Diary Entries in English

Recent diary entries

Computational Science

Posted by Mesfin Diro on 12 July 2017 in English (English)

Computational Science Program

College of Natural & Computational science

Graduate building, 7th floor

Addis Ababa University

Location: Kebena, Arat Kilo, Addis Ababa, 7821, Ethiopia

Start of #SweetsyDoha

Posted by Sweetsy on 11 July 2017 in English (English)

I started a hashtag of all the buildings I am outlining. I am getting the images from the DigitalGlobe Premium Imagery 'background'. I will add further information, where relevant, when I am on location.

I have noticed that currently Google Maps has a more up-to-date satellite of the area.

A not so bad method for interacting with the mailing lists on an as needed basis

Posted by maxerickson on 9 July 2017 in English (English)

Pretty easy, the mailto: links in the archives at, used with a reasonable client, maintain threading.

I'm using the support for Gmail that is built into Firefox. A couple clicks to set it up, find mailto on the about:preferences#applications page and select 'Use Gmail' from the dropdown list.

Statistics Canada and OSM building pilot project in Ottawa background.

Posted by Johnwhelan on 8 July 2017 in English (English)

The story actually goes back more than five years when it was realised that some Open Data was more Open than others because of licensing issues. The City of Ottawa gave its bus stops and some other information to Google in GTFS format. Because of the need to announce bus stops for improved accessibility all the bus stops were very accurately re-calibrated. This made the bus stops a very attractive high quality import but since the City of Ottawa’s Open Data license did not align with OSM it couldn’t be done but it provided the motivation to get the licenses sorted out.

The Canadian Treasury Board is responsible for standards and open data within federal government in Canada and they set about consulting with many would be users to come up with the 2.0 license. They have been working with a number of African governments on Open Data licensing by the way.

Once this license was in place Ottawa city council acted to ensure that all users had equal access to their data, ie bus stops, by releasing the data under a similar license and even that took a year or two to do.

Statistics Canada has a very different corporate culture than OSM and very early in the project a meeting / conference call was held with various players including Blake Girardot from HOT, Mojgan Jadidi, who had imported some Stats Canada data into OSM under the new 2.0 license and compared both carefully, and Tracey Lauriault, an Open Data specialist from Carlton University, who identified a building data set that the City of Ottawa owned completely. Other data sets were partially owned by various agencies such as MPAC who normally sold the data. That meeting changed the direction of the Stats Canada project, now it was to be an Open Data import with extra tagging by the public and that meant the local mappers had to both approve the import and be involved. In Ottawa local group of mappers meet up every few weeks, they were very supportive and held a number of meetings to discuss how they could help. In the end it was they who ran the import and handled much of the OSM discussion.

The City of Ottawa new Open Data license wasn’t formally approved for some time into the project. There was lengthy discussion in the Canadian community and with the import mailing list about the import, and eventually the questions about the license were referred to the legal working group who formally approved both the Federal Government 2.0 Open Data license and the City of Ottawa one. Mapbox were very supportive of the project providing a customised version of the iD editor.

It should be noted that normally handling both French and English or bilingualism can be a major problem for Canadian Federal Government departments. In this case OSM handles multiple languages very well both on the input side and on the display side, locally in Ottawa street names can be displayed in English or French and bilingualism was not a problem. Also the range of tools for entering data such as iD, JOSM, etc. meant the project was not committed to using one method of data entry.

One very significant part of the project was the use of R (, an Open Data statistical program, to analyse the data and this should provide a low cost tool for other parts of the world although as always training has its own costs.

Tagging bridge heights from open imagery

Posted by Richard on 7 July 2017 in English (English)

OpenStreetMap is navigable for bikes, on foot, and increasingly so for cars. But one thing we're not yet great at is truck routing.

HGVs, lorries, trucks, whatever you call them, need to get from A to B without breaking either the road or themselves. Which means the map needs to know about height and width restrictions. is a good example of what happens when truck drivers don't have this information (and also can't read):

OSM coverage is good in parts but patchy. Fortunately, the existence of open street-level imagery means it's really easy to map this sort of thing from the comfort of your own armchair. Here's a brief how-to.

Step 1: Identify low bridges

The majority of important restrictions are height restrictions, and the great majority of height restrictions are railway bridges. (There are a few canal aqueducts too, though canal-related restrictions are generally weight restrictions on overbridges.)

So one way to find potential low bridges is to follow a railway on the map, looking for instances where the railway crosses the road on a bridge, rather than the other way round (or a level crossing). Doing this systematically is pretty easy.

