OpenStreetMap
태그는 traffic_calming=*; traffic_calming=yes
traffic_calming=dynamic_bump : 제한속도를 지키는(즉 천천히 달리는) 차량은 영향을 받지 않거나 적게 받지만 과속을 하는 차량은 영향을 크게 받도록 한 과속방지 장치.(
To whomever is reading this, my apologies.
I work for my state’s Dept. of Wildlife Conservation, and help make maps of agency-managed lands for public use. I’ve noticed a few projects geared towards community-development of basemaps.
At a recent Division-wide meeting, one of the Field Biologists brought up that they were surprised to find one of the WMAs (Wildlife Management Areas) depicted in an online vector basemap. At which point, I decided that I needed to take it upon myself to add/update our areas in those community-driven basemap projects.
I began by using the osm.org basic iD Editor. I was surprised to learn that shapes could not be imported directly. But happily began playing “connect the dots” with gpx files rendered from my shapefiles’ vertices.
We use Esri tools, so I made use of Dan Patterson’s “Poly* features to points” tool to create numbered points for each WMA.
This was okay for the first week.
I found myself losing patience with all those dots… Why couldn’t I trace another editor’s lake boundary? Why are this area’s boundaries linked to the roads? Why is this one area treated as two… is it not possible to dissolve them into one area along the shared boundary?
I don’t want to anger the rest of the OSM Community, but nor do I want to spend the rest of the month connecting the dots over some million-and-a-half acres and fiddly boundaries along man-made reservoirs.
So I found JOSM. It is horrendibly confusing to me, but I hope to get it right. …I note there is a ‘trace other feature’ tool. ^_^
(I’m publishing it now, I will review, and might add screenshots.)
Here in Panama I’ve occasionally noticed bursts of name contributions by foreigners who do not know the language, or by local people who copy from official information where the accents have been purged, or contributed long ago when non-ASCII character became a question point.
Whatever the case, we have textual mistakes in the database, so that when from time to time I browse the database, I still stumble on “Simon Bolivar”, “San Jose”, “Canaveral”, “la Compania”, and the commonplace terms Panaderia, Pasteleria, Fruteria, etc.
If you’re not familiar with Spanish, you haven’t noticed anything wrong, or have you?
Those familiar with the language and/or fixated on formal correctness like linguists, philologists, and mathematicians, have felt pain, because the correct Spanish form of the above words is “Simón Bolívar”, “San José”, “Cañaveral”, “la Compañía”, “Panadería”, “Pastelería”, “Frutería”, etc.
Just for reference, at the time of writing, “Simon Bolivar” in the Bolivarian Republic of Venezuela returns 32 objects, while “Simón Bolívar” gives 200, possibly giving a measure of some national pride. Colombian “Fruterías” however score 56 vs. 64 against “Fruteria” without the accent.
Here I only focus on what are obvious orthographic mistakes, skipping any data that might look wrong only because it’s in a different language, and I want to fix the mistakes only looking at the textual information, not to the geographic or geometric characteristics of the object.
This spares me downloading object coordinates, and the base map, but still I will advise checking every single instance we’re fixing, no automatic blanket fix.
I suggest using overpass-turbo, level0, the standard unix stream editor sed. Then correct the data in the level0 html interface.
Acabo de trabajar en una tarea marcada por el validador para más mapeo por tener muchos edificios duplicados y muchos sin escuadrar.
El proyecto está catalogado para todos los mapeadores, pero yo creo que corregir una tarea como esta no está al alcance de todos los mapeadores. Este proyecto ha sido utilizado, al parecer, en mapathones de iniciación. El mapeador principiante pide una tarea aleatoria y el programa le puede adjudicar esa tarea.
Me parece que corregir la mayoría de teselas debería reservarse a mapeadores intermedios o avanzados, mejor mapeando con JOSM que con iD ya que es más fácil seleccionar edificios duplicados o no ortogonales para corregirlos de forma rápida.
