Due to working in camp occhannock on the bay all projects are paused

شارع

Shortly?

It was a year ago on yesterday (July 10, 2022) since I joined the OSM community. I would say it’s been nice to be a part of this awesome community that intends changing the world through open data provision.

Achieved?

• Fact that I became a part of the community of free data provision
• Meeting friends on the same endeavor in the community

On HOTOSM?

1. Achieved both Intermediate and Advance Mapper status in my first year
2. Mapped over 5k buildings, 100km waterways, 20km highways, close to 30 POIs, (on a close to 15hr mapping time)

It’s been GOOD

Continued working on matching OSM nodes with VSI stores. There were 6 near-perfect matches (exact same name, points less than 10 m apart), but after introducing some fuzziness to the name comparison, that number jumps to 23!

I manually inspected those 23 pairs and indeed they seem to be referring to the same business. The matching remaining in the initial 10 m matching attempt is “49th parallel cafe & lucky’s doughnuts” in OSM vs “49th Parallel Coffee Roasters” in VSI. This one requires further inquiry to see if the OSM should really be updated or not.

I’m not totally satisfied with this 10 m threshold though. It’s arbitrary and not really what I’m looking after. I think I’ll redo the analysis but using “nearest VSI business within 100 m”, so that each OSM node will always match at most one VSI store and it won’t be so strict on the distance.

Південний захід від Бару, села Гулі та Слобода-Гулівська. Вся зона, починаючи від Гулівського лісу, і закінчуючи кордоном з Хмельниччиною була картографована на 100 відсотків.

Цей відсоток стосується ненаселених об’єктів, об’єкти в цих двох селах не враховуються поки що. ДО об’єктів в населених пунктах я приступлю тільки після того, як я закінчу повністю картографування свого рідного району.

We had another great OSM meetup today in Perth (Western Australia). This time we were in Fremantle, where there’s lots of 19th century buildings that need address data and business information, as well as a fair bit of clearing up confusion about where one building ends and another starts. About eight people came.

We started in the café, fuelling up with coffees and pastries, and talking about how to map, what to map, and the general semantics of footpaths and roofs.

Then we wandered around for an hour and a half or so, splitting into two groups — one went down to the harbour and found lifebuoys, statues, and memorials to seafaring immigrants — the other attempted to add more detail to the University of Notre Dame’s campus, but actually ended up mostly working on addresses, businesses, and trying to make sense of building façades.

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Dear all,

Today, v5.5.0 of the OpenStreetMap Carto stylesheet (the default stylesheet on the OSM website) has been released. Once changes are deployed on the openstreetmap.org it will take couple of days before all tiles show the new rendering.

Changes include

• Fixed colour mismatch of car repair shop icon and text (#4535)

• Cleaned up SVG files to better align with Mapnik requirements (#4457)

• Allow Docker builds on ARM machines (e.g. new Apple laptops) (#4539)

• Allow file:// URLs in external data config and caching of downloaded files (#4468, #4153, #4584)

• Render mountain passes (#4121)

• Don’t use a cross symbol for more Christian denominations that don’t use a cross (#4587)

Thanks to all the contributors for this release, including stephan2012, endim8, danieldegroot2, and jacekkow, new contributors.

For a full list of commits, see https://github.com/gravitystorm/openstreetmap-carto/compare/v5.4.0…v5.5.0

As always, we welcome any bug reports at https://github.com/gravitystorm/openstreetmap-carto/issues

I spent most of my time today adding sidewalks in the area of Waterloo where my parents live, basically in an area boxed by Brookridge Drive, Kimball Avenue, Ridgeway Avenue, and 9th Street. There are some other areas of Waterloo that have sidewalks and crossings mapped, but they tend to be near downtown which, while useful, is a small percentage of the sidewalks that exist in Waterloo.

