Recent diary entries
It's London Tree Week. I saw someone tweeting at OSMLondon asking "Can you help identify tree named pubs In London?". Why yes I believe we can! We've always specialised in pubs. We even used to have a tree named pub "The Mulberry Bush" as one of our OSMLondon regulars.
This seemed like fun, so I went ahead and did it. Here's the tree-named pubs of London on a map.
I found that to be the easiest way to do it, having done similar things before (This old blog post describes similar osmosis/osmconvert steps for example) ...but there's probably many different much easier ways of pulling up a map of tree-named pubs in London (or at least getting as far as the csv output). So that's an exercise for the reader.
I'm quite sure we should be able to do a single Overpass API query to get the pubs of London (as centroids for ways).
I once saw a talk by people from Tableau (GIS software) Visualising the Great British Pub with OpenStreetMap data and Tableau which was all about mapping pub names. They could get it done that way for sure.
Pub names are always fun, but we should probably look to do something more directly related to London Tree Week. We have a lot of trees mapped in London. Maybe we should visualise this. Make a dedicated tree mapping app or something. No doubt London's tree data is still skewed towards Southwark where we've got them all imported. Tree mapping party anyone?
Five years ago I created an Amazon.de affiliate account for OSM. I was unable to make other people do this so I had to do it myself. :)
I had not made any calculations beforehand and thus no clue what to expect. So I cannot say I am surprised but nevertheless I was quite pleased by the amount of money coming in. I want to thank everybody who used and spread this possibility to generate some money in the name of OSM. In these five years they:
- bought nearly 7000 products on Amazon.de
- thus creating nearly 200.000 EUR sales figures for Amazon.de and so
- generated nearly 10.000 EUR affiliate fee for OSM.
Even when people criticize Amazon I want to repeat my earlier statement that if you want to buy or even live completely correct regarding politics and environment you had to go back to your own farm. Just think of BSE, the various meat scandals, the cease-and-desist-orders of Wolfskin against bloggers, the logging of the rain forest for palm oil and McDonalds meat and the exhaust fume fraud of several car producers: nearly every consumer makes compromises while shopping (consciuosly or unconsciously). So I hope that environmentally aware persons won't criticise people shoping at Amazon and vice versa.
My self-chosen task of managing the affiliate account I recently handed over to Frederik Ramm, the treasurer of the FOSSGIS e.V. Because of this I don't have exact numbers of the last months but interpolated them from the months if the last years.
It is a pity that the mapper colleagues on the other site of the great pond don't make use of the account I created on amazon.com. I lack the needed American bank account to do so myself.
I have been mapping my home town of Gudivada. This is where I grew up and did all my schooling. In the Telugu language, "Gudi" means temple, and "vada" means a settlement or a town - Gudivada has many Hindu temples.
When I decided to map, I expected that since this is a small town there would just be a node with a name, and not much else. I was wrong though - trunk, primary, secondary, and tertiary roads along with many points of interests and buildings around the center had been well mapped, thanks to the active OpenStreetMap community.
I focused my efforts on mapping residential streets, and adding places like hospitals, temples and schools I was certain about.
Before and after
Here are the residential roads I added within Gudivada. A number of features such as water bodies, public water tanks, school names and area names which I have added most recently are not visible in the 'after' gif due to OpenStreetMap not rendering those objects at that zoom level.
Closeup of my edits
Here is a closeup of my edits in my hometown. One issue I encountered was not being 100% sure about road names so refrained from adding local names to the roads. For example, as I was mapping, I came across "Eluru Road" which goes across the town - my hunch is that this road has a different official name.
What I added and modified:
- Missing residential roads were added
- Re-classified many roads to Tertiary roads based on road classification documentation
- Added places like schools, school grounds, property boundaries, water bodies, places of worship, stadium and other amenities.
- Misaligned roads
- Added amenities for existing buildings
I've enjoyed mapping my hometown and added numerous features which I am intimately aware of. My plan is to add more details based on satellite imagery and local knowledge, and do a field survey the next time I visit to ground-truth Gudivada data on OpenStreetMap.
I'd also welcome any comments others in the community have to improve what I've mapped, or tips for mapping.
Pilani is my college town set in the Jhunjhunu district of Rajasthan, India. With a population of less than 30,000, it's one of the more quieter towns of the North. Being close to the desert, the weather here gets pretty wild: from summers rising up to a scorching 50 degrees Celsius, to frozen winters with the mercury hitting sub-zero.
In the middle of this quiet desert town is BITS Pilani -- a bustling engineering and science institute established in mid-60s. Between 2009 and 2014, I spent my time here, working through my engineering degree.
The first thing anyone would notice about BITS is it's beautifully designed campus. A clear visual line runs across the center, starting from the BITS tower up to the Saraswati temple. Low rise buildings on the side serve as hostels, academic buildings, libraries and student workshops. A circular rotunda below the tower leads to the new constructed academic buildings (built below the ground level to conserve space). Trees of various sorts line up the roads and gardens. Over 100 different species of birds make the campus their home.
Photo credit: Alok Pacholi
Before I started mapping, the buildings and roads within the campus had already been pretty well mapped by maheshrkm. So I focused on adding more detail to some of the landmarks within the campus and tracing the surrounding town.
The town itself, though small, is pretty dense. It's tight, winding streets and crowded clusters of buildings make the tracing difficult. I added some major roads, buildings, water bodies, and local points of interest like temples and bus stands.
Here's a screenshot of some my edits:
My favourite part by far has been tracing Shiv Ganga. It's a beautifully designed circular lawn surrounded by a canal. The lawn is built out of circular sectors, has a statue of the deity Shiva and a footpath.
It renders beautifully as a 3D map in F4map's demo.
Being my first mapping experience, this has been pretty enjoyable. A special thanks to planemad for improving some of my edits. If you have any feedback or corrections for me, please feel free to leave me a comment. Thanks!
