Today while looking at the hand drawn parcel maps that the county provides I learned the creek that runs through my neighborhood has changed it’s name. On the maps it’s called Sulphur Spring Creek. On all the other maps I’ve seen, road signs, and from what we locals call it, it’s just Sulphur Creek. There’s even a nature center / animal rescue that is named for the creek. They don’t use the spring in their name either.

在中国大陆，OSM 要素的缺失是众所周知的事实。然而，具体的缺失程度如何？哪些要素相对完善、哪些要素更加稀少？“一片空白”的区域又主要分布在哪里？当前，社区对此的认识大多是定性的，少有具体的数据支撑。自己动手，丰衣足食。为此，本文旨在尝试构建一种定量化的评价指标，用于界定某个地区的“空白”程度，比较不同类型要素的缺失程度，此即该地区 OSM 要素的完备性。

然而，何为“完备”实际上是非常主观的判断，对于相同的地理区域，不同需求的数据使用者可能会有不同的判断。例如，一个城市的路网和公共交通被绘制得十分详尽，或是植被和用地类型被划分得尤其清晰，就足够“完备”了么？对 POI 有兴趣的数据使用者可能不会这么觉得。然而，调查的进行仍是需要一个标准，那怕是比较粗断的标准。

思考过后，本文决定将“完备”的定义对象设定在中国大陆具有一定工商业活动和人口聚集规模的最小行政单位——乡、镇和街道等——所应当存在的设施，如道路、学校、医院、建筑等，设定由行政节点和边界、道路交通、公共和商业设施、建筑和土地利用四个维度构成的 OSM 基础要素“完备度”评价指标。这些基础要素既与当地居民的日常生活息息相关，亦与不同绘图者的兴趣有所重合，希望能给各位社区同好寻找补充目标提供小小帮助。

此项工作由个人一时兴起完成，思虑不周之处，还请各位海涵。本文展示的是此项工作的先期结果，涵盖中国大陆 27 个省/市/自治区中的 9 个。后续工作倘若顺利预计会在农历新年前后完成。待全部工作完成以后，本文使用的脚本、示例及数据将会以 GPL-3.0 协议共享于 GitHub，有相关兴趣的读者可以自行取用。如有不当之处，敬请通过评论和私信指出，我会尽量及时更正。

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1 统计对象

1.1 乡镇中心

本文的统计对象限于中国大陆各乡级行政区划的行政中心周边区域，而非整个乡级行政区划的下辖范围，其原因是：

1. 乡级行政中心通常集中了整个区划范围内最多的人口和基础设施，应当作为 OSM 要素和公众兴趣点最多的区域
2. 比较未被普遍标注的乡级行政边界，乡级行政中心的位置容易界定，周边区域范围较小，统计难度较低

具体地，考虑中国大陆普通乡镇的规模，本文将周边区域限定在行政中心所在节点的 1 km 和 3 km 之内，前者用于搜寻人口密集区所需要的建筑、居民道路、医院、学校和商店等设施，后者则用于搜寻可能里行政中心更远的政府机关、大型道路和各种用地类型等。对于行政中心所在坐标，根据 中国大陆地区行政区划标注指北 的建议，其在 OSM应以 place=suburb 或 place=town 标注，因此本文的想法是通过 overpass 接口对齐进行匹配。然而，由于存在 place 节点未被标记，或 name 标签中名字不清晰的情况，完全依赖 OSM 获取乡镇列表及其坐标显然是不合适的。为此，本文将 GitHub 上存档的 2024 年中国全国 5 级行政区划 列表作为参考，使用 overpass 接口尝试匹配 OSM 数据库中相应的节点并从中获取行政中心的位置信息。对于未能匹配到相应节点的乡镇，则由其他地理信息平台（如高德 API）补充其行政中心的位置信息。

在中国大陆，乡级行政区划涵盖街道、镇、乡、民族乡、苏木、民族苏木及县辖区共 8 种类型，但在这 8 种“由民政部门确认的单位”之外，中国大陆还存在数量可观的“类似乡级行政单位”，如开发区、产业园、农场、林场、牧场、兵团等，即俗称的“黑区”。考虑到此类“黑区”在 OSM 中被准确标注的情况寥寥，同时部分“黑区”还可能涉及敏感内容，本文会将其排除在统计范围之外。具体的排除方法则以行政代码为准，即剔除掉列表中乡级行政代码为 400–999 的条目。