Or you can automate it with this clever maxheight map, which looks for exactly this scenario, and highlights the map accordingly. (Github code here.)

Step 2: Find height from imagery

You can use Mapillary or OpenStreetCam as open(-ish) equivalents of Google Street View. Here, for example, is a railway bridge captured on OpenStreetCam.

Personally I like to use Geograph, the long-running UK georeferenced photography project. You can go straight to Geograph itself, but I actually use my own bike route-planner,, which has Geograph photos integrated into it. First you plan a route under the bridge:

plan route

then you click the road, and 'View photos':

see photos

and hey presto, you can see there's a pic showing the height limit signage. Click that to see the full-resolution picture on Geograph.

There's even an (undocumented?) option to show Mapillary views directly in the OSM Maxheight Map:

Step 3: Map it!

Just split the road to create a short way underneath the bridge, and add a maxheight= tag. You can use imperial units without a space (maxheight=12'9") or metric with a space (maxheight=4.5 m).

The results

It's a really simple, straightforward process that makes the map instantly usable for truck routing. I fixed the bridges on the Cotswold Line railway (from Oxford to Worcester) in half an hour, from Geograph and personal knowledge. Greatly improving maxheight coverage in the UK should be doable in weeks rather than years. And, of course, it's a good excuse to get out and survey those places where the height isn't visible from imagery.

Once you've reviewed a whole railway, consider noting your work somewhere so that others can focus on other railways. I've started a wiki page for the UK at .

Declaration of professional relationships and potential conflicts of interest

Posted by Milli1201 on 6 July 2017 in English (English)

Dear HOT and OSM community,

I joined the HOT Board of Directors a couple of weeks ago and am now holding the position of the Board Secretary. As I am now also representing HOT and the HOT community, I put together this diary entry to explain my further professional relations and responsibilities.

Disaster Mapping and Management Department @ HeiGIT (GIScience Research Group Heidelberg University)

I am a Master student at the Geographical Institute of Heidelberg University and research assistant at the Disaster Mapping and Management department of the Heidelberg Institute for Geoinformation Technology. The objective of our department is to support humanitarian and disaster management organizations and volunteer communities through current technology, innovative methodologies and research, as well as through awareness building in our international research community. Therefore, the formal collaboration of the GIScience Research Group and Humanitarian OpenStreetMap Team includes collaborative work on tools and services, workflows, research, in teaching, and proposals, to support the objectives of the international Humanitarian OpenStreetMap Team community.

I am hereby not involved in any financial matters, my role is to rather build a bridge between the OSM/ HOT community, our department, and the GIScience research community in general. Apart from my work in the department, I also supported the NSF Eager Project on Crowdsourced Damage Assessment that was launched by HOT, Stanford Urban Resilience Initiative, GFDRR, and University of Boulder which I joined in a consultancy position for GIScience (Heidelberg University).

Missing Maps partnership with disastermappers heidelberg/ GIScience Research Group

Apart from being a student and research assistant at the GIScience Research Group, I am one of the founding members of the disastermappers heidelberg initiative. disastermappers as well as the GIScience Research Group have been supporting Missing Maps since the launch in 2014 and also became a formal partner of the project.
disastermappers/GIScience Research Group involvement in the project includes research, the development of applications and workflows as well as related teaching, the organization of mapathons and workshops, and joint proposals. I am hereby again not involved in any financial matters and abstain related discussions involving HOT and the GIScience Research Group, thereby following the conflict of interest guidelines of the Humanitarian OpenStreetMap Team and our department.

Better Walking Papers

Posted by Zverik on 5 July 2017 in English (English)

Walking papers from the Tula Mapping Party

I have talked publicly about improvements to walking papers since at least SotM 2013. Made a blog post here in 2014 with some thoughts. But all I've seen were new ways to print tiles or atlases. While I admire the Field Papers and MapOSMatic fork improvements over the past years, a good walking paper is more than that.

For a long time I have been using a 28-step process to prepare walking papers for my mapping parties. It involved using Maperitive, Inkscape and some proprietary software. This year I finally got fed up with reanimating that old renderer, which doesn't work perfectly on Linux, and tried something else. I had always been recommending QGIS for printing maps, and I decided to try it myself. Turned out, making walking papers with it is really simple and straightforward, albeit not without issues.

I started writing another guide with QGIS and GDAL and all the new tech, but it quickly grew to 22 steps. Still too many. Having discovered the Python Console in QGIS, I started experimenting with automating a few tasks. One thing after another, and now I have automated almost everything, fixing a few issues in QGIS on the way. I present to you...