I actually haven’t been in the area since Easter weekend, but between the satellite imagery and my own memory I think I did a reasonable job mapping the sidewalks and crossings. I actually didn’t know about putting a node where a sidewalk/crossing and the road it’s crossing intersect until I got well into it, but I’m glad I went back and read the OSM Wike entry on Key:crossing as I hadn’t been creating the intersecting nodes until I did. I haven’t seen the results in OsmAnd yet (which is where I’ve seen crossings here in Champaign), but I’m pretty sure they’ll show up now that I’ve added them.

Admittedly part of the reason why I’m mapping these sidewalks is to direct some attention to where there aren’t sidewalks in Waterloo, but in my opinion there should be. A good example is here where the sidewalk on the north side of Park Lane ends after the Kimball Avenue access road crossing, but then starts again by Brockway Road, the next street to the west, only to end again at Colby Road. Gaps like this exist all over southern Waterloo, forcing pedestrians to either cross twice to stay on the sidewalk, move onto the street, or cut through the grass where the gap is. I’m hoping that by mapping the sidewalks I can highlight these gaps and maybe motivate people still living there to get them filled in.

Received some valuable feedback from the imports mailing list on the matters of data quality and the expectations on someone’s level of OSM experience before executing large scale automated data imports. I was pretty much well set in terms of data quality concerns, but it looks like I would need a bit more hand-holding from more experienced mappers and importers to properly execute a big import.

This is not a problem, though. It’s very reasonable and thankfully not a deal breaker to me because I chose a scope small enough that it’s feasible to execute this import manually instead of automated. In fact, my previous analysis that the VSI had about 570 coffee/café related business was an overestimation because - rookie mistake - I forgot to deduplicate by survey period.

The new numbers are:

• OSM Nodes Matching Coffee/Cafe: 574
• VSI Stores Matching Coffee/Cafe: 278
• OSM Nodes within 10 m of a VSI Store: 28
• OSM Nodes within 25 m of a VSI Store: 195

So yeah, lots of nearby matches to investigate. Now is the time to start fuzzy matching the business names and SK53 provided me some good reading material on that. It will be a bit challenging to do that with pure SQL (I’m trying to use dbt + BigQuery only for now), but I think it’s worth a try.

Foreword

I live in the St. Ann’s electoral ward of the City of Nottingham. As well as wishing to be able to improve the coverage of old_name + start_date for each street in Nottingham, I am intrigued to be able to discover when streets were laid out, metalled, drained & provided with sewers. Today that all seems normal, but I was astonished to discover that Blue Bell Hill Road had no street drainage nor sewers until the 1970s; a friend in Dowson Street has a well in their basement, whilst their road also has zero street drainage nor sewer, plus no water main through the street (water supply, sewer + drainage only at the rear of the terrace).

Like many cities in the UK, Nottingham has suffered shed-loads of physical upheaval/churn across the years. That has led to the appearance, alteration, disappearance and/or reappearance of streets and thus of street-names. I’ve recently gotten access to definitive information on (at least some of) those changes, and decided that I should strike the iron whilst it is hot. This diary is going to concentrate on local streets + national communication (rivers/canals/railways) as they apply to Nottingham City; it will also filter in items of national importance that occurred in Nottingham and/or affect the whole UK.

First, here is the OpenStreetMap Wiki on names.
Second, the principal sources I’ve been using:

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Placa conmemorativa del plan ‘Málaga hace historia’ dedicada a Anita Delgado, bailarina malagueña y princesa de la India, en el número 17 de la calle Peña. Fuente: trabajo propio (CC BY-SA 4.0) disponible en Wikimedia Commons.

Esta semana se ha inaugurado una nueva placa conmemorativa del plan ‘Málaga hace historia‘, en esta ocasión dedicada a Anita Delgado, bailarina malagueña y majaraní (princesa) de Kapurtala. La placa ya aparece en Open Plaques y también puede encontrarse en OpenStreetMap, a la altura del número 17 de la calle Peña.

Todas las placas del plan ‘Málaga hace historia‘ se encuentran en el mapa. Me he ocupado personalmente de ubicarlas tanto en OpenStreetMap como en Open Plaques, donde hay una serie dedicada a estas placas. Hasta el momento se han colocado trece placas. Mi intención es seguir añadiéndolas conforme se vayan inaugurando.