截止 2024 年 6 月，中国大陆地区共设有 38672 个乡级行政区划，相关数据的下载、校对周期漫长。因此，本文作为工作的第一部分，选取了北京、山西、吉林、江苏、浙江、湖北、广东、四川、甘肃共 9 个省份展开试验。这 9 个省份的乡级行政区划数量恰好也占到了全国的三分之一，相信对整个中国大陆地区有充分的代表意义。

1.2 基础要素

“基础要素”在本文中是指被纳入统计标准的，应当被标记的各类 OSM 要素，数据类型包含节点、路径和关系共三类。考虑到是在乡镇水平上的统计，以及中国大陆各乡镇现实的标注情况，本文认为“基础要素”的选取要考虑其内容的普遍性，同时标准还不能设立得太高（全是零分的话就没有意义了）。因此，本文的设计思路是：对于中国大陆内陆地区的普通乡镇，里面有什么要素是普遍存在，且当地居民、外地访客、研究学者会共通关注的？基于这个标准，本文目前能想到的有如下内容：

… See full entry

Danh Mục Các Đường Dây 500kV Hiện Hữu

1. Đường dây 500kV Bắc-Nam mạch 1

Chiều dài: 1.487 km

3.437 trụ tháp sắt

Từ: trạm biến áp 500kV Hòa Bình

Đến: trạm biến áp 500kV Phú Lâm

Khởi công: 5/4/1992

Đóng điện: 27/5/1994

Công suất truyền tải thiết kế: 600 – 800 MW

Sản lượng điện truyền tải hàng năm: ≈ 2.000 GWh

Tổng mức đầu tư: 5.488,39 tỷ đồng (~ 544 triệu USD)

2. Đường dây 500kV Bắc-Nam mạch 2

Chiều dài 1.596,3 km

4 dự án độc lập: Pleiku - Phú Lâm, Pleiku - Dốc Sỏi - Đà Nẵng, Đà Nẵng - Hà Tĩnh và Hà Tĩnh - Nho Quan - Thường Tín.

Khởi công: Đầu năm 2002

Đóng điện: 19/4/2004, 30/8/2004, 23/5/2004 và 23/9/2005

Công suất truyền tải thiết kế: 1.300 – 1.500 MW

Tổng mức đầu tư: 7.510 tỷ đồng (~ 476,7 triệu USD)

The Belgian OSM community is importing buildings from governmental data into OSM for some years now. In December I was supposed to present a analysis about this process regarding the import of buildings data from the PICC, the source of data for the Walloon region.

Unfortunately I got sick and I could not present. Anyway, here are some key numbers about this process not only for Wallonia but for Belgium.

The big picture

In Belgium, there are 3 different sources of government data for buildings, each one for the 3 regions of Belgium: Flanders, Wallonia, Brussels. All these sources are integrated in what we call the “building import tool”: the web application buildings.osm.be. People who want to use this tool are encouraged to learn about the import process and to conflate (merge) with existing buildings. In many places indeed, there are already buildings in OSM and integration of every single imported building with existing ones is the preferred way, rather than “delete and replace”. We also ask to not blindly trust official data and to always look if current data in OSM does not bring interesting added value in terms of accuracy and/or local knowledge. After all, it is one of the key force of OpenStreetMap.

What are the lessons

Having imported thousands of buildings myself in the past 3 years using this tool, I found some weird situations in the government data: oddities in house numbering, strange shapes of buildings compared to aerial imagery, etc. Honestly, these are very rare situations, but still it might be interesting to report it to the administration. What is more frequent are update of buildings compared to official data: during the import, by comparing with the aerial imagery or local knowledge, one can find some new buildings, or demolished ones, or some changes in the building outline.

For other opinions, see this thread: https://community.openstreetmap.org/t/feedback-about-the-buildings-import-process-for-the-picc/138241

… See full entry

In regards that the tool https://wiki.openstreetmap.orgdata.link works best with smaller administerey areas I will break it down on the municipality level(Kommun in Swedish) we have 290 in Sweden.

