This is the script I came up with to make some stats on the huts and shelters of Sweden. The data was fetched via overpass-turbo.

download the geojson from Overpass Turbo -> export or save as from JOSM.

example query: access!=private and (tourism=alpine_hut or tourism=wilderness_hut or (amenity=shelter and shelter_type!=public_transport)) in sweden

you can run this query from inside JOSM - see the JOSM wiki.

The script is here: https://gist.github.com/pangoSE/5294e835c9bead773e8036603a90b898

This was the output for Sweden:

$ ./stats.sh vin-190110.geojson 
Numbers of each type:
Shelters - total: 2629
Shelters - Lean to (sv. vindskydd): 793
Shelters - Basic hut (sv. stuga utan uppvärmning): 129
Shelters - Weather shelter (sv. väderskydd endast lämpad för kort uppehåll vid dåligt väder): 355
Shelters - Picnic shelter (sv. liten byggnad med tak, eldstad och skorsten i mitten): 251
Shelters - Unknown type: 1692
Wilderness huts: 43
Alpine huts: 82

Lean_to shelters details:
- has description tag: 29 - 3%
- has fireplace=yes: 305 - 38%
- has floor=wood: 7 - 0%
- has image: 18 - 2%
- has snowmobile=yes: 28 - 3%
- has water_source tag: 4 - 0%
- has wood_provided=yes: 3 - 0%

Basic huts details:
- has description tag: 16 - 12%
- has fireplace=yes: 52 - 40%
- has image: 1 - 0%
- has snowmobile=yes: 18 - 13%
- has water_source tag: 0 - 0%
- has wood_provided=yes: 0 - 0%

Wilderness huts details:
- has description tag: 18 - 41%
- has fireplace=yes: 41 - 95%
- has image: 5 - 11%
- has snowmobile=yes: 18 - 41%
- has water_source tag: 0 - 0%
- has wood_provided=yes: 0 - 0%

Alpine huts details:
- has description tag: 12 - 14%
- has fireplace=yes: 4 - 4%
- has image: 5 - 6%
- has snowmobile=yes: 19 - 23%
- has water_source tag: 2 - 2%
- has wood_provided=yes: 5 - 6%

Earlier this year, Facebook launched their new AI detected feature service MapWithAI along with their custom version of the iD editor, RapiD. Kaart quickly adopted RapiD into our road vectorization workflows and saw impressive efficiency and data accuracy increases for those projects by being able to focus on the quality of the edits with the time usually spent on vectorization. We recognized the potential impact on data coverage and editing efficiency but noticed a need for an integration with JOSM.

It’s a known problem that web based editors like RapiD are difficult to use where an internet connection is either unstable or is slow enough that it brings the editor to a halt. Incorporating the MapWithAI data into JOSM would facilitate use of the data in parts of the world where a network connection may be unstable.

In September, one of Kaart’s engineers, Taylor Smock, started working on a project to create a JOSM plugin that would utilize the MapWithAI service. With some technical support from the Maps team at Facebook, we have been able to create a plugin at feature parity with RapiD but with some JOSM-esque additions.

… See full entry

For those who aren’t aware, inside some OSM editors is something called the “Name Suggestion Index” or NSI, and this lets mappers use a consistent name / brand across the map, for places such as a McDonald’s, or a Supermarket.

Many people may have used the NSI (https://nsi.guide) without even realising it - if you added a node or way and started to type, for example “Burger King”, and had the editor suggest to you that you select “Burger King” with the official logo on screen, this was the NSI at work.

The NSI is maintained over on GitHub, and suggestible names don’t all exist on the list automatically, they have to be added to the index.

One such suggestion I have made to the group of maintainers is adding brand names for Supermarket Cafe’s within the UK, including Tesco, Asda, Sainsbury’s, M&S and Morrisons, as I believe many of the supermarkets include a cafe inside, and having them mapped as a node (amenity:cafe) within each store would be beneficial to OSM and OSM users. All these supermarkets have a separate NSI entry for their respective petrol stations, and I think the same should be true for their cafe’s

Not all stores have a cafe, and of those that do, not all of them follow the same opening hours as the main store, which is another reason I think adding them separately would be beneficial.