A good deal of my Diaries seems to be one long, continuous set of brick porn as I detail my affaires with various walls positioned in different parts of St Anns, Nottingham, England. Sadly, today is no different. Witness your surveyor as he gets up close & personal with the tattoo on a wall next to (what used to be) Thorneywood Station.
I began surveying Honeywood Estate last Sunday 22 May. The estate (and particularly at the upper end) is sat within the site of the former Thorneywood Brickworks (Nottingham Patent Brick Company). Robert Mellors, the owner of the Brickworks in the 1880s, was anxious to get access to a railway as to be able to ship his bricks to all parts of Britain. He was therefore one of the instigators of the Nottingham Suburban Railway (NSR) (I believe that St Pancras Station in London is made from Thorneywood brick).
Here is a picture of the rear of the New Engine House Pub:
Jim, the last Brickyard worker left living within Honeywood Estate, and who I met via an introduction within the pub, told me that the pub was built around the Engine that was used by the Brickyard to pull wagons from Thorneywood Station up the hill to the yard. That Engine was a horizontal steam engine made by Tangyes, of Birmingham in 1850 and bought 2nd-hand by the Brickworks in 1867 from a Nottingham Colliery (Thorneywood Station was opened in 1889). 100 years later the pub opened up with the Steam Engine in a glass cabinet in the Lounge. Later, when the Brewery decided to refurbish the pub, it donated the Engine to the Nottingham Industrial Museum at Wollaton Park.
The original location of the Brickworks was likely to have been just within the southern-most fringe of the legendary Sherwood Forest, which itself was surrounded by fields, and just a mile or two from the walls of Nottingham town.
All this part (NG3) of Nottingham land is composed of alternating horizontal layers of clay & sandstone, and continues like that right up to Nottingham Castle. An aeon or two ago, this part of England was a few miles offshore from a large river within a much warmer climate. Alluvial clay from the river settled upon the sand beneath. The clay was impervious to water & marvellous for making bricks, whilst the sandstone was a perfect pot for rainwater; streams poured forth from wells both natural & man-made.
The surface of the land fell as the Brickyard workers dug with their shovels into the side of the hill. The NSR & Thorneywood Station were established because folks with money were finally pouring out of Nottingham & into Thorneywood & St Anns. That also meant that roads were being built all around the Brickyard, and houses being built along those roads (many built of Thorneywood brick, of course). It happened with remarkable speed: the brickyard was no longer in a rural location, but was within the suburbs.
The hill could not withstand the Brickyard shovels, but the Brickyard could not overcome those new houses.
My surveying followed the course of those workers as they dug away at the hill, and also turned around at the same points. Honeywood Estate is surrounded by a 30 foot / 9m hill on two sides (Standhill Road & Cherrywood Gardens) and by rising hills on the other two sides (Carlton Hill & Porchester Road). Here is a view of the quarry wall at the west side:
Porchester Road is just beyond the trees at the top, whilst the entrance to Cherrywood Gardens is a little further up Porchester on the right.
Here is an east side view (shot halfway up the hill at the The Brickyard Work Out) (that is “Life on the Edge”, an interesting house built in 1913 on Standhill Road, in the background):
Another view of the back of the estate quarry wall, shot from near the top of Brick Kiln Way (a footpath that runs from the base of the estate to Standhill Road) (the building at the top is “Life on the Edge” again):
Finally, this a view of the south-side of the quarry face:
Carlton Hill is a little beyond the trees at the top, with the entrance to Standhill Road a little further beyond on the left.
To complete this circumnavigation we need to look at my original focus of interest:— just where exactly is/was the Porchester tunnel that allowed goods wagons from Thorneywood Station to pass under Porchester Road (at the lowest point of the whole estate) and to be pulled by ropes up the hill to Thorneywood Brickworks?
This is a 1952 photo from the Thorneywood Station page of disused-stations.org.uk:
At front left is the 1889 blue-brick wall that served as a base for the Coopers Arms pub. Here is the top 2m of that same wall in the garden at the rear of the house of a lovely couple of folks that were charitable enough to let me photograph it:
On the other side of the fence above is the old Cooper Arms public-house (now a hostel). You can also see The Station-House beyond & also on the 1952 photo.
Notice that the bricks in this astonishing 1889 wall are of Tamworth Blue Brick. The wall turns a corner to the left near the far right-hand-side of this photo and, shortly before it leaves the garden, one of the coping stones is imprinted with the mark of it’s maker:
Hathern Brick Cº, Tamworth, Staffordshire. These are 1ₛₜ quality Engineering Brick: virtually water impervious, hard as rock, almost vitreous in nature. I got an insight from Jim into these bricks. He described rare occasions in which bricks being cooked may turn “jelly” in the kiln and begin to topple; any nearby workers would need to leg it to survive. Blue Brick are cooked at the highest temperature to gain their qualities.
I was also a touch naïve; I thought that the colour came from the heat at which they were cooked. Of course not. It is a question of the tints and/or glazes applied to the surface of the brick that gives it it’s colour.
Returning to the 1952 photo above: just beyond the wall on the left is a spur-siding below the Station-masters’ House. The track runs to the left through a tunnel under the modern Porchester Road (then called “Thorneywood Road”) and on up through the modern Honeywood Estate to the Thorneywood Brickworks. One rather odd thing is that I can trace little information & photos of this particular tunnel at either end. However, I now am sure of the location of the western end.
This is the only photo that I’ve been able to find of the Porchester tunnel that led to the brickworks (the link also contains photos of the Engine & maps of the tunnel):
The location is below the extension of that wall. It is just beyond the southern boundary of the Coopers Arms, in the rear of a house in Len Maynard Court, and I am going to have to visit yet another home-owner & beg to take a photo (Tue update: I called at tea-time & after confirming that the tunnel entrance was in her garden, and my asking to be able to photograph it, she said ‘I'm eating, come back later’ so I went back today & she said ‘no’).