QGIS with a Walking Papers popup menu opened

Walking Papers QGIS Plugin

It is the simplest way to prepare good walking papers for your mapping party. All you have to do is sketch the pie, and the plugin does the rest. Here are the complete instructions:

  1. Install the "Walking Papers" plugin from the official QGIS repository.
  2. Click the button with blue rectangles and choose "Download OSM Data".
  3. On a layer it created draw a polygon around your mapping party area (click a pencil button, and then "area" something near it. Left mouse button adds a node, right button closes the area), and choose the same menu item again.
  4. Yay, we've got a map. Sketch the pie with lines in the "Pie Overview" layer.
  5. Having finalized the pie, activate the "Pie Sheets" layer and draw areas around quarters that go on each of the printed sheets. Usually it's 2-3 sheets per a pie piece. Name areas like "4-west", where 4 is a pie piece number, and "west" helps a mapper to locate themselves.
  6. Click the blue rectangles button and choose "Prepare Atlas". That's all, check out the sheets and print them or export them to a PDF file.

Amazing, right? For a regular mapping party this way of preparing walking papers gives you much more control, and you would need to do much less explaining when handing these sheets to participants. Here is why I prefer it to atlas-printing websites:

  • The data is very recent. It is downloaded from Overpass API, and you don't have to wait for a server somewhere to catch up. Buildings missing? Ask mappers to help drawing them, and print the papers an hour before the party, with everything they managed to draw by that time.
  • Custom map style. With online services you have basically one good choice: Stamen's Toner. It is not perfect for walking papers: labels are in English, lines are too thick and dark, buildings don't have numbers and are hatched, so you can't draw anything on top of them, and the water is awfully black.
  • Vector maps. You are not limited by zoom levels, and thickness is specified in millimeters, not pixels on some maximum zoom level.
  • Custom attributes. The bundled style prints house numbers and building heights on buildings. It is not easy to alter that at the moment, but by manually editing osmconf.ini and wp_style.yaml files in the plugin directory ($HOME/.qgis2/python/plugins/walking_papers) you can add any attributes and change the style however you want.
  • Rotation. It is frustrating when the roads in your mapping area go in 45° angle on the map, which makes most of the space on walking papers sheets unusable. With this plugin, maps on your sheets are rotated so objects on the map are as big as possible, and you have plenty of space to put down POI names and house details.
  • Speed. No more waiting for an hour while your task crawls through the queue. Click a button, get an atlas, that's all.
  • Works offline. Download a map area in JOSM beforehand, or copy it with a flash drive from a connected computer, and use the "Open OSM Data" menu item.

I hope this plugin helps you with organizing a mapping party. We know these don't help with attracting new contributors, but parties are fun, you get to know your city or village better, and the amount of data you collect is unmatchable by any other data collection method.

Bookmarklet OSM <--> Mapillary to rapidly switch between the two

Posted by Romainbou on 4 July 2017 in English (English)

Hi all, I just adapted an OSM <--> Google Maps bookmarklet made by The_Knife, into OSM <--> Mapillary.

I find the Mapillary integration into iD quite usefull of course, but having everything drawn on the same window makes the whole thing very messy and hard to read. I always ended by opening a new tab for Mapillary navigation, and staying with a clear OSM window to work on.

The bookmarklet just open a new tab at the exact same place and zoom, in the other service, in both ways osm->mapillary and mapillary-osm.

So you just have to create a new bookmark in your favorite browser, and copy-paste the text below as the url field :

javascript:(function(){params=location.href.match(/\d{1,2})\/(-?\d{1,3}.\d+)\/(-?\d{1,3}.\d+)/); if(params!=null){""+params[2]+"&lng="+params[3]+"&z="+params[1]);}else{params=location.href.match(/www\.mapillary\.com\/app\/.+lat=(-?\d{1,2}\.\d+)&lng=(-?\d{1,2}\.\d+)&z=(\d{1,2}\.?\d)/); if(params!=null){ z=params[3];""+Math.round(z)+"/"+params[1]+"/"+params[2]);}else{ alert("OpenStreetMap - Mapillary impossible");}}})()*

Here is the wiki page of the bookmarklet : Bookmarklet OSM-Mapillary

PS : the OSM <--> Google Maps bookmarklet can be found here and is extremelly useful. The_Knife also made a one way "->OSM" version of his bookmarklet, that is compatible with more url types : 0/0.000/0.000 or zoom=0&lat=0.000&lon=0.000 (can be in an other order and not in a straight string !)
And there is also a huge bookmarklet, MapJumper, that seems to allow switching between OSM and 35 other services, but I didn't see mapillary in the list!


edit : Philipc enhanced the code today and I updated the text of the code written on this article accordingly.