One question that has arisen is if this is a suitable addition to the NSI, and if the name tag should be that of the Supermarkets name, eg “Asda Cafe”, or if it should be something else, as the cafe itself is inside the Supermarket, and often physical signage within the store simply reads “cafe”, which, while might be the correct “name” to give, could be considered too generic, and actually flags an error within iD.

I’d be keen to hear anyone else’s views on whether Supermarket Cafe’s should exist individually within OSM, and if so, should they have the name that matches the supermarket itself, eg “Asda Cafe”, or be left blank, or as something else?

The Land of Hills and Ponds

As I mapped Turkmenistan a couple of years ago, I noted that two locations were marked as the town of Darganata. Only one could be correct, and in my explorations I determined which one was Darganata, then pursued the correct name of the other, which turned out to be a village named Çarwadar. I made the correction, but filed away a question in the back of my mind: why would a mapper insert such an obvious error in OSM?

The answer came to light yesterday as I examined a Soviet military map of the area. In Soviet times, Çarwadar was a state farm named Sovkhoz Dargan-Ata, or in Russian совхоз “Дарган-Ата”(the contraction “sovkhoz” means “state farm”). Not a town, not even a village in Soviet terms, but a state farm community named in honor of its big brother a few kilometers away. Mystery solved! Today Çarwadar is a full fledged village, not just a farm community, and enjoys its own name, which means “herdsman”. The old state farm focused on sheep raising, and presumably the residents of Çarwadar still do.

Whilst doing my current routine of validating mapped areas, I came across what is potentially a significant time save. The mapper(s) had drawn an area around a large group of houses and labelled it as a “residential area”, instead of what I and I imagine many others currently do of mapping individual buildings.

This seems like a humongous time save in areas where the details of buildings (e.g. their name) are unknown. But I do have a feeling that ultimately one would want to map each building, as it would be helpful to know where the nearest hospital is, for example, rather than having to scour the area in an emergency.

A compromise could be to map unknown areas with these all-encompassing residential area squares, whilst filling in individual details for known buildings. I know that busy areas such as London and New York are already mapped out in great detail, so I can only assume that the time save I am proposing would just be the first step in mapping an area. If the idea is acceptable, I would then assume the idea would be used in the initial mapping stage, and that validators would fill in the details. That is, unless there is another step after the validation stage that I am unaware of (I am currently only an intermediate mapper and cannot validate all maps). I could also see the details being filled in during further iterations of the mapping process, such as when extra data on an area is gathered.

Thanks to Engin Gem, OpenStreetBrowser has a new translation (it was started today, so it’s still very basic): Turkish! Thanks a lot :-)

If you want to create or improve a translation, you can do so on OpenStreetBrowser Weblate.

Check the translation statistics.

I created 3 bookmarklets to load relations from WT and to load a relation from osm.org in WT

See osm.wiki/Waymarked_trails

I created these when I got tired of copy pasting the numbers over and over. I hope they will be of use to you.

Happy mapping of relations!

PS: I just updated this bookmarklet to support jumping from Google Maps: osm.wiki/Bookmarklet_JumpToOsm

Hi! 😃

Yesterday I worked on hiking routes in Sweden. I wonder how many there are? (“type:relation and route=hiking in sweden” gave me 70 mb of data which is a lot, but actually it would be more useful to measure how many kms of routes there are in comparison to say the area of the country)

I use JOSM and would like to praise and recommend the plugin relationtoolbox. It makes working with relations so much easier.

I probably should make a video about it if nobody beats me to it.

If you want to help you are very welcome, see osm.wiki/WikiProject_Sweden/Hiking_trails

I estimate that it will take me years to map, update and split up in parts as I keep finding missing routes, routes with no source, etc. 😅

My review of “The Red Atlas” has been posted online by Cartographic Perspectives. You may find it here: https://cartographicperspectives.org/index.php/journal/article/view/1589/1815

STATE OF THE MAP AFRICA CONFERENCE 2019 IVORY COAST MY EXPERIENCE The revolution of open data in Africa has come at the right time when most of the counties are at the pick of development and data is one of the tools that is helping in decision making and influencing the government and other organizations that use data in their activities. Data is been used in many ways in Africa some of the most prominent areas were data is been is in the area of health environment such as climate change, urban planning, etc.

If Africa has to develop there is a need to make sure that the ordinary people take a keen interest in Making extraordinary things. One of the extraordinary communities of people that are making a change in Africa is the OSM community. The data science in Africa has come at the right time because Africa is rapidly growing which means there must be people to understand what is happing and plan for the future and try by all means to overcome the challenges that are coming with the rapid growth of the African content.