Rather than ending on such a negative, here is a rather good view I found today (Tuesday 31 May) from Porchester Road whilst surveying the final houses on the Honeywood Estate:
My back is to Wheatfields Road in this picture. It shows the drive up from Claygate at the bottom to The M.A.D.D. College at the top in the distance (the passage is not actually possible due to a swing barrier at bottom & top, a feature that keeps defeating taxi drivers using Sat Navs based on OS Maps!).
Just a quick hello to all you folks out there making a wonderful project. I can't believe how well this project has been going.
This is a greetings from Australia to the rest of the world, and of course, those of us who are here too.
I'm mainly editing and adding in things which I know of, and am using sources that aren't copyright for other areas. I have extensive knowledge of a few areas, and a few subjects at that, but I would also enjoy some feedback from fellow users.
I've just joined, and am currently working on introducing the kingdom halls into the maps where they exist, as well as some of the local businesses that I've been in contact with (local can mean sometime where I was there), and other necessary points of interest when something isn't known.
Looking forward to hearing from you, and seeing this project grow even MORE!!!
I've spent the week sparing with Java layout managers and Swing components, but at least I have something to show for it. Here are two of the finished dialog boxes, fairly simple as far as purpose, the first one is where most of the meat of what I'm doing is. This dialog will allow users to specify settings for what I'm adding, with different settings for Image exporting and previewing in the viewer. This dialog is pretty self explanatory, it leads into the next thing I did this week...
After talking with Tordanik and Basti I decided to flip my first two goals around, tackling the lighting first. It was a good decision, I was able to do all of the work without diving too far into the shader code. The gif above is 23 separate renders all taken an hour apart. There are still some colors I want to tweak, and right now the color of the lighting is a hard cut off between day, sunset, and night. I want to implement a gentler transition, mostly likely just by adding more steps to the lookup table. If I find some time, I may come back and try and implement some sun effects with shaders (atmospheric scattering, glare/lens flare) but for now a fixed color transition provides the effect I was aiming for.
The direction of the shadows is actually calculated based on the latitude and longitude of the location. The calculations follow the wikipedia page, its a bit of a fun exercise in trigonometry.
This is a summary of a few key topics from the OSM-Colorado Meetup yesterday. I was really excited to have this handful of folks together; it felt more like an ‘OSM super group’ meeting than any of the meetups I have organized; reminded me of some of the early OSM-Colorado events I attended back in 2010-2011. Although I think we all had some kind of mobile device/laptop/etc. no one ‘fired anything up for show and tell’ but instead we really just had a great time hashing-out some of the major issues and opportunities around OpenStreetMap in Colorado, USA.
One of the most significant items is a wonderful opportunity to work directly with the Denver Regional Council of Governments to explore importing a huge volume of data that they have purchased and are releasing as Public Domain. We are still very much in the ‘exploratory’ stage, and have started a wiki-page. There are so many ‘side-topics’ that come up with this discussion: how to conflate with existing data, perform import(s) when/where appropriate, make it community driven, frequency that the data will be updated, how to maintain and update when there is need, and a whole lot more. Stay tuned to that page and/or the import mailing list as we begin to ramp up the effort.
We also discussed this year’s MapCamp! – Poudre Canyon. The High Park Fire in 2012 and Floods in 2013 reeked some havoc in and around Poudre Canyon, so although I have been told that some of the camping/recreation is still closed; I think it’s an even better reason to ‘head up north’ so we can do some surveying and get OSM up-to-date with the changes caused by those incidents. However, we might be looking further ‘up the canyon’ towards Cameron Pass or maybe Pingree Park area for camping. We also discussed timing and it seems like mid-August is what we are looking at (i.e. between SotM-US and SotM-International, but before it starts getting cold up high; and June seemed pretty full already for most of us).
Outside of those two ‘major topics’, we generally discussed what people want to see out of the meetup group; types of events, etc. We have some great ‘competition’/friends in Colorado, like GeoSpatial Amateurs, MapTime! Chapters in Boulder and Denver/MileHigh, and tons of other mapping/GIS/Coding/etc. groups; so we really want to ‘find our niche’ and not ‘step on toes’ with other groups. In my opinion that means focusing more on mapping and data collection versus presentations; also sticking fairly strictly to ‘just’ OSM versus more general mapping platforms and applications fairly well covered in the other groups.
We also discussed some of the more ‘interesting’/controversial things like the tagging of National Forests/Parks/Monuments/etc. It seemed a general agreement that boundary=protected_area with appropriate protect_class=* is the better tagging schema; but there is reluctance to make this wide-scale change as we understand this is not rendered yet. So with the folks on hand, this and several other of our conversations went pretty deep into how all these things work and are related. I talked about my favorite OSM feature, South Park (the real geographic feature vs. cartoon town) and how the conversation on talk-us spurred some motivation in me to further work on the natural features (forest and grassland mostly) around me – which I started years ago, but there’s a lot of forest around here :)
All and all, it was a great meetup and I think the momentum around OSM in general is fueling a renewed desire to make OSM-Colorado one of the most active ‘micro-chapters’ in the United States. Please feel free to join us!
Welcome to Yelahanka
13.1N , 77.5E (degrees)
I reside in a place called Judicial Layout near Yelahanka, which is ~21 km north to the Bangalore city. It is skirted by two beautiful campuses namely, the University of Agricultural Science and the Central Institute of Medicinal and Aromatic Plants, making it a perfect escape from the otherwise concrete jungle. Source: Skyscrapercity
Status prior to my mapping task:
Most of the basic amenities and road networks in and around my residence is already on OSM.
I tried to focus on two major aspects:
- Checking for the correctness of the already existing edits.
- Adding features that were overlooked.
