A 50m x 25m geoglyph of what appears to look like a pointing arrow. is oriented northwest to southeast points at a trail heading in the same direction. It is impossible to determine exactly what the arrow is pointing at but there is a large irregular shaped geoglyph nearby. The pointed arrow direction aims along trail for more than 500m.

14°34′39″S, 75°9′48″W -14.5775299, -75.1634527 Llipata, Province of Palpa, Ica, Peru

A 20m wide x 500m long oriented northeast to southwest is a trapezoid geoglyph which appears to also have multiple 1m diameter concave holes or convex dome similar sized varying shapes appear to be in a loosely fit grid formation towards its narrowing tip. It is difficult to tell exactly the purpose of the circular shapes but they cover about 1/3 of the entire trapezoid and there are over 50 of them. The remainder of the trapezoid has other unsorted shapes that the aerial images do not detail making it difficult to trace. The trapezoid is on relatively flat land and lay 400m south of a greater cluster of trapezoid shapes and geoglyph lines. The base of the trapezoid has an interesting smaller trapezoid 25m wide x 75m long that is not clear why that purpose.

14°35′9″S, 75°10′38″W -14.5859621, -75.1771800 Llipata, Province of Palpa, Ica, Peru

A 200m x 20m wide trapezoid shaped geoglyph with what appears as large graffiti initials have a marked AYF / 10 inside of it. The entire shape is on flat land and roughly etched. . The initials are set upside down with the top of the letters facing nearly southwest. The AYF initials also have periods behind them. It is unclear what the initials stand for. There is also the number 10 indicated below the AYF.

Maybe one might speculate that the initials might stand for Alien Landing Strip.

14°36′43″S, 75°10′30″W -14.6118590, -75.1750500 Llipata, Province of Palpa, Ica, Peru

A large 25m x 25 of a counter directional spiral near other lines are indicated on relatively flat land. There is no indication that these two lines might or might not be part of a larger geoglyph.

14°34′37″S, 75°9′19″W -14.5769534, -75.1552543 Llipata, Province of Palpa, Ica, Peru

The tag #osmIRL_buildings is a kind of handy brand name our community has developed for our mapping campaign to map all of Ireland’s buildings. The campaign started with a brief test at a single mapathon in Galway in September 2019, and kicked off in earnest in Kilkenny at the end of November the same year. I say “in earnest” because this is when tasks were opened and the tasking manager started to be used every day.

The campaign has a number of effects which merit discussion beyond just the obvious upturn in mapping. But let’s mention that upturn first. The upturn started at the same time as the task manager being opened at the end of 2019. The number of buildings went from 810k to 1.5million in those 15 months, which means 47 thousand buildings were added each month.

picnic images

… See full entry

There’s a guy in Amarillo, Texas who is dead set on vandalizing the same features over and over and over. He’s been banned at least 4 times now. This diary entry will be used to keep track of all the user’s alt accounts and edits.

Usernames

1. Northridge 8
2. celltowerm
3. vanf5060
4. arbyswendys
5. tomorrowfireworks

Popular features to vandalize

• Park to movie theater
• Park to drive-in theater
• Drive-in theater to park

A geoglyph of a seal 75m x 35m drawn to appear to swim east to west on moderately sloped land. It is unclear where the seal is going however its proximity is rather close to another ocean related geoglyph. There seems to be are other shapes in the immediate area that suggest this is a scene related to an ocean.

15°17′33″S, 74°32′43″W -15.2923897, -74.5454017 Acarí, Province of Caravelí, Arequipa, Peru

A monolithic 20m x 25m split rock and trail going through it might have been some kind of benchmark. Located on moderately sloped land and appears split right down the middle.

15°17′32″S, 74°32′33″W -15.2923595, -74.5425975 Acarí, Province of Caravelí, Arequipa, Peru

Two geoglyph heads appear to be stacked one on top of the other on moderately sloped land. The bottom head is 25m x 25m and the top head significantly smaller 5m x 5m, oriented north to south. Both heads seem to suggest having bodies but they are hard to read at this time. Both heads look in the forward direction. It is unclear why they were created or what they are doing there.
The bottom head suggests that its body seems to have a bent arm, torso and two legs, though very short and stubby, they do appear there. The upper head, being smaller seems to have a smaller body and is unclear if the head is resting on a hat the of the bottom head. It might be suggested the top head is of a monkey.

15°17′27″S, 74°32′23″W -15.2907672, -74.5397234 Acarí, Province of Caravelí, Arequipa, Peru

Recent articles and blog posts about paid editing in OSM has renewed interest in the topic on social media and OSM discussion channels. The data and numbers presented in these discussions primarily come from a paper I co-authored in 2019, and are now outdated. This diary post presents new, updated figures.

Paid editing in OSM is receiving new attention in light of two articles in the past few months that are reporting on the phenomenon. Both articles heavily cite numbers from our 2019 Corporate Editing in the Evolving Landscape of OpenStreetMap paper:

• OpenStreetMap is Having a Moment (Joe Morrison - Medium)
• OpenStreetMap Charts a Controversial New Direction (Corey Dickinson - CityLab / Bloomberg)

These articles have prompted some discussion on Twitter from the larger OSM Community. What’s missing in these follow-up threads, however, are updated figures regarding the editing over the past two years.

This post only presents updated figures relevant to paid-editing in OSM and observational analysis. As the OSM research community continues to expand, stay tuned for more in-depth research in this space, such as: novel ways to identify undisclosed paid-editors and occupational mappers, new community-detection algorithms from editing editing patterns, and further investigations of the mapping interactions between paid and unpaid editors. At the end of this diary post I include a glossary with some of the terms in both this and previous posts of mine such as paid editing, professional editing, and occupational editing. These terms are becoming more common in this research space, so I am hoping to better introduce and define them.