Goal:

To be served a table which have the following data:

municipality(kommun)	Amount of linked lakes	Total amount of lakes	Precentage
Total amount of municipality(kommun)	Total amount of linked lakes	Total amount of lakes	Total Precentage

Main category of all lakes in Sweden on sv.wikipedia.org:

• Kategori:Insjöar i Sverige

The catgory I will use to get total amount of lakes in each municipality(kommun)

Kategori:Insjöar i Sverige efter kommun

Approach

I will then query each municipality(kommun) using Sophox in the SPARQL language on each municipality(kommun) (by name). I will then get a list of QID of all the wikidata lakes that I then can use to ask Sophox if any element has that wikidata QID. If anyone has that

Acknowledged drawbacks/limitations of this strategy:

1. This database query will not detect cases which multiple elements in OSM has the same QID. The tool https://wiki.openstreetmap.orgdata.link will make you aware of this but not i a table which can give you an overview. For that it is best to update the code at that project, see issue #680 I created in it´s repostory.

Where does the data off the lakes come from in wikidata?

They are inported some time the last 10 years from the national database of lakes and bodies of water called VISS Bots created the articles on Swedish wikipedia from this database and this is the reason we now can link the data from OSM to the wikipedia articles through the wikidata QID on the https://wiki.openstreetmap.org/wiki/Tag:water=lake polygons(enclosed ways/areas and multipolygons).

Why didn´t I just use the Overpass Turbo API?

… See full entry

Merry Christmas!

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Part 1

Hi! I’m @likeToTravel, and I suck at writing, so I’m gonna go straight to the point:

THE LIST

Pascal Neis Stuff:

• OSMviz. I use this to visualize my changes because I am so dumb, I don’t understand OSMCha (hence, you won’t find OSMCha on my list). To see a changeset, go to the link and add the changeset number after ?c= in the link. Or, just go to…
• Find Suspicious OpenStreetMap Changesets. This is very useful to find changesets that asked for help. You can also have a link directly to that changeset’s OSMviz or Achavi page.
• How did you contribute to OpenStreetMap? (aka hdyc). Cool because you can visualize any user’s stats.
• OSMstats. It’s cool because it has a lot of stats, for lack of a better word.
• OSMfight. Funny :)

Overpass & other:

• Overpass Turbo. I use this to create challenges on MapRoulette, which is cool, but it also has some other interesting uses.
• Achavi. Better version of OSMviz! Basically the same, even the link thing I was talking about with the changeset number.
• OSM Buildings. It’s just cool.
• OSM Lane Visualizer. This helps me a lot with understanding any tag that starts with turn, especially https://wiki.openstreetmap.org/wiki/Key:turn:lanes& https://wiki.openstreetmap.org/wiki/Key:turn:lanes:*.

Honorable Mention

To my hikers, OSM Destination Signs.

Sono entrato da poco nel magico mondo di open street map, e sto cercando di mappare il mio quartiere in maniera più precisa possibile di capirne sempre di più, ma non posso fare altro che chiedermi sono solo a mappare nella mia città? esistono mappatori di Palermo con i quali è possibile scambiare opinioni e consigli ?

I´m trying to start a project to learn SPARQL to be able to get on how many of the 63 00 lakes which are in swedish wikipedia/wikidata has their wikidata tag on the OSM element. If the OSM element contains the wikidata tag we can show the proper zoomed polygon in the template sidebar on the articles in all their glory, instead of just a coordinate from wikidata. Mall:Insjöfakta Sverige is the template which makes this possible, please share it for other purposes to use the maplinked feature on other WMF Wikipedias than sv.wikipedia.org!