10 years in OSM

Posted by Ambush on 4 July 2017 in English (English)

Hi osmers,

Today is my 10 year anniversary in OpenStreetMaps. Congratulations are accepted.


Providing translations of changeset comments to other Philippine languages, aside from English and Filipino/Tagalog

Posted by TagaSanPedroAko on 4 July 2017 in English (English)

While I will be starting using changesets in Tagalog, sometimes along with English, I started providing a translation of a changeset comment to another regional language, for example, Cebuano, when doing an edit in a specific area in the Philippines where it is the dominant language. While translations to Cebuano can be easily provided through Google Translate, this is something that is problematic with other regional languages, like Ilocano, Bicolano, Hiligaynon, Waray, Chavacano, etc., as a possible translator may not be reliable enough to provide a grammatically correct translation that a local can understand. Are there any possible reliable online translators for other Philippine languages, like for those I pointed above?

New cycleway on Cambridge Terrace, Christchurch NZ

Posted by Adam Heinz on 4 July 2017 in English (English)

Went for a stroll with OSM Tracker down Cambridge Terrace to check out the new path for pedestrians and cyclists, created as part of the Accessible City plan.

The GPS trace can be found here

Developments on southwestern barangays of San Pedro, Laguna

Posted by TagaSanPedroAko on 4 July 2017 in English (English)

It was since January 2016 when I requested to map the less mapped barangays in southwest San Pedro, Laguna, which includes Magsaysay, United Bayanihan, Riverside, Laram, and Langgam. But, now, this effort now came to fruition.

From July 2016, after doing ground mapping after visiting Langgam, the less mapped areas of San Pedro, Laguna, finally has grown. Several POIs have been added, plus street names. The main priority is the important POIs, like schools, barangay halls, and churches. I have uploaded a GPX track as a guide when someone wants to realign the roads there, that are traced from aerial imagery, that may be offset.

Here are some POIs added on the survey:

  • Divine Gift School
  • Vian Rechel Academy
  • IETI
  • The Church of Jesus Christ of Latter-day Saints
  • 7-Eleven (Magsaysay branch)
  • San Pedro Relocation Area Cooperative
  • United Bayanihan Community Church
  • Alfamart (United Bayanihan branch)
  • Ministop (United Bayanihan branch)
  • Polytechnic University of the Philippines - San Pedro Campus
  • Laguna Relocation Community School
  • Upper Villages Christian Academy
  • Laram Barangay Hall
  • Most Holy Name of Jesus Parish
  • United Montessorean School of San Pedro (Langgam campus)
  • Jesus the Faithful Savior Christian School

Yet, several POIs and street names found on the survey are still not mapped, but can be mapped on following changesets. An update on the OSM Wiki page for San Pedro, Laguna provides all mapping updates (with dates for tracking latest updates). And for other POIs not found on the survey, I leave it to the other users (especially locals) to map, or note for others to resolve. The POIs added may start increased efforts to map the least mapped barangays of San Pedro.


Posted by cugrassroots on 4 July 2017 in English (English)

Hello! It seems others have used the user diaries as a means of introduction before, so I thought I would do the same, especially since getting involved with OSM for me is in support of a broader research project.

I’m a doctoral candidate in Communications and Media with the Institute of Communications Research at the University of Illinois at Urbana-Champaign, and I’m interested in the evolution of location-aware projects in alternative media, particularly with the emergence of grassroots forms of mapping in mind. My dissertation thus relates to the political, cognitive, cultural, and social implications of digital mapping and increasingly available location-aware media technologies, and looks at alternative projects to learn more about the current state of digital mapping.

So, as I go about my dissertation research, I’ll be reviewing the community’s work, contributing through edits, and participating in mapping events. In writing up findings from this research, personal identifiers will not be published or presented - no such information (including usernames) will be included that would reveal any user’s identity in any results of the research.

Please don’t hesitate to message me if you wish to learn more. Thanks for reading, and I’m looking forward to contributing and learning more about the community’s work!