List of features that I tried including into the OSM:
- Tagging my home, adding street names, clinics, agricultural fields, eatery, parks and buildings.
- Tried to amend spatial extent of a lake and fixing roads that were misaligned.
- Contacted a local mapper in my area and attempted to resolve a note.
The idea of adding spatial information to a map has always excited me. I really enjoyed my time mapping!!
What could be improved
Supplementing mappers with finer resolution satellite imagery.
Thanks for visiting Yelahanka!! Hope your navigation was smooth with most of the edits in place.
This blog was originally posted in the Blog from Improve-OSM, if you want to see the complete Blog please click http://blog.improve-osm.org/en/happy-mapping-hour-presentation-import-project-inegi-mgn-national-geostatistical-reference/
Last April 6th 100% of the Mexico Telenav’s team (Andrés Ortiz 50% and Miriam Gonzalez 50% 😀 ) presented the results of Import Project INEGI National Geostatistical Framework. The meeting point was the Felina bar on the edge of Condesa and Escandon neighborhood.
Andres_presentando Miriam_presenta Image by @Tlacoyodefrijol More than 20 people booked and came to the appointment. The project was originally announced in May 2015 with much skepticism because this was the first time a project of such magnitude was taking place in Mexico and the OpenStreetMap community in Mexico at that time was very disperse.
Before_import Image by Ruben @Mapbox Many import projects have been conducted in many parts of the world, such projects have helped (mostly) to create the map of the world that we have today and Mexico was going to be part of them. People with extensive knowledge in imports formed part of the project including Victor Ramirez, Ernesto Carreras, contributors od OpenStreetMap Puerto Rico and Rafael Avila, a HOTOSM collaborator and expert in African countries imports. At the beginning of the project we realized that there were only 69 valid administrative boundaries (although in the image it looks more than 69, these lacked the tag SOURCE which made them invalids) and the end of the Import project the team had added 2,457 administrative boundaries with tag Source = INEGI MGN 2014 v6.2
After_Import Image by Ruben @Mapbox To the #HappyMappingHour diverse OSM contributors atended such as geographers, developers, archeologists and also Armando Aguiar – INEGI IT Services Director witnessed how the Open Data Inegi released at the end of 2014 has been in benefit of OpenStreetMap. Let me share some statistics:
Node numbers/Ways/ Deleted relations
500K / 2k / 500 Node numbers/ Ways / Added relations
1000K / ~4k / ~1050 Number of hours dedicated :
250+ NUmber of administrative boundaries added:
Now that the map has de MGN boundaries as a reference mappers as Irk_Ley have been investigating the local laws of the states of Veracruz and have been reviewing historical maps of the Map Library Manuel Orozco. These mappers will be verifying and correcting those limits which have differences with the MGN when they have the backup of the documentation of the local law.
Here you will find the presentation of #HappyMappingHour and if you want more technical details we suggest you check the following blogs and the wiki.
Blog-Process used to import more tha half of the municipalities in Mexico Blog-How we imported Administrative Boundaries for Mexico from INEGI Wiki- Mexico’s Administrative Divisions Import Project Here also you will find two Blogs from collaborators in the Import Project:
Blog: My experience in OSM during the MGN Import by Pablo Garcia (OSM user: Irk Ley)
Blog: Import of INEGI Mexico municipalities finished by Andres Ortiz (OSM user: Andresuco)
You can contact them directly if you have any questions or comments for them.
What are the next challenges?
Evaluate data from the National Road Network and create a joint project with Mexico OpenStreetMap community to carry out its import. It is also in the radar create a tool where information from OpenStreetMap in Mexico is a kind of “inspector” to send feedback to INEGI about possible shortcomings or errors can be corrected and improved thanks to contributors OpenStreetMap but first we need more discussions with the local community.
Note: For having complete access to the links from the technical Blogs and download the presentation click http://blog.improve-osm.org/en/happy-mapping-hour-presentation-import-project-inegi-mgn-national-geostatistical-reference/
Hello OSM community, this would be my 2nd diary post for my Summer of code project. Do checkout my first blog post where I introduce myself and the project I will be working on.
This week would be the last week in the community bonding process. All the GSoC students would receive their first stipend at the end of this week. Hurray !!!!
I believe my community bonding is going well. This week I was mostly busy with adding mapillary-js to iD. Thanks to the awesome work by Peter Neubaur, we have a PR ready to implement this feature to iD.
If you use iD editor you will find that the mapillary images are static and don't have navigation buttons.
To have this feature, we would need mapillary-js in iD's source code. This library gives the developers powerful new ways to interact with mapillary ecosystem. But this was easier said than done. Peter helped us with setting up the basic work required for the inclusion of this library.
The major problem which I was aiming to solve was the asynchronous loading of images by the mapillary-js. If you quickly click on multiple points, the system suddenly enters into chaos. The point highlighted and the current image no longer tally. The following screen cast should do justice in depicting this situation.
To fix this problem, without messing up the code of mapillary-js, I added a variable which keeps track of the last point clicked on by the user whenever mapillary-js goes into loading mode. This allows me to do cool things like show loading and keep the system stable and predictable. After fixing this here is the screen cast showcasing the awesome blip.
So this was all about mapillary-js and its humble addition to iD. Apart from that iD is soon going to get this huge internal makeover by splitting the code into modules. Now, this is an architectural shift. Doing this will make way for easy development of iD. Head over to this ticket for any updates regarding this.
Why is it impossible to report spam in these diaries? A simple ‘report me’ link would do it.
Here are the latest examples (just in the last hour - all Chinese, naturally):—
Added 10:49 UTC 01:00:
I ran a website for 10+ years and am a moderator on stopforumspam.com. I know precisely what it takes to stop spam...