Creo que el Tasking Manager debería permitir al validador marcar una tarea con una restricción que evite el mapeo de esa tesela por parte de un mapeador principiante
J’ai été diagnostiqué avec un diabète de type II, il y a de cela deux ans. Il me fallait donc changer certaines habitudes alimentaires et il me fallait faire plus d’exercice. J’ai donc allongé les promenades du chien - mais ce n’était pas suffisant en termes de temps passé - Il me faut faire au moins 40 minutes d’exercice 3 fois par semaine. J’ai trouvé une super motivation avec “street complete” et j’ai commencé à résoudre la plupart des quêtes du village, puis je prenais la voiture durant la pause déjeuner afin de faire les villages alentours. Puis l’été est venu, plus de nouvelles quêtes, plus de motivation et j’ai arrêté.
J’ai récemment repris, mais à vélo ce coup-ci. Certaines nouvelles quêtes m’ont poussé à désormais ajouter des choses que je ne faisais pas avant. Cela m’a permis de faire plusieurs passes sur certains secteurs.
Je cartographie donc :
Je le fais à vélo, sur les petites routes ou personne de passe. Cela me permet de faire l’exercice dont mon corps a besoin.
Nice to belong to this community.
주차장인데 한 곳에서만 요금을 정산하고 다른 입구 또는 출구에서는 차량 진입 시각과 번호판 식별만 하는 경우가 있습니다.
이런 경우 요금을 정산하는 장소에는 당연히 ‘barrier=toll_booth’를 쓰나*** 요금은 받지 않고 차량 식별만 하는 장치에는 ‘surveillance:type’ 태그를 쓰며, 특히 자동 번호판 인식 시스템은 ‘surveillance:type=ALPR’을 씁니다.
osm.wiki/Key:surveillance:type
아마 이 태그는 고속도로에서 ‘구간단속 구간’의 감시카메라에도 쓸 수 있을 듯합니다.(어쨋든 카메로로 번호판을 자동으로 인식하는 모든 곳에…)
다만, 도로에서 달리면서 바로 정산을 하는 비접촉 정산 시스템(가장 쉽게는 고속도로 ‘하이패스’)에는 ‘Open Road Toll’(‘highway=toll_gantry’ 태그)을 씁니다.(주로 도로 끄트머리인 요금소에 함께 있지만 가끔 요금 체계가 다른 도로의 경우에는 나들목에도 있는 경우가 있습니다. 이 경우는 차량 번호판 인식 방식임에도……) 이 경우는 차량 번호판을 인식하는 것이 아니라 다른 정보를 비접촉 태그하는 경우여서 그런 것 같습니다.
*** 중요! 위키문서에서 ‘barrier=toll_booth’ 태그의 경우에, ‘As the charge needs to be in relation to using the road, the tag should not be used for places collecting parking or admission fees’라고 되어 있고 그런 곳은 대신에 ‘barrier=lift_gate’와 ‘fee=yes’를 쓰라고 되어 있는 것을 찾았습니다. OSM 포럼에 물어 놨으므로 결과를 지켜 봅시다. https://forum.openstreetmap.org/viewtopic.php?id=75659
차량 ‘주차’와 관련해서도 ‘주차장’과 ‘주차 구역’을 구분하며, ‘주차 구역’의 경우에도 다양한 항목이 있으니 확인하시압.
osm.wiki/Parking osm.wiki/Key:parking osm.wiki/Tag:amenity=parking
Tag:amenity=parking : 독립된 성격을 가진 주차장(지상, 지하, 다층, 길가, … ) Tag:amenity=parking_space : 주차 ‘공간’. 다른 성격을 가지는 공간과 함께 공존하면서 주차를 목적으로 쓰는 영역?
Edicíos disponibilizados pela Microsoft para o Mapeamento No Brasil.
O Bing Maps está lançando pegadas de edifícios abertos em todo o mundo. Detectamos 777 milhões de edifícios de imagens do Bing Maps entre 2014 e 2021, incluindo imagens Maxar e Airbus. Os dados estão disponíveis gratuitamente para download e uso no ODbL. Este conjunto de dados complementa nossos outros lançamentos.
I nominated the new voting members about 49 of them to become HOT voting members.