Why is it so good with mapframes/maplink maps in wikipedia infoboxes?

https://en.wikipedia.org/wiki/Wikipedia:Why_mapframe_maps%3F

Part 2

Honestly, I have been reading everybody’s diary entries and diving in and looking at all the different areas and detail and I forgot how I even got here! NO idea but I am very intrigued I do not know how much I will have to contribute but I’m determined to figure this all out! I’m fresh meat here amd have never heard of openstreetmap until I landed in the middle of Nigeria very far from home…safe travels and Merry Christmas from Michigan 🇺🇸💋

Love and Light Aphrodite888

I was doing some Unmapped Small Town USA work this evening, and realized that I had tagged a bunch of probable grain silos in other areas as buildings, specifically in Arbela, MO, and Granger, MO, so I’ve gone back in and corrected those to more accurately reflect their purpose. Apologies to Arbela and Granger!

Otherwise, Dover, KY showed up on Unmapped Small Town USA. There’s some great progress already, but still more to do, so I’m taking advantage of some holiday downtime to fill in more buildings.

Otherwise, I hope you have a lovely Christmas Eve, if that is your custom, and a lovely Christmas Day, if that is your custom. If not, I hope you have a very Merry Thursday. :)

নাগা বাজার রাজশাহী জেলার বাগমারা উপজেলার কাতিলা গ্রামের একটি গুরুত্বপূর্ণ বাজার। নাগা বাজার থেকে প্রায় ১৬০০ মিটার দূরে অবস্থিত কাতিলা সবুজ সংঘ হাই স্কুল ও কলেজ, যা স্থানীয় শিক্ষার্থীদের জন্য উচ্চ মাধ্যমিক ও কলেজ পর্যায়ের শিক্ষা প্রদান করে।

বাজার ও স্কুলের ঘনিষ্ঠ অবস্থান এলাকার শিক্ষার সাথে বাণিজ্যিক কার্যক্রমকে সংযুক্ত করে। এই দুই কেন্দ্রের ম্যাপে Node ও Area হিসেবে যোগ করা OSM ব্যবহারকারীদের জন্য এলাকাটিকে সহজে চিহ্নিত ও বোঝার সুযোগ তৈরি করে।

১৫ নং যোগীপাড়া ইউনিয়ন পরিষদ বাগমারা উপজেলার কাতিলা গ্রামের এলাকায় অবস্থিত। এটি নাগা বাজার থেকে প্রায় ১৫০০ মিটার দূরে অবস্থিত। ইউনিয়ন পরিষদ স্থানীয় প্রশাসনিক কার্যক্রমের কেন্দ্র হিসেবে কাজ করে। এখানে ইউনিয়নের বিভিন্ন সরকারি সেবা, নথি, পরিকল্পনা ও নাগরিক সেবা প্রদান করা হয়। নাগা বাজারের সাথে ঘনিষ্ঠ অবস্থানের কারণে এটি এলাকার মানুষের দৈনন্দিন জীবন ও বাণিজ্যিক কার্যক্রমের জন্য গুরুত্বপূর্ণ।

Suite à la découverte du projet “Surveillance under Surveillance” grâce à @apitux, je cartographie les systèmes de videoprotection et de videosurveillance dans le Haut-Mâconnais.

Pour voir le résultat (impressionnant) : suivre de lien.

Số nhà

It is both weird and cool to see the map of my community change in apps I use regularly. Before I started actively updating things in OSM I didn’t recognize all the places OSM is used.

Last November, I [Re]Introduced Ultra v3 which introduced a bunch of new features. Today, I’m happy to share what’s changed in Ultra over the past year.

Since my last update, I’ve implemented the following features in Ultra:

• Many new styling features enabled by continued MapLibre updates
• Sprite support updates
• A new Overpass/OSM XML&JSON-to-GeoJSON conversion library
• More basemap styles & style previews
• More export options
• Transforms
• More providers
• An “Open with Ultra” bookmarklet

🌍 MapLibre updates

In January of 2025, Ultra updated to the freshly released MapLibre v5, introducing globe support! View Example

Since then, further MapLibre changes have enabled a host of new styling features including:

• color-relief styling from raster DEM sources
• Data-driven line-dasharray support
• Improved font support
• New hillshade methods

📍 Sprites

I’ve added two sprite-related features to facilitate map styling:

SVG Support

… See full entry

As a principle, I’ve always tried to use open-source software over proprietary software for any of my digital needs. I’ve personally found open source to be both more accurate and more sensible to use than proprietary alternatives.

