I worked on Norse and Orchard in Golden Colorado. The area could use some mapping love.

Info from:

https://gis.jeffco.us/webmaps/pzpublic/index.html

আজ আমি রাজশাহী জেলার বাগমারা উপজেলার কাতিলা গ্রামে অবস্থিত নাগা বাজার এলাকায় মাঠ পর্যায়ের পর্যবেক্ষণ (field survey) পরিচালনা করি। নাগা বাজার–মৌলভীবিভা সড়ক দিয়ে চলাচলের সময় লক্ষ্য করি যে, প্রধান সড়কের পাশে একটি গ্রামীণফোন সেলুলার টাওয়ার স্থাপিত রয়েছে, যা এখনো OpenStreetMap-এ সঠিকভাবে চিহ্নিত ছিল না।

মাঠ পর্যায়ে অবস্থান নিশ্চিত করার পর আমি টাওয়ারটির সঠিক লোকেশন নির্ধারণ করি এবং OpenStreetMap-এ একটি নতুন পয়েন্ট (node) যোগ করি। ম্যাপিংয়ের সময় টাওয়ারটির ধরন, অপারেটর ও নেটওয়ার্ক তথ্য যাচাই করে যথাযথ ট্যাগ ব্যবহার করেছি, যেমন—communications_tower, operator=Grameenphone এবং tower:type=cellular।

এই টাওয়ারটি নাগা বাজার এলাকার মোবাইল নেটওয়ার্ক কভারেজ নিশ্চিত করতে গুরুত্বপূর্ণ ভূমিকা রাখছে। স্থানীয় ব্যবসা প্রতিষ্ঠান, বাজারের দোকানদার ও আশপাশের বসতবাড়ির মানুষ প্রতিদিন এই নেটওয়ার্কের উপর নির্ভরশীল। তাই টাওয়ারটির অবস্থান ম্যাপে যুক্ত হওয়ায় ভবিষ্যতে ডিজিটাল ম্যাপ ব্যবহারকারী, গবেষক ও জরুরি সেবাদানকারী সংস্থার জন্য তথ্যটি উপকারী হবে বলে আমি মনে করি।

গ্রামীণ এলাকার গুরুত্বপূর্ণ অবকাঠামো OpenStreetMap-এ যুক্ত করার মাধ্যমে স্থানীয় এলাকার ডিজিটাল দৃশ্যমানতা বাড়ানো সম্ভব। ভবিষ্যতেও নাগা বাজার ও আশপাশের এলাকায় রাস্তা, শিক্ষা প্রতিষ্ঠান ও অন্যান্য গুরুত্বপূর্ণ স্থাপনা ম্যাপিং করার পরিকল্পনা রয়েছে। Location: Naga Bazar,Katila, Bagmara Upazila, Rajshahi Source: Field survey Mapped features: Mobile communication tower (Grameenphone)

I am going to make some improvements to the Walla Walla Washington area over the next week. I’ve just found the Rapid editor uses the Microsoft Building Footprint data to suggest features. That’s excellent. Speeds things up significantly.

I worked on Lloy street today in Portage MI. It could use some mapping love. Streets are there but not much else.

Porage GIS: https://mi-portage.civicplus.com/177/GIS-City-Maps

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.

OK… after getting the comment re sulfurous springs, I did some digging. I haven’t found any historic proof of the claim in this article from last year, but …

“Nestled in the Hayward hills, the Sulphur Creek Nature Center is home to dozens of birds, amphibians, reptiles and mammals, including a coyote and a fox. The site straddles a small section of Sulphur Creek, named after the sulphur water bubbling up from nearby springs. In 1970, H.A.R.D. acquired the property, then a wellness retreat, and transformed it into the animal sanctuary it is today.”

The “spring” part of the creek is shown to be at the current location of the nature center. The other creeks that feed into it have been conflated into all being “Sulphur Creek” I suppose.

https://tricityvoice.com/sulphur-creek-nature-center-completes-renovation/

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。报告本身欢迎以 CC BY 4.0 协议转载 。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”。考虑到乡镇级的此类“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，存在行政代码和下辖单位的县级及以上黑区则予以保留。

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

… 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:*.
• Go Map!!. OSM Editor for iOS and iPadOS! I don’t use Android, so this is my best option. The UI is weird, and you really need to know your tags if you want to map here, but apart from that, it can also do GPS Traces, which works insanely well with Shortcuts (it is an app).

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

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