The simple method would be:—
- Make a Report Link
(at the backend send an email)
(that will take an hour to setup)
(mods & admins get an immediate heads-up on new spam)
(once in place, do next steps)
- Start blocking on combos of IP+email address
(if a new user tries to create an account from a known bad IP + Email, then block it)
- Start reporting IP+email address+username from spammers
(note that this loops back to )
(it means that the amount of spam on the site rapidly begins to fall to zero)
It was fantastic to be welcomed by Mapillary power users [Vincent de Château-Thierry](twitter.com/_vdct) and Jean-Louis Zimmermann and speak over dinner to Christian Quest, President of OpenStreetMap France. Thanks a lot for getting me to our stay at the Indigo-Camping site.
Photo by JL Zimmermann
For the conference, it was great to see a whole lot of interest in the work we are doing for OSM and the wider community. Here is the link to my short presentation - the videos should be up soon I hope. Jean-Luis showed a LOT of interesting examples of the use of Mapillary for different OpenStreetMap applications, available as a wiki of links - check it out!
Also, Jean-Luis is the master of 360 DIY rig mapping and congrats to your promotion in the OSM community to national secretary of OpenStreetMap France!
Also, we got a lot of interesting opinions regarding improvements of upload, apps, editing and integration into JOSM, iD, OpenLevelUp and other projects.
Thanks a lot, and keep the ideas coming so we can get the best of the two communities to help each other out! Learn more how to use Mapillary for OSM.
Cuba Shapefile Data
On Saturday 14 May we held the second day of #MapeoLibre (OpenMapping), in the continuity of the open mapping day in the UAEMEX university in Toluca (State of Mexico). This format seems to be a good cross between technical education with the use of web and field apps; an overview of different ways to collaborate with Openstreetmap; and an opportunity to inform and get feedback on different projects and collaborations that can be developed as well, using OpenStreetMap open technologies and data.
We hold these days in series: the first was in the UAEMEX, it continued with the UNAM of Mexico City (Faculty of Engineering) with the support of Francisco Rojas Duran in the organization, and we are planning the next workshops in 3 others public universities for the next semester. The conference format combines theoretical and practical activities with different tools on a full day.
This time the conference included:
- A general introduction to open data, to the uses of data for many purposes such as public policy and research. We presented some cases of projects for various purposes based on Openstreetmap: Lerma mapping (State of Mexico), and the #Repubikla project.
- A training to Id Editor, focused on mapping the university campus as in the last experience in the UAEMEX.
- An introduction to HOT and tasking manager, with exercise on a medium-level emergency in Ecuador.
- Training and field exercise with #Mapillary and OSMtracker in the campus. For the exercise with mapillary, we encourage participants to participate to the #Mapeaton action. Mapeaton (Pedestrian mapping) is a collective account created with Mapillary, that reveals transit conditions for pedestrian and wheelchairs (sidewalks conditions, accesses, ramps, etc.).
Alberto Chung, Eldesbastemap, Ealp, Ccossio, Juane90, JosueR, Mapanauta, Mapeadora, Tavooca, Yoltotolhua are those that participated in this dynamic.
The attendance was large, equivalent to the workshop in the UAEMEX, with about 80 people. People were students from the UNAM (about a half part), teachers and researchers, people invited from social organizations in the context of other workshops that we have organized these last months (3rd Congress Peatonal), people from public institutions with whom we are developing collaborations, from Mexico City and other states (Hidalgo). Based on these massive training, we are building an ever wider broadcast network, in order to have a large impact on strengthening the mapping community in Mexico, and enhance the knowledge of OSM by public institutions and universities.
Since the UAEMEX workshop, looking to have a dynamic that strengthens learning among participants, and making them constant mappers, we launched an competition initiative over a month, with a recognition for top 5 mappers. So we ask for the use of two hashtags in the changeset (#MapeoLibreUNAM, in this case, and #mapathon), to monitor progress and issues, with http://resultmaps.neis-one.org/osm-changesets ? comment = MapeoLibreUNAM # 4 / 11.09 / -92.99 and http://overpass-turbo.eu/s/goB.
We post about the progress during the month of competition, to motivate the group, while gifts are managed with sponsors. This action serves a threefold strategy: to track users and build community; continue training beyond the framework of the workshop, with the ability to detect and report on recurrent errors, strengthening skills; sow love for mapping. We also try to to have a symbolic and visible result: the detailed mapping of the campus where the event takes place and its surroundings.
Each activity resulted in an meaningful dialogue with the audience, with both theoretical and technical questions, interest to learn more advanced tools, inspiring ideas and projects, with which we can possibly collaborate formally. We also established a feedback dynamic between instructors, discussing comments made by the participants individually, as well as personal impressions in order to improve the dynamics. We thought for example that in coming sessions may have a final brainstorming time with attendees about potential projects, collaborations, or potential uses of OSM tools to serve current projects.
Each of the workshops given in the last 8 months (we had 12 including Openstreetmap, Repubikla and Mapillary-Mapeaton workshops) has generated a great potential for collaborations with related projects or tools from OpenStreetMap community. We always perceived innovative visions on mapping questions. A recent example (in the last Repubikla workshop in Morelia, Michoacan with Bicivilízate collective) is the use of mapping as a memory performance (#PerformanceDelCaminar) on missing persons in the state of Michoacan where the artist Fabiola Rayas recreates the last known path of the disappeared along with his family and community (it will be the subject of a future post).