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I was finally able to start reconciling the Vancouver Storefronts Inventory (VSI from now on) and the OSM nodes. VSI has 578 coffe/café matches, OSM has 574. These numbers are so close, it gives me hope.

When searching from nodes in OSM that have a nearby (<10 m) node in VSI, 54 results come out. Of those, 51 are perfect matches (business name in OSM is the same as in VSI, except for things like “Starbucks” in OSM vs “Starbucks Coffee” in VSI). This isn’t too thrilling, but honestly a near 10% perfect match from the get go is pretty sweet.

Using 10 meters is pretty bold, so I’ll experiment a bit on a healthy threshold that gives me more matches but doesn’t yield too many false matches. A 25 m radius already jumps to 391 matches and a 50 m radius gives 705 which is obviously too much.

If I have the time, I should also probably start getting fancy with fuzzy matching business names to get the obvious non-identical matches out of the way so I can investigate proper mismatches.

Condivido alcuni dei miei tool/siti/app preferiti relativi ad OSM con una brevissima descrizione, compresi quelli più conosciuti (non si sa mai). Sicuramente ne ho dimenticati molti e non ne conosco altrettanti.

Siti

• overpass turbo: Sito essenziale per fare query sul database. Utile anche per fare filtri QA personalizzati.
• taginfo: Per controllare quali tag sono più utilizzati, il loro uso nel tempo, i valori più utilizzati per ogni tag ecc. Per la history di un tag esiste anche questo sito.
• RapiD: iD sotto steroidi. Segnala possibili edifici e strade mancanti.
• osm-revert: Per revertare interi changeset. (ho sostituito Revert UI, non più supportato).
• Level0: Per revertare singoli nodi. È un editor testuale utile anche per cambiare svariati tag contemporaneamente. Leggete però questo prima.
• NotesReview: Per filtrare le note di OSM per utente, data, testo ecc. C’è anche un sito di Pascal Neis.
• Strade senza nome
• Disaster Ninja: Non è il suo scopo principale, ma c’è un layer interessante chiamato “Building Quantity” nel caso vogliate trovare zone con edifici da mappare.
• YoHours: Un sito per semplificare la compilazione del tag opening_hours=*
• How Did You Contribute: Statistiche riguardanti gli utenti. C’è anche la heat map delle vostre modifiche.
• Is OSM up-to-date?: Interessante sito creato da un italiano che vi segnala i nodi meno aggiornati. Se non c’è nulla da aggiornare potete comunque lasciare un tag check_date.
• Field Papers: Modificate OSM prendendo appunti su carta.

Renderer

• F4map Demo e OSM Buildings: Nel caso vogliate vedere i tag 3d renderizzati.
• Indoor=: Nel caso vogliate vedere i tag indoor renderizzati.
• Open Etymology Map: Altro sito creato da un italiano. Renderizza il tag name:etymology. Esiste anche un sito che agevola l’inserimento del tag.

Wiki

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本文章同時嘛有提供 English version 佮華語版本

開放街圖臺灣社群（OpenStreetMap 臺灣社群）誠歡喜爭取到維基媒體基金會的聯盟補助，主要欲買兩台 Insta360 One X2 翕相機（佮相關的配件），猶閣有規劃對2022年3月開始，一直到2023年2月的街景踏查團佮對應的編輯工作坊活動。咱欲辦理六擺實地踏查佮至少六擺的編輯工作坊。社群成員欲共360翕相機囥佇汽車車頂，若開車若翕360相片，翕猶未翕著街景的所在。翕了後佇咧電腦前，閣來若看翕的相片，若編輯 OpenStreetMap 共編地圖添加資料，猶有共路途中間經過的景緻佮在庄聚落，共相關相片上傳到 Wiki Commons 多媒體站。