Quantifying Edits

… See full entry

I liked Pete’s diary at the first sight. However, when published, I was already decided about my next work. Last Thursday I finally found some time to look closer at this interesting topic. I spent night working on it. And I will share the results in this diary.

First, I will not write about the HOT tasking manager. Second, these are my opinions. Third, understand damn in the following text as the shortcut of Divide and map. Now.

The summary of my understanding of the original diary follows. I’ll append my thoughts, though. I made a few toots during the night, which can serve to track the time effort.

What is TM?

Questions:

• What the TM is?
• What mapping process is?
• What is the origin of a project?
• What is the ownership of a project?
• For who is TM for?

Problems:

• New mappers don’t understand (because they don’t have answers.)
• New mapper edits frustrate old mappers.

Consequences:

• Discourage new mappers.
• Learning process interruption.

Thoughts:

The damn project has advantage here, because the name says exactly what the project does. Using areas, squares, and commits notation improves the clearness, too.

As there are multiple clients, each of them targets different group of mappers. Therefore, it’s easier to improve client for newbie mappers without limiting the experienced ones.

Each commit to the area is stored and shown when requested (statistics page,) improving the understanding of the area history.

Project creators

Original problem:

• When TM was opened, the data quality was low due to poor project description.

Solution:

• Onboarding process. Making sure that managers fulfill the expectations of having skills to:

  • engage local communities and contributors,
  • respond the questions and info requests,
  • ensure the documentation of the project is on the wiki (in the case of organised editing,)
  • ensure that standards are met,
  • ensure that the mappers are able to do what requested.

… See full entry

Im growing quite fond of editing. Loving it, i see great things coming from this.

A 20m x 40m geoglyph of a fish is oriented east to west. Etched on moderately sloped rock in profile and shown with a single dark visible eye, body fins and gills. The fish appears to be one of several hard to read geoglyphs nearby..

14°52′19″S, 74°56′26″W -14.8719975, -74.9405325 Vista Alegre, Province of Nasca, Ica, Peru

A geoglyph of a laughing face (25m x 25m) oriented north to south on a moderately sloped rock is a little hard to see. A front view image with both eyes appears to roll to the left, a long nose and gaping large mouth appears as its laughing. There is possibility of this geoglyph also has a neck and shoulders and torso. It is unclear what the geoglyph seems to be laughing at and why, the face is located to the right (east) of another geoglyph a sea lion. The reason for the laugher might simply be the joy in seeing these amazing animals.

14°52′21″S, 74°56′8″W -14.8725180, -74.9356717 Vista Alegre, Province of Nasca, Ica, Peru

Frog Park

A geoglyph of a puffer fish (25m wide by 50m long) oriented north (head) to south (tail) on relatively flat has both eyes and a wide open mouth. The geoglyph includes a tail fin and two dorsal fins. The shape of the fish is large in the state that it isn’t puffed up. It is unclear how the fish is associated to the immediate surroundings. There seems to some other very nearby geoglyphs but possibly highly damaged and hard to read.

14°48′29″S, 74°55′24″W -14.8081793, -74.9233388 Nazca, Province of Nasca, Ica, 11401, Peru

Well, after a lot of field activity, introducing OpenStreetMap to Ugandan rural, humanitarian and govenmental communities in Uganda, Sierra Leone, Zimbabwe, and through conference presentations, Namibia and Tanzania, I finally decided to write a chapter about ‘Motorcycle Mapping’ - a concept and practice developed by Ivan Gayton (and myself) in West Africa, and scaled into Uganda under my watch as Country Manager.

The book in which this chapter appears was expected to attract a relatively niche market, until COVID happened globally, and a newly-found interest in Data Ethics was born out of various scandals around government treatment of COVID data in the UK.

Free downloads of the book are available: https://www.sas.ac.uk/publications/mapping-crisis, and an abstract for my chapter can be found here: https://rupertallan.com/modalities-of-united-statelessness-chapter-9-abstract/

For nearly a year, the government outbreak effort extensively overlooked humanitarian knowledge and experience on how to manage COVID data in the UK, but it seems they are consulting Epidemiologists now (including MSF).

During the last few months, COVID figures have been making headlines in Merthyr Tydfil, South Wales, and OpenStreetMap now has an opportunity and support to map the South Wales Valleys. I feel fortunate to have lived and worked in the Valleys in the 1990s, and am excited to be part of this venture. At time of writing, there is every chance that Merthyr Tydfil will see african refugees working in its streets and alleys, helping its community to map their own vulnerability metrics.

Registering utilities in Pilar Executive Village to enable best possible improvement instead of implementing features only partial.

Power lines are crossing streets zig-zag, sewage is barely working and up to three different street lighting systems are in place.

Access to area is being restricted as it it is used as pass through and short cut to reach other areas. The heavy traffic has caused severe road damage to one of the roads, annoying people living on that street.

Hope the mapping can improve insight and unite inhabitants.

Automate the creation of buildings and address tags using Microsoft’s AI building footprints.

Load the building footprints into QGIS and save into a shape file limited by the canvas bounds.

Iterate through each geometry and convert to polygon.

Check if polygon contains the address point.

If it does, then save address information and building polygon for import.

If any address points remain that have not been assigned a building polygon, then add them to the map as an addressed point.

When automating the creation of the ways and nodes, get the map for the bounds of the new element and check if it has already been created. This can be done by using OSMSharp on a freshly downloaded PBF or by querying the live map by bounds.

Upload changesets by zipcode in batches or 1000 to 2000. Possible add tag to specify your import.

This is dream come true…Being a non-coder,…was eagerly waiting for a chance to, be a part of the Open Source World.So here it is..Let’s help and improve everyone’s life for good..Thank you to the People who made this possible.God bless you all.