When looking through the pages of Open Street Map community at Google+, I stumbled upon an article about collaboration between Open Street Map and Mapillary. Mapillary – is a service for sharing of geotagged photos developed by Mapillary AB, located in Malmö, Sweden. The goal of the company is to represent the whole world (not only streets) with photos using Crowdsourcing. What got me interested is that geotagged photos may be used for OSM map data creation because they licensed under CC-BY-SA license, availability of the plugin for the popular JOSM editor and possibility to turn on Mapillary layer in web-based iD Editor. Mapillary service is an alternative to Google Street View and Yandex Panoramas except that it is users who provide photos for the service. Mapillary service has apps for the mobile phones based on Android, Windows Phone, iOS and BlackBerry OS. But shooting photo-sequences with your phone while you walk or ride bicycle is not very comfortable, besides that phone battery dies very quickly, mount for the phone could be unreliable etc. That’s why in this article I will describe how to create panoramas for the Mapillary service using action camera. When you use Mapillary app on your phone all exif-tags that are necessary for photo geolocation (coordinates and shooting direction) acquired automatically because phones mostly come with compass and GPS unit already built-in. Action cameras usually doesn’t have built-in GPS unit (not like Sony Action Cam HDR-AS30v) that’s why we would need GPS-track for manual geolocation of photos.
What we would need is:
- Action camera with car/bicycle mount that can shoot in time-lapse mode. I use cheap but powerful Xiaomi Yi Action Camera.
- Device that could record GPS-track. It could be GPS-logger or mobile phone with GPS, or combination of both. I use GPS-logger HOLUX RCV-3000 connected to the phone by Bluetooth and mobile phone with OSMTracker (Android) app installed to record GPS-track. If satellites are dispersed in the sky-evenly in each direction HOLUX RCV-3000 could output GPS data with 1.7 meters accuracy.
- A little mind-twisting (dance with a tambourine – in original article, from Ukrainian) around Python, wideband internet access for manual photos upload to Mapillary.
Now in detail:
Start your GPS device and leave it in the place with clear visibility of the sky until GPS position is fixed (for better accuracy let it be for at least 5 min), after GPS position is fixed start GPS-track recording, make a picture with your camera of your phones current time with precision to the seconds (may be needed later for synchronization and setting offset), then start your camera in time-lapse mode and start to move through streets/places for which you wish to create Mapillary photo sequences, when you done export data from OSMTracker into .gpx-file. For the bicycle ride I chose shooting interval of 2 seconds, for the car which could move much faster would be vise to select shorter interval, the camera mentioned above could do time-lapse mode with interval up to 0.5 seconds, as long as fast class micro SD card installed. In my case I still make picture of the phones clock with the camera and make sure that camera clock is synchronized with phones clock, in the OSMTracker Preferences menu I check box to ignore GPS-time and use phone-time (my local time) for the time stamps. In that way photos from camera and time stamps in .gpx-file will be in the same time zone and already synchronized, if you didn’t do that you still could correlate photo position with GPS-track later in JOSM as long as you took photo of your phones clock. As a result we got a sequence of the photos and .gpx-file of recorded track. For convenience create a folder named with current date and copy photos and .gpx-file in that folder. It is recommended to create a backup folder here as well and copy all photos in it before making any changes in case something will go wrong.
There many ways to geotag a photo ranging from use of Windows-programs and to Python scripts or libraries/ modules Ruby Gems on Linux-like operating systems. I will describe two the most easiest ways for the common user:
Geotagging with old and powerful JOSM:
I use JOSM for tagging photos with GPS position, it’s simple and fast to use.
In order to write exif-data to the photos after we synchronized them with GPS-track in JOSM, we need to install Photo Geotagging plugin. Go to the JOSM Preferences (F12)>>Plugins tab>>Search for Photo Geotagging and check the box to install, after installation restart JOSM.
After JOSM is started>>Open .gpx-file and add photos to the loaded GPS-trak, set correlation to 0, because our track recorded using local time zone (phones time), if GPS-track was recorded without prior correction (GPS time is always in UTC 0:00 time zone) then you need to correlate the difference in relation to Greenwich. The best way to do this is to determine the difference from the first picture we took of mobile phones time on the screen, just select this option from dialog and enter the time you see on the picture, in result all sequence will be lined up properly.
Then just right-click the “Geotagged Images” layer and select “Write coordinates to image header”, then yes. Additionally you could check the box on the “keep backup files” option if it wasn’t done earlier. Saving of changes is very fast.
After those steps is done each photo should have coordinates and altitude above sea level (if altitude above sea level was recorded to .gpx-file). To check this you could use simple program called ExifTool by simply dragging photo on the program icon.
Alternative way using freeware-program GeoSetter
Run GeoSetter and in the directory choose dialog select folder with photos which you would like to geotag.
Select all photos in the folder (Ctrl+A) and push on the “Synchronize geo data of selected images with GPS data files” button (Ctrl+G) which will call the dialog window to choose GPS-track and synchronization parameters setup.
Choose .gpx-file (if track in the same folder as photos, option to use track from that folder will be automatically checked), if needed choose parameters for correlation and press OK. If photo time stamps (Original Taken Date tag) and .gpx-file track-points time in the same time zone program will tell us that GPS positions was found for some amount of the files. If photos doesn’t match the time of .gpx-file track-points you need to set time zone difference. After photos is synchronized don’t forget to save the changes by pressing either floppy disk icon or Ctrl+S key combination. It takes a lot more time to save changes compared to the JOSM.
After those steps is done each photo should have coordinates and altitude above sea level (if altitude above sea level was recorded to .gpx-file). To check this you could use simple program called ExifTool by simply dragging photo on the program icon.
Preliminary photo adjustment and compression
This step could be skipped if you have broadband internet connection with high speed of upload. This step should be done before image direction is calculated because in my case Adobe Lightroom deleted “GPS Img Direction” tag from file header, ignoring the fact that I chose to leave all metadata as is. After import into Adobe Lightroom automatic tone and white balance was done to all photos, then photos exported at the same resolution but with compression to 700 kB and sharpening option for the screen. You could use trial version of Adobe Lightroom, which is free, and continue to work with limited functionality after the trial license expiration date. Tab “Library” still remain active with and you could use “Quick develop” standard presets to do the adjustments. Check out this article for more information. Mapillary team in their instructions recommends to use freeware editor IrfanView, which could do the batch processing of the files.