Khai-hóng Kue-tôo Tâi-uân Siā-kûn（OpenStreetMap Tâi-uân Siā-kûn）tsiânn huann-hí tsing-tshú kàu Uî-ki Muî-thé Ki-kim-huē ê Liân-bîng Póo-tsōo, tsú-iàu bueh bué nn̄g-tâi Insta360 One X2 hip-siòng-ki (Kah siong-kuan ê phuè-kiānn), iáu-koh-ū kui-uē tuì 2022-nî 3–ge̍h khai-sí, it-ti̍t kàu 2023-nî 2–ge̍h ê kue-kíng tah-tshâ-thuân kah tuì-ìng ê pian-tsi̍p kang-tsok-hong ua̍h-tōng. Lán-bueh pān-lí la̍k-pái si̍t-tuē tah-tsâ kah tsì-tsió la̍k-pái ê pian-tsi̍p kang-tsok-hong. Siā-kûn sîng-uân bueh kā 360 hip-siòng-ki khǹg tī khì-tshia tshia-tíng, nā khui-tshia nā hip 360 siòng-phìnn, hip iah-bē hip-tio̍h kue-kíng ê sóo-tsāi. hip liáu-āu tī tiān-náu tsîng, koh-lâi nā khuànn hip–ê siòng-phìnn, nā pian-tsi̍p OpenStreetMa kiōng pian tuē-tôo thiam-ka tsu-liāu, iáu-ū kā lōo-tôo tiong-kan king-kè ê kíng-tì kap tsāi-tsng tsu-lo̍h, kā siong-kuan siòng-phìnn siōng-thuân kàu Wiki Commons to-muî-thé-tsām.

這擺踏查團和頂擺行無仝的方向，頂擺是對北海岸（主要是基隆、金山、萬里）的方向行，毋過這擺是對鶯歌、三峽、大溪的方向翕相，和頂擺無仝，這擺是三台車的出發地點攏無仝（筆者駕駛的車是對和運租車新店站出發的，佇出發進前嘛發見路對面的新店區公所站二號出口猶未翕過，所以就順手翕一張囥佇 Wikimedia Commons頂懸）。

Tsit-pái tah-tsha-thuân hām tíng-pái kiânn bô-kâng ê hong-hiòng, tíng-pái sī tuì Pak-hái-huānn (tsú-iàu sī Ke-lâng, Kim-san, Bān-lí) ê hong-hiòng kiânn, m̄-koh tsit-pái sī tuì Ing-ko,Sam-kiap, Tāi-khe ê hong-hiòng hip-siòng, hām tíng-pái bô-kâng, tsit-pái sī sann-tâi-tshia ê tshut-huat tuē-tiám lóng bô-kâng (pit-tsiá ká-sú ê tshia sī tuì Hô-ūn Tsoo-tshia Sin-tiàm-tsām tshut-huat ê, tī tshut-huat tsìn-tsîng mā huat-kìnn lōo tuì-bīn ê Sin-tiàm Khu-kong-sóo tsām 2-hō tshut-kháu iah-bē hi̍p–kè, sóo-í tō sūn-tshiú hip tsi̍t-tiunn khǹg tī Wikimedia Commons 頂懸）.

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This article is also available in Taiwanese Mandarin (台灣華語) and Taiwanese Hokkien / Taigi (台文)

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The OpenStreetMap Taiwan Community (OSMTW) is pleased to receive the Wikimedia Alliance Fund for procuring two Insta360 One X2 (and accessories), as well as holding at least six Expeditions and Post-expedition Mapping Workshops from March 2022 to February 2023. OSMTW members will initiate surveys to the street-view terra incognita with a 360-degree-camera-mounted vehicle, then edit on OpenStreetMap and upload media taken throughout the exploration to Wikimedia Commons.

The path of this expedition differs from last time and headed south for Yingge, Sanxia, and Daxi rather than the Northern Coast (Keelung, Jingshan and Wanli). The “Street view car” dispatched this time also departs differently. (The vehicle author droves kick off at Hotai Easyrent Xindian, so he took a photo of the unphotographed Exit 2 of MRT Xindian District Office Station and uploaded to Wikimedia Commons before departure.)