I supported my Chapter members with internet data subscription through the help of Mr. Victor Sunday.
I am a co-founder of Oyomappersteam of Uniquemappers network Nigeria. I have trained participants on Missing Map and how to use id editor to map in Open Street Map.
OSM日本コミュニティでは、Plateau建物データのインポートを行うかどうかについて、議論を行ってきました。 user:nyampireは、コミュニティの意見を広く集めるためにアンケートを行い、その結果を公開しました。
全体的な結果についてはOSM wikiに記載されていますが、ここではその結果を少し深堀りしてみたいと思います。
アンケートのなかで、明確な反対、あるいは一定程度の懸念を表明している割合は、以下のとおりです。
| 票数 | 回答 |
|---|---|
| 4 | 条件付きで賛成 |
| 1 | GMLファイルをOSMファイルに変換するcitygml-osmの仕様についてより煮詰め、かつOSM関係者に説明することを条件に賛成 |
| 6 | タイムスタンプは活用すべきである。ソースの写真が古いというのは些細な事。むしろ新しい建築物がインポートで消える方が大ごとです。 |
| 4 | 第1バッチをさらに分割し、ナレッジを蓄積しながら第1バッチを段階的に実施するなら賛成する。 |
| 1 | 反対 |
合計16回答（全75回答, 21.3%）
今回は、これらの方々の属性や意見をもとに、簡単な分析をしてみたいと思います。
反対・懸念を表明しているかたのペルソナを推測するべく、まずはマッピング経験年数から見てみましょう。
| 票数 | 割合 | アンケート全体の割合 | 回答 |
|---|---|---|---|
| 3 | 19% | 20.8% | 10年以上 |
| 7 | 44% | 29.2% | 5年以上10年未満 |
| 3 | 19% | 34.7% | 1年以上5年未満 |
| 2 | 13% | 9.7% | 6ヶ月～1年未満 |
| 1 | 6% | 5.6% | 6ヶ月未満 |
全体傾向と比較して、“5年以上10年未満”の方が多く（29% -> 44%）、 “1年以上5年未満”のかたが少ないことが見て取れます。（34% -> 19%） 10年以上などその他の選択肢は5%程度の違いであり、概ね許容誤差程度の範囲ですので、有意とは言えないでしょう。
5年以上10年未満といえば、だいたい2012年〜2017年頃になります。 これは東日本大震災が発生し、Yahoo!Japanデータインポートが一段落（2015年）した頃にスタートした方、ということです。 インポートによって作成された品質の低い道路の修正や、その頃まだそこまで高品質ではなかった衛星写真を利用して地道に建物を描いてきた方、ということができるでしょう。
そうした方々が建物形状の入れ替えについてどのような印象を持っているか、割合をみてみましょう。
| 票数 | 割合 | アンケート全体での割合 | 回答 |
|---|---|---|---|
| 2 | 12.5% | 44.4% | 積極的に賛成（入れ替えて欲しい） |
| 8 | 50.0% | 44.4% | どちらかといえば賛成 |
| 4 | 25.0% | 8.3% | 形状の入れ替えはNG、新規形状の追加やタグの追加はOK |
| 1 | 6.3% | 1.4% | どちらかといえば反対 |
| 1 | 6.3% | 1.4% | 積極的に反対（入れ替えは絶対NG） |
“積極的に賛成（入れ替えて欲しい）”というかたが有意に少ない（44% -> 12%）ことが見て取れます。 また、“形状の入れ替えはNG、新規形状の追加やタグの追加はOK”、のかたが多くなっています。（8% ->25%） 反対の理由のひとつとして、少なくとも形状の入れ替えには、大小なりの抵抗があるようです。
Wetterpilz : 그야말로 잠깐 서서 햇볕만 피하는 정도.(한국의 건널목에 있는 폭염대피양산?)
‘징검다리’의 경우 ‘highway=footway’ 가운데 징검다리 부분에 ‘‘길’[way]에서 ‘구조물’ 속성은 ‘여울’로 하고, ‘유형’에 ‘stepping_stones’ 속성, ‘노면’에 ‘stepping_stones’을 준다.(태그로는 ‘ford=stepping_stones’, ‘surface=stepping_stones’로 한꺼번에 속성을 줄 수 있다.)