Setting up Python environment for use of Mapillary Tools scripts.
Prerequisite for this step is installed and properly set up Python programing environment, in our case we would need Python version 2, latest release could be downloaded here. How to properly set up Python could be checked here. Then we would need Mapillary Tools scripts, they could be downloaded from project GitHub page. Unpack archive for example in your user Documents folder. Not entirely full and precise article on how to run Mapillary Tools scripts in Python here. First we need to install a few libraries/packages by means of pip (Python Package Manager) in order for Mapillary Tools scripts to work:
- exifread – installed by means of pip.
- gpxpy – installed by means of pip.
- PIL – installed by means of pip.
- pyexiv2 – installed using Windows-installer, depending on the version of your Windows OS x32 or x64.
Now in detail:
Run Windows command line, by means of Run menu (Win+R), enter “cmd” into the search field. We need to check if Python is working, enter “python” in command line, if everything was set up i.a.w. instruction in the link above, then Python command interpreter should start. You can tell that Python interpreter started by the appearance of “>>>” in command line, now you could do simple commands like “print (“All hail OSM”)” and simple math operations. After we checked that Python set up properly, close the command line and start it again. Then we need to install necessary packages necessary to run Mapillary Tools scripts, namely: exifread, gpxpy, Pillow, pyexiv2 package installed manually by running the installers from the links above. Python (version at the time article was written 2.7.11) by default installed to the following file path: C:\Python27\python.exe. Along with the Python itself, Python Package Manager “pip” installed as well, in my case path to the pip is: C:\Python27\Scripts\pip.exe. In command line change directory to the C:\Python27\Scripts\ in order to run “pip.exe”, for that type in the command line “cd C:\Python27\Scripts\” (path could be simply copied and pasted into command line by right-clicking the mouse over the cmd window, without need to type it manually) Then enter one by one and observe the progress of the packages being downloaded and installed. pip install exifread pip install gpxpy pip install Pillow Because those packages already installed on my system, I only receive message to update the package and the path to witch it was installed: If everything went well and without errors, then Python environment is ready Mapillary Tools scripts execution.
Calculating the image direction with use of Python scripts.
First I need to mention that Mapillary Tools has a lot of scripts for image processing and further upload to the Mapillary service, including the script to geotag the photos, but not all of them are working or work incorrectly, and author of the scripts mentioned this in the comments to the scripts. For example, I didn’t manage to geotag my photos (currently in correspondence with the scripts developer to resolve the issue), that’s why I described two easier ways to do that in this article. But fortunately, script for calculation of direction photo was shot, in my case, is working and very quickly calculates and writes image direction tag in degrees based on the coordinates of the next photo that was taken in time-lapse sequence. Thus, let’s start calculation of the direction photos were shot. At this step we already have a folder with photos that already has GPS coordinates and time stamps and only thing we need is to enter the path to the script, then to the folder with photos and camera angle offset in regards to the direction we moved. If camera was pointed in same direction to which we moved, then angle offset will be “0”. Scripts are in the archive Mapillary Tools that we downloaded and extracted earlier in the Documents folder. In my case path to the script “interpolate_direction.py”, which we need is: “C:\Users\vfedo\Documents\Mapillary\mapillary_tools-master\python\interpolate_direction.py” Path to the folder with photos: “D:\Mapillary\19.05.2016\backup” Then run the command line and enter: python “C:\Users\vfedo\Documents\Mapillary\mapillary_tools-master\python\interpolate_direction.py” “D:\Mapillary\19.05.2016\backup” 0 (you could use quotation marks or not, it doesn’t matter, but it helps me to outline separate parts of the command) After the script is done its magic we have geotagged photos which has direction of shooting and ready to be uploaded to the Mapillary service. You could check the direction of photos visually in the GeoSetter program by selecting directory with photos and switching from photo to photo by arrow key, this will help to detect the photos which was possibly processed incorrectly by “interpolate_direction.py” script, for example when you wait for the green light GPS-track points will be “dancing” around your real position, due to the GPS unit working principle and possibilities, thus the direction of such images will be calculated improperly, consider deleting such photos from sequence before you upload to Mapillary. Direction could be set after you upload to Mapillary as well, but it will take long to process, (currently service accepts up to 100 changes at time from the editor) and even if you could see that the angle was set for the photo in editor it still points to the north and when you check them in JOSM it’s the same. That’s why to get quality sequence better upload completely ready photos (that include tags: "GPSLongitude", "GPSLatitude", "DateTimeOriginal" та “GPSImgDirection” in the exif header). If photos still were uploaded to the server without “GPSImgDirection” tag, it could be corrected in the editor for the whole sequence: enter the editor and check the box to set the direction angle so each photo will be facing next photo in the sequence and if needed specify the offset angle. Offset angle is counted clock-wise in the North-East system of coordinates in range from 0 to 359 degrees. For example, if camera was pointed from left window of the moving car, then angle offset will be 270 degrees (or -90 degrees, which is same direction). While testing, three of mine first sessions were (1, 2, 3) were uploaded without proper tag “GPSImgDirection” and though I edited them on Mapillary they still facing North on the service and in JOSM, maybe Mapillary team will fix that over time. There are upload scripts as well, but in this article I will describe manual upload in the web-browser, so you could see if photos were geotagged and processed correctly.
Uploading to Mapillary
In order to be able to upload photos to Mapillary service you need to create user account. After your successful registration go to the right upper corner and by clicking your user name you could set up your profile, go to your profile or start Manual Uploads. Go the Manual Uploads and press Choose Files, select photos for upload and Mapillary will check them: If all necessary tags are present, then you will see photo sequence connected by line and each photo has the direction arrow: Then press Upload and wait for upload to be finished: If during upload process the progress shown in percent doesn’t change or your internet connection disconnected, you could continue to upload by pressing “Upload hung up? Click here.” link. Page will update and show the photos that already uploaded, and the option to upload more photos to the sequence and Publish Sequence or cancel. Select upload more photos to the sequence and choose all photos again, Mapillary will check them, discard the duplicates and offer to upload rest of the photos, showing them on the mini-map with orange points. After upload finished, better to double-check the amount of photos in the folder. Everything seems right 646 photos uploaded. Now you could click Publish Sequence and receive a high five for the good work. Now let’s find out how to use photo data from Mapillary for mapping in OSM.