Visapur Hiking Route

Posted by Saikat Maiti on 3 July 2017 in English (English)

Visapur fort is a very famous place for hiking in monsoon. This fort was built by Balaji Viswanath. There is a possibility for hikers to miss the actual trail for this spot. Alt text There is a very tiny instruction for hikers to follow the path. After this left turn hikers need to follow the arrow sign to reach this beautiful spot. Previously this route was mapped by a straight path from top to bottom. I made some correction using GPS track. Alt text Alt text

Location: Mumbai-Pune Expressway, Malavli, Pune, Maharashtra, India

OSM Node Density – 2017

Posted by tyr_asd on 2 July 2017 in English (English)

The latest installation of my yearly osm node density visualization is now online: shows the freshest data from mid 2017 (while the results from previous years starting with 2014 are also available on the site's layer selection menu).

Can you guess where the following example screenshot was taken?

Click here to find out.

Using NCDR evaulated center Data to Add Missing School

Posted by Supaplex on 2 July 2017 in English (English)

Due to preparing for disaster situation, NCDR maintain a list of evaluated center in Taiwan. Some of these places are school. We could use this list and filter school, check if these schools are on OpenStreetMap. If there are missing schools on OpenStreetMap, we could draw the schools. Schools on NCDR data has much more items than GNS data.

This has been generated by the overpass-turbo wizard.
The original search was:
“emergency=access_point and name~"國小|國中|高中"”
[out:xml]/*fixed by auto repair*/[timeout:225];
// gather results
  // query part for: “emergency=assembly_point and name~/國小|國中/”
// print results
out meta;/*fixed by auto repair*/
out meta qt;/*fixed by auto repair*/

OverPass Turbo Link

Location: 106, 中湖里, Fenliao, Linkou District, New Taipei, Taiwan

Sunday drive

Posted by apm-wa on 2 July 2017 in English (English)

Ann and I explored the neighborhood around Duşanbe köçesi this afternoon as the new satellite imagery and map as drawn did not correlate. Collected some good ground-level imagery with Mapillary and good GPS traces with the Garmin navigator, and updated the map in that neighborhood. Also located (and added) the Border Service Institute and the mineral water sanitorium in Berzengi, location of both of which had been minor mysteries!

We keep adding bus stops, thanks to Mapillary, and at some point I hope somebody will help with including data on bus routes.

We finished with a visit to the Watutin (Vatutin) Cemetery, where we geolocated two significant monuments, to the composer Nury Halmamedow and the physician cum Sanskrit scholar Boris Smirnov, who translated the Mahabharata into Russian.

I am increasingly more impressed with Mapillary than with OpenStreetCam. It works with with ID, its base map is kept updated (OpenStreetCam's is woefully out of date), and it does not try to force traces to align with existing highways in OSM, leading to greater accuracy.

Deriving smaller multipolygons from larger ones

Posted by Robert Copithorne on 1 July 2017 in English (English)

Recent discussion on breaking up multipolygons in to smaller units. Note that the original polygon contains many members. The objective was to show the original land use of an area adjacent to, and draining into, the Alberni Inlet as a natural wood (forest), then break the area in to smaller units based on the nature of the tenure. The tenure in most cases sets the major purpose of the land use.

The initial comment could be based on my saving a session with a number of errors which I intend to correct through the work to be done on setting smaller units, as described below.

Comment from (OSM contributor) about 6 hours ago

Do you know what you are doing?
Comment from Robert Copithorne about 3 hours ago

Hello. Yes, I believe I am doing what is required, but I am aware that I created a big potential problem for myself when I created a very large complex multipolygon related to land use in Alberni land areas. Things became more difficult when I started to break the large multipolygon in to smaller pieces; specifically portions related to Strathcona Park, and Western Forest Products operations at Great Central Lake. Currently I face a large task of separating the elements of the three multipolygons, but I am working on that, and I believe will be able to straighten it out.. Any suggestions you may have at this point that would help to reduce the work involved would be appreciated.

Comments from other users relevant to the issue of splitting multipolygons in to smaller units would be appreciated.

Additional Info: Having worked in Forestry in areas around Port Alberni, including updating Forest Inventory maps, I am intensely interested in developing a map of land uses, features and access roads in the Alberni Inlet drainage area, and adjacent areas, for the benefit of all users.

Location: Cameron Heights, Alberni, Port Alberni, Alberni-Clayoquot Regional District, British Columbia, V9Y4G1, Canada


Posted by agustina123 on 30 June 2017 in English (English)


Location: Komplek STPP, Pasir Buncir, West Java, Indonesia

[TBCL]OSM activities in Japan, July 2017

Posted by muramototomoya on 29 June 2017 in English (English)


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