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本文章同時也提供 English version 與台文版本

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開放街圖臺灣社群（OpenStreetMap 臺灣社群）很榮幸爭取到維基媒體基金會的聯盟補助，主要用在購置了兩台 Insta360 One X2 相機（與相對應的配件），並規劃自2022年3月開始，一直到2023年2月的街景踏查團與對應的編輯工作坊活動。將辦理六次實地踏查與至少六次的編輯工作坊。社群成員架設360相機在汽車上面，邊開車邊拍攝360相片，拍攝還沒有人拍攝街景的地方。之後回到電腦前，再來用拍攝到的相片為依據，編輯 OpenStreetMap 共編地圖添加資料，以及將沿途經過的景點與在地聚落，上傳相關照片到 Wikimedia Commons 多媒體站。

這次踏查團跟上次走了不同的方向，上次是往北海岸（主要是基隆、金山、萬里）的方向走，而這次是往鶯歌、三峽、大溪的方向拍攝，與上次不同的是，這次三台車的出發地點都不同（筆者駕駛的車是從和運租車新店站出發的，在出發之前也發現其對面的新店區公所站二號出口尚未拍攝，所以就順手拍了一張放到 Wikimedia Commons上）。

走的路線也幾乎都不一樣（但中間還是設了會合點，是在三峽白雞山的行脩宮）。

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Getting familiar with the Vancouver Storefront Inventory dataset. Apparently there are around 578 businesses with names that include Coffee or Cafe/Café, which looks pretty good. Judging by name only is pretty unreliable, but at least the vast majority of the matches are in the Food & Beverages category which is reassuring.

By chance, one of these businesses is already permanently closed (according to other sources): Café Logos. It was literally the first one I randomly selected to investigate, and it’s already data that should not be imported to OSM. Oh well. This is going to be tough.

On the OSM front, today I learned how to use the BigQuery dataset that has a handy table containing the OSM areas/ways as GDAL objects, which I can use to further sub select the nodes that are inside the region of interest (Vancouver) using ST_DWithin.

My last fortnight has been spent updating the photo-URLs within these diaries of pictures that I’ve taken whilst mapping. By default the Mapillary page will normally show a small version of any photo in it’s GIS-database, whilst behind it is a map using OSM-mapping; here is an example of that, showing the front of a business called AST, as it was displayed in a 12 July 2019 diary.

In the past the owner of the photo — the person that uploaded it to Mapillary — was given a button that would give them a URL that allowed them to download the raw file of the original photograph. That was useful for webpages such as these diaries, since it allowed the photograph to be displayed. However, Mapillary has changed it’s policy on the usage of those download URLs.

At some time in the past Mapillary changed the URL format for both map-display pages & download-file pages. The original map-display URLs had the following format (1st line below) whilst the download-files were 2nd-line below (the IDs in each URL were identical for a specific photo):

• https://www.mapillary.com/map/iM/<12-digit-alpha-ID>
• https://d1cuyjsrcm0gby.cloudfront.net/<12-digit-ID>/thumb-2048.jpg

Mapillary changed the format to the following (sorry about this):

• https://www.mapillary.com/app/?pKey=<16-digit-numeric-ID
• https://scontent-man2-1.xx.fbcdn.net/m1/v/t6/<150-digit-alpha-ID>?stp=s2048x1152&ccb=10-5&oh=<61-digit-alpha-ID>&_nc_sid=122ab1

Mapillary also made 3 crucial extra decisions:

1. The map URL would auto-rewrite via a 302 between the old & new format
2. The old Download URL would NOT rewrite to the new
3. The new Download URL would timeout after 14 days (or maybe less) (appears to be just 2 days)

Thus, after 14 days of trawling through every relevant page & changing all relevant URLs the photos are still not showing. I’m not happy.

And here the relevant photo to see what happens:

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나는 이 완벽한 날을 즐겼다