… See full entry

On 21/12/2019 we had meeting with UniqueMappersTeam Uyo and other leaders of UniqueMappers across Nigeria.

Meeting time :9:30pm Meeting ID 755 993 243 Zoom

MEETING TOPICS

1.Introduction of attendees 2.Introduction of Leader of UniqueMappersTeam Uyo Mr Victor 3.OSM Community Structure 4.UniqueMappers-Uyo 5.Annuual OSMites Diary Record/Reports 6.Mappy Chrismas and UniqueMappers 2020 7.AOB

ATTENDANCE

*Victor N Sunday- Convener- leader UniqueMappers Nigeria *Knigsely Chukwu-LMTEnugu *Victor Ezeugwu- UniqueMappers Kogi *Victor -UniqueMappers Uyo *etc

The End with more passion to reach the un-reached across the country from 2020

For the last 4 days of mapping:

Day 9: I did some photo mapping based on Imagery I captured in December

Day 10: Went out surveying and checking out some notes.

Day 11: Used updated ESRI layer to add some buidlings and roads that’s just been build

Day 12: Continued from Day 11, added solar, gardens, parking, green spaces and trees

I finally figured out how to filter for thingies within, say, the province of Groningen, and to load everything into JOSM:
(this example extracts everything with operator starting in Biblionet; turns out that’s the public libraries operated by Biblionet Groningen)

[out:xml][timeout:90]; 
//{{geocodeArea:Netherlands}}->.searchArea;  // search within entity called Groningen (city) 
area[admin_level=4]["name"="Groningen"][boundary=administrative]->.searchArea; // specify: within province (admin_level=4) 
( 
  node[operator ~ '^Biblionet'](area.searchArea); 
); 
out meta;

Unclassified and residential highways within a place, say Ezinge, plus recursions up and down (partly from this link ):
(One lesson I learned the hard way: it’s dangerous to merge and/or split ways in that type of sparse editing. Do make sure to “download parent ways / relations” in JOSM, and still be careful! It’s very easy to break relations such as bus lines / routes)

[out:xml][timeout:90];
{{geocodeArea:Ezinge}}->.searchArea;  
(
  way[highway~"unclassified||residential"](area.searchArea);
  >;
);
(._;rel(bn););
(._;rel(bw););
(._;rel(br););
out meta;

Equivalently, but specifying that Ezinge is a ‘woonplaats’ rather than any random entity:

[out:xml][timeout:90];
area[admin_level=10]["name"="Ezinge"][boundary=administrative]->.searchArea; 
(
  way[highway~"unclassified||residential"](area.searchArea);
  >;
);
(._;rel(bn););
(._;rel(bw););
(._;rel(br););
out meta;

Useful (for me) admin levels within (ref):

… See full entry

I recently have been mapping the Chàm islands in Quảng Nam province, Việt Nam. The main island and some other ones (Hòn Lá; Hòn Cô; Hòn Cụ) - are now completely detailed, as there should now be no area left unmapped on them.

I also have been mapping in various places on the mainland, many roads are still missing. I would like to use data emitted by MapWithAi but their Fork of the iD editor is heavyweight (I prefer Josm) and I cannot easily use it, also because wiyh it every changeset has a limit of 50 ways. I am looking to find a way around this problem somehow.

For a while i have been working in hotosm ,project #4908 in Japan.Last July, 2018 heavy rain,floods and landslides happened in South West area of Japan.The people of the affected area had to face huge destruction. Now Japan Red Cross is working in this affected area Kurashiki/Sojya,Okayama.They ask support from others.They demand only building data. So if you have time,you can support them and can take part in humanitarian activities.

[hotosm(https://tasks.hotosm.org/project/4908#bottom)]

I am especially not good at dealing with image offsets.

My challenge is finding a close-enough to truth for certain locations. In absence of proper markers, what I will be using for reference consists now of the following:

1. The roundabout.
2. The lanes of the Trans-Canada highway as they meet Roberts.

For Bing imagery, this gives me an offset of 1.61, 1.53

Los Angeles

I’m documenting some seasonal 12 days of mapping on twitter

Alternatively, the thread can be viewed here on Thread Reader App

Another 4 days to go, probably on a new thread.

Sveiki,

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