconvert andorra-latest.o5m -o=merged.o5m
rm -rvf andorra-latest.o5m

for FILE in ./*.osm.pbf; do ./osmconvert --drop-version $FILE -o=$(basename $FILE .osm.pbf).o5m; ./osmconvert $(basename $FILE .osm.pbf).o5m merged.o5m -o=merged_cache.o5m; rm -rvf $(basename $FILE .osm.pbf).o5m; mv -v merged_cache.o5m merged.o5m; done

echo "splitter" 
## latest splitter Version r653 used
java -Xmx5G -jar splitter-r653/splitter.jar --output-dir=tiles --max-nodes=1200000 merged.o5m

echo "mkgmap"
## latest mkgmap Version r4910 used
## template 2022pn.typ used, use what you like :)
java -Xmx5G -jar mkgmap-r4910/mkgmap.jar --country-name=OSMMap --family-name="OSM map" --product-version=1 --bounds=bounds-latest --dem-interpolation=auto --make-poi-index --poi-address --unicode --index --split-name-index --gmapsupp --report-routing-islands -c mkgmap-r4910/examples/sample.cfg -c tiles/template.args 2022pn.typ --style-file=../ --check-styles --route --net --gmapi --add-boundary-nodes-at-admin-boundaries

echo "final clean up"
rm -rvf *latest.o5m
rm merged.o5m
cd tiles
rm -rvf *.osm.pbf
cd ..
rm -rvf 6*.img 
rm -rvf ovm_6*.img

echo "The End"




… unless you want a greatbighuge label inexplicably hovering over the map at z=16.

Looking over this fine city of Toronto, I saw a couple of brown labels for places that are sort-of not real. Exporting and grepping local exports showed me they were landuse ways with a name value set.

I’m sure there are plenty of good examples where a landuse area would have a name. In these cases, though:

  • one was the name of a city/developer study from roughly five years ago that has disappeared from the record since then. Will it become a neighbourhood name? Who knows, but that’s for the future and not for us to force. (fun fact: it’s apparently the densest concentration of office workers in the city. Less fun but very Toronto fact: there is no dedicated transit there. I had a job there ~2006–2008 and new transit was planned, but then the trainwreck formerly known as Mayor Rob Ford happened so it didn’t.)

  • one was a drive-by tagging error by an out-of-band specialist. I really think they meant it for a bus stop.
Aligned with my personal policy of “Only kvetch after fixing”, they’re gone and our z=16 will be so much less jarring. Thank me later.