길[way]에서 뿐만 아니라 노드[node]에서도 물길과 만나는 지점에 ‘여울’ 속성을 확인.(ford=yes)
한국에서 교통정책을 맡고 있는 경찰청에서 보행자우선도로를 지정하고 있으나 몇 가지 까닭으로 정착이 안 되고 있다는 보도가 있습니다.
‘보행자우선도로’는 보행자와 차량이 섞여 다닐 수 있는 길로, 단순히 천천히 달려야 하는 ‘주거도로’나, ‘도로’이지만 보행자만 다닐 수 있는 ‘보행자전용도로’하고는 다르게 보행자가 도로 전 구간을 차지하고 걸을 수 있으며 차량은 천천히, 보행자와 거리를 두고 지날 수 있는 곳입니다.
찾아보니 ‘보행자우선’길에는 ‘주택가거리’와 같은 ‘highway=living_street’ 태그를 붙여야 하고 속성에서 ‘도보’와 ‘자동차’에 ‘yes’ 값을 주어야 하는 것 같습니다.
반면 ‘보행자전용도로’에는 ‘highway=pedestrian’, ‘주거도로’는 ‘highway=residential’ 태그로 서로 구분이 됩니다.
(혹시 제가 잘못 알고 있거나 덧붙일 것이 있으면 알려주시면 고맙겠습니다.)
This is my first journal entry on OSM diary. Exciting. Alright, RTK GNSS units are amazing. You can use them in so many different applications, both professional and hobbyist (try doing a quick search on your favourite search engine for example applications)… but they are expensive.
This is how you DIY your own real RTK! You will need to have some knowledge of bash, python, the fundamentals of GNSS, and some interest in troubleshooting.
Last, I should mention that this project will be considerably cheaper than the commercially available options. More on this in the coming sections. I will detail how to make the connections to all the devices and maybe the software setup.
Hello everyone.
Recently, I’ve been trying to map National Recreation Trails in OSM. the NRT program will designate a ‘system’ as a national recreation trail, generally meaning all of the trails within a park or other public land.
I want to represent this on the map, but it seems to be beyond the scope of the type=route relations.
I’ve been considering using this: osm.wiki/Relation:network to try and represent these, but I ran into problems with this as well. I tried interpreting the documentation, but it was written so confusingly that I could not understand how to use this relation on the map at all. I asked on the talk page, but I’m still confused on the meaning of this relation.
Additionally, there are National Recreation Trails designated to places serving ATVs or ORVs. I don’t know if this is some redneck thing that the Europeans don’t have or what, but there was no documented tag for ATV or ORV paths on the wiki. so I also created the page osm.wiki/Tag:route%3Datv. I’ve been working on expanding this page as well.
Right now I’m using type=route for these system NRTs, but I feel that it’s probably incorrect and I’d love input from others.
Thanks, SherbetS
This is an osm.org logout link. Don’t click it:
Hi everyone, my name is Tareq Al-Ahdal. I am a computer science undergraduate student at Universiti Teknologi Malaysia. Recently, I got accepted into Google Summer of Code 2022 as an open source contributor with OpenStreetMap. I will work this summer on enhancing Nominatim: OpenStreetMap’s geocoding software that enables us to search and find location addresses based on their names and vice versa.
Nominatim is currently using a computed importance value to rank the search results based on the location’s perceived importance. This importance value is derived from the popularity of the Wikipedia article of each location. However, not every location on earth has its own Wikipedia article. As a result, the locations that do not have their own Wikipedia articles will not have an importance value, thereby the ranking of the search results, in that case, is deemed inaccurate. OpenStreetMap has data regarding the number of times users accessed each location on the map. This data is a good indicator of how popular a place is. The aim of my work is to integrate this data into Nominam’s computation of the importance value so that the search results become more accurate which will help the users find the correct places that they are looking for in less time.
I will use this diary to keep you updated about my work. Please feel free to reach out if you have any questions regarding my work or anything else you have in mind.