One of the very few aspects of my life that had still not adopted open source was maps. I always used both Waze and Google Maps for everything. But whenever I looked at the maps, it felt like something was missing. I looked around, checked the environment, and realized how much of my surroundings simply wasn’t reflected on the screen.

I wanted to fix it, but… Google Maps doesn’t allow you to just add things. And while Waze does have an editor, it’s extremely locked down for the average user. So, I looked up online alternatives.

I discovered OpenStreetMap two months ago, and I found myself in awe of the sheer amount of detail… Far more than Google Maps or Waze could offer. It just so happened that I was on a trip to Barcelona, and I was using CoMaps to navigate. Using CoMaps proved extremely reliable, especially for public transportation. I never missed a metro, I found all my destinations quickly, and it was very easy to get around.

Still riding the Barcelona high, I opened CoMaps back at home and was fairly shocked to see that my neighborhood didn’t exist at all… Where the heck is it?!

So, I got on my computer, logged into OpenStreetMap for the first time, and started using the iD editor. In just a few hours, the rough outline of my neighborhood was there.

Soon enough, I found myself mapping for hours. Even during lectures, I’d have an OSM tab open for casual mapping. Then it escalated. I started bringing my laptop everywhere I traveled to map things on the go. I began using StreetComplete to add missing metadata. I took pictures and videos. Then I started recording GPS traces. And now I’m even considering setting up a full LiDAR mapping mount for my car…

… See full entry

• Приказ Министерства образования и культуры Калужской области от 27.08.2008 N 1506 “О выявленных объектах культурного наследия, расположенных на территории городского округа “Город Калуга” (вместе со “Сводным перечнем выявленных объектов культурного наследия, расположенных на территории городского округа “Город Калуга”)

OSMWrapped is a fun tool that visualizes your personal OpenStreetMap (OSM) mapping statistics — including edits made, countries mapped, and active mapping days.

Today I’m celebrating one full year of mapping every single day! 🎉🥳

Grateful for the OSM community and the joy of contributing, one edit at a time.

Cheers!

93/93

আজ আমি আমার স্থানীয় এলাকা নাগা বাজার OpenStreetMap–এ যুক্ত করেছি। এটি একটি গুরুত্বপূর্ণ স্থান, কারণ নাগা বাজারের আশেপাশের জনগণ দৈনন্দিন জীবনযাপনের জন্য এই স্থানটি ব্যবহার করে।

নাগা বাজারের বিশেষত্ব হলো এটি তিনটি গুরুত্বপূর্ণ সড়কের সংযোগস্থল। এই সড়কগুলো হলো:

নাগা বাজার – মুলিভিটা সড়ক

নাগা বাজার – বীরকুৎসা সড়ক

নাগা বাজার – ভবানিগঞ্জ সড়ক

এই তিনটি সড়ক এলাকার মানুষকে একে অপরের সাথে সহজেই সংযুক্ত করছে এবং স্থানীয় বাণিজ্য ও যোগাযোগে গুরুত্বপূর্ণ ভূমিকা পালন করে। আমি OpenStreetMap–এ নাগা বাজার যুক্ত করার সময় এ সমস্ত সড়ক ও এলাকাসহ বিস্তারিত তথ্য দিয়ে কাজ করেছি।

এটি আমার ব্যক্তিগত ডায়রিতে সংরক্ষণের জন্য একটি গুরুত্বপূর্ণ অর্জন। OpenStreetMap–এ স্থান যুক্ত করার মাধ্যমে স্থানীয়দের জন্য তথ্য সহজলভ্য হবে এবং ভবিষ্যতে মানচিত্র ব্যবহার ও রাস্তাপথ পরিকল্পনায় সহায়ক হবে।

নাগা বাজারের সঠিক স্থান, ল্যাটিটিউড ও লংগিটিউড, এবং সংযুক্ত সড়কগুলো OpenStreetMap–এ উল্লেখ করার মাধ্যমে স্থানটি আরও বেশি কার্যকরভাবে চিহ্নিত হয়েছে। এই কাজ আমার জন্য শিক্ষণীয় এবং এলাকার ডিজিটাল নথিপত্র তৈরিতে সহায়ক হয়েছে।