Using Mapillary service for mapping in OSM
Because we can use photo data from Mapillary to map the objects in OSM, let’s check how to do it with two most popular OSM editors, namely JOSM and iD Editor.
Using Mapillary with JOSM:
In order to use Mapillary service with JOSM and be able to set Mapillary imagery as a layer we need to install pugin of the same name. For that go to the JOSM Preferences (F12)>> Plugins tab>> Enter Mapillary into the search line. Restart JOSM after plugin installed. After JOSM is started load the map data for the area that has Mapillary coverage. Mapillary coverage could be checked at this web-page, enter your location or zoom in to it, by red lines photo sequences are shown. I will download an area of my own town, for which I uploaded photo sequence earlier. After OSM map data layer is loaded, Mapillary photo layer could be loaded by going the menu Imagery>> Mapillary (or by keyboard shortcut Shift+comma).
Using Mapillary with iD Editor:
It is easy to make iD Editor show Mapillary photo layer, just enter the Edit mode for the chosen area, then click on Map Data button (shortcut F) and choose Mapillary photos. After that Mapillary photo layer will appear, showing the photo direction and photo markers which you could click to fix or hover you mouse pointer over them. (screenshot left as in my original post, i.e. iD Editor layout with Ukrainian language)
Mapillary and OSM collaboration plays a big role in both projects development. This How To was created with intention to inspire OSM community to increase Mapillary coverage, because most likely small towns and other places don’t have it, and use of commercially available analogs for mapping in OSM is prohibited.
Beautiful gif-animation was created with use of open-source program ScreenToGif.
This is translation of my original article, I am not native English speaker, if you find any mistakes please leave a comment, also share this with your local OSM community and any social network, feel free to use material in the article to translate it into your mother language with reference to this article.
Happy and productive mapping to everyone.
I'm trying to understand how to interpret the "Parsed by Markdown" table that appears next to the text "Body" in the OSM "New Diary Entry" form.
I understand to add a heading I must prefix it with a pound sign followed by a space "# " :
This is a heading
To create an "Unordered list" you prefix the text with an asterisk followed by a space "* "
- First item in an unordered list
- Second item in and unordered list
Similarly an "Ordered list" is a number followed by a period and a space "1. "
- First item
- Second item
A link is to be entered by using the format "[Text](URL)". Here you retain the brackets and parenthesis and replace the word "Text" with the name of the URL and letters "URL" with the actual web address.
Here's an example where I replaced "Text" with "OSM Diary Form" and URL with "http://www.openstreetmap.org/diary/new"
The last example for displaying an image is giving me trouble. The problem is that you need to use a URL for an image and the places I store photos like Flicker and Google Photos don't allows you to copy the link to the image file.
The format is "[Alt text](URL)".
I have to say that when I started using OsmAnd+ for surveying location, I saw occasional rendering hickups. It was not as pleasant as the other mapping applications, but it was still doing it's job.
Things changed dramatically when I tried using it on the roads with 45 mph (76 km/h) speed limit with complex intersections where zoom in/zoom out or turns caused the whole thing to redraw so furiously it was hard to keep track of what was where.
I posted a number of videos to show what I mean and I regret to say that I ended up with a result completely different to what I've hoped.
Yes, it is Open Source, and it has a ton of features (and almost awesome OSM Live!), but I just cannot use it for car navigation, sorry.
Improved Shaders for OSM2World
Read the proposal here.
My name is Zach, I'm a sophomore computer science student and research assistant at Southern Illinois University Edwardsville. I'm also a gamer, so when I saw the project suggestion I was excited to get the excuse to play with OpenGL and figure out how it works. I'd done some work with it in the past for 2D applications, but I haven't played with it in 3D. By the end of the summer I no doubt expect to have a firm grasp of it at the very least. Check out my github.
Getting set up
By default OSM2World doesn't use any textures, and has shadows disabled. There is an existing "texture pack" that contains the textures used to generate this map. My first step was tracking that down, its here (Basti sent it to me, so it wasn't actually that hard). To use it, the textures folder and properties file must be in the same directory as the built jar. After dumping those into my build folder, I was ready to go. I loaded up a map file and immediately crashed. I tried a few different map files until finally getting an empty parking lot to render, albeit with strange graphical issues. After crashing Java several more times, I moved from my underpowered laptop to my more powerful desktop computer (with an actual graphics card) and didn't have any problems from there. With this in mind, all of the changes that I plan to implement will be configurable so as not to make OSM2World unusable on a less powerful computer.
Shadows and Sunlight
I'd like to have the ability to change the time of day, many neat effects and images can be produced by moving the sun around and changing its color. I'm going to produce a small menu that lets you do just that, changing the time of day (or night) with a slider, and then calculating the appropriate angle and color of the sun and shadows.
What I'm most excited about seeing is this picture. The second major component of my project is reflections. If this were a real image, you would see the reflection of the short building in the foreground on the front of the building behind it. On the right side of that same glass building, if the sun were in the right place, you would expect the shadow of the short building on the right to be illuminated by the sunlight reflecting off the glass on the tall building, potentially a glare hitting the camera.
If you want a full breakdown of what I plan to do, have a look at the proposal, it includes a handful of other things I didn't mention. If there's anything you want to see, feel free to leave a comment here, send me a message, or open an issue on github, but I can't promise anything until I get through the big stuff.