Introduction

Humanitarian Openstreetmap Team (HOT) is an international team dedicated to humanitarian action and community development through open mapping.

Accurate and up-to-date data is essential for effective humanitarian response. Validators use tools such as JOSM and the HOT Tasking Manager to identify and flag errors and mistakes. From experience, i know that this is a complex and time-consuming endeavor.

One tool to save time and enhance the validation process is OSMCha.

The funding for OSMCha is currently at risk, which could lead to the degradation of this invaluable tool. In this diary, i want to highlight the essential role OSMCha plays in my own (and other’s) validation and quality maintenance workflow.

What is OSMCha

OpenStreetMap Changeset Analyzer (OSMCha) is a tool designed to monitor and analyze changes made to OpenStreetMap data. It enables data validators to quickly identify potential issues, track changes, and ensure data quality.

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peraia δευκαλιωνος 35

Здание ГИБДД заброшено.

Координаты 57.189472, 39.42346

Halo, saya Mulyawan asal Indonesia, aktif di OpenStreetMap

Здание заброшено, Ростовский МО МВД переехало на ул Февральская .

Координаты 57.190312, 39.427535 Дом снесён

Ярославская область, город Ростов Великий, улица Бебеля Координаты 57.190766, 39.428734, Дом сгорел полностью, место заросли кустарники, деревья

In collaboration with a local team in Grünstadt, Mannheimer Mapathons e.V. completed the mapping of the historic Jewish cemetery in early 2024 after five months of data collection. The cemetery was used by the important Jewish community from around 1700 to around 1937 and comprises 464 gravestones that are still visible. A high-precision Sparkfun RTK Facet GPS receiver was used for the survey. A map has been available online since May 2024. In recent weeks, with the support of the Heidelberg University of Jewish Studies, the names and dates of many of the oldest purely Hebrew gravestones have been catalogued and integrated into the map data. The translation work will continue with the aim of supporting both descendants and historical research.

In Zusammenarbeit mit einem lokalen Team in Grünstadt hat Mannheimer Mapathons e.V. nach fünf Monaten Datenerhebung Anfang 2024 die Kartierung des historischen jüdischen Friedhofs abgeschlossen, berichtet RCD49. Der Friedhof wurde von der bedeutenden jüdischen Gemeinde etwa von 1700 bis ca. 1937 genutzt und umfasst 464 noch sichtbare Grabsteine. Für die Erfassung kam ein hochpräziser Sparkfun RTK Facet GPS-Empfänger zum Einsatz. Seit Mai 2024 ist eine Karte online verfügbar. In den letzten Wochen wurde mit Unterstützung von der Hochschule für Jüdische Studien in Heidelberg begonnen, Namen und Daten von vielen der ältesten rein hebräischen Grabsteine zu erschließen und in die Kartendaten zu integrieren. Die Übersetzungsarbeit wird fortgesetzt, mit dem Ziel, sowohl Nachkommen als auch historische Forschungen zu unterstützen.

I have continued mapping Happy Valley Goose Bay. I noticed that the ESRI world imagery isn’t particularly good. I could do with some more or better data, and I may have to do some drone flights to get it.

I have also started to reach out for data in the surrounding towns.

Bliss

133000延吉市区（进学、新兴、北山街道）、小营镇东郊部分（光明、光进、小营、新光村）

133001延吉市区（河南、建工街道）、小营镇南郊部分（东光、东新、东明、东风、仁坪、吉兴、新光、新农、河龙、理化、长东）

133002延吉市区（公园街道）、小营镇西郊部分（民主、吉兴、果树村），依兰镇北郊部分（发展、大成、实现村）

133003依兰镇（原烟集乡下辖的兴农、利民、台岩、龙渊村）

133004依兰镇（九龙、古城、平安、春光、东兴、北大村）

133005三道湾镇（镇区、五道、梨树、东沟、平岗村）

133006三道湾镇（南张芝、北张芝、屯田、支边村）

Transjakarta, jaringan rute Bus Raya Terpadu (BRT) terpanjang di dunia ini menjadi tulang punggung transportasi umum di dalam Kota Jakarta. Dengan ratusan rute dan ribuan kendaraannya, Transjakarta menjadi bagian penting dalam identitas Kota Jakarta. Namun sayangnya, data rute dan infrastruktur pendukung Transjakarta kurang diminati untuk dipetakan. Hal ini mendorong saya untuk memetakan Transjakarta, setidaknya jaringan koridor utamanya terlebih dahulu.

Mengenal sistem Transjakarta

Transjakarta merupakan sistem jaringan bus kota di Jakarta. Ditinjau dari rutenya, rute Transjakarta terbagi menjadi dua, yakni rute BRT dan non-BRT. Rute BRT merupakan rute yang berjalan sepenuhnya di jalur khusus dan hanya berhenti di halte BRT. Sementara itu, rute non-BRT merupakan rute bus kota yang melayani halte di pinggir jalan dan biasanya tidak melewati jalur khusus. Sebagian kalangan membagi lagi rute non-BRT menjadi rute non-BRT yang juga melayani halte BRT dan rute yang sama sekali tidak melayani halte BRT (sepenuhnya melayani halte biasa di pinggir jalan).

Jalur khusus yang dimaksud pada kenyataannya tidak benar-benar “khusus”. Sebagian jalur khusus memang memiliki pembatas atau separator untuk memisahkan jalur untuk bus dan kendaraan lain. Namun, sebagian lainnya hanya berupa jalan yang diberi marka, sehingga pada kenyataannya juga dipakai oleh kendaraan lain. Sebagian lainnya bahkan tidak memiliki penanda apapun, sehingga bus “BRT” berjalan di jalan yang tidak memiliki perlakuan khusus apapun terhadap bus Transjakarta.

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This is a compilations of what I sent to other people.

I have taken it from the cadastre at (https://seduvi.cdmx.gob.mx/programas-delegacionales-de-desarrollo-urbano), I was extremely surprised that CDMX’s cadastre has not being used because it is in the public domain (“Este programa es de carácter público, no es patrocinado ni promovido por partido político alguno y sus recursos provienen de los impuestos que pagan todos los contribuyentes.”) You only need to credit the source: “Agencia Digital de Innovación Pública “Sistema Abierto de Información Geográfica (SIGCDMX)” Disponible en: https://sig.cdmx.gob.mx/”.

After reading osm.wiki/Import/Guidelines, I will make a import page for CDMX data to serve as a documentation for where the data comes from.

Step 1

I download the data from (https://sig.cdmx.gob.mx/datos/descarga). There are two types of data there, the actual cadastry data “Descarga de datos del catastro” and landuse data “Descarga de datos SEDUVI”. The cadastry data is basically a bunch of points and I find that the only useful data there is the address data, which is fairly inaccurate.

It is better to download the landuse data since it has the polygons to work with. I download the shapefile from the “Descarga de datos SEDUVI” section. I’m working at Cuauhtémoc alcadia because it is the central alcadia of CDMX

Generally, since houses in Mexico are connected to each other, often the landuse is the building footprint itself. But, for more complex places like schools, churches, hospital, government areas, etc. it only covers the surrounding of the complex.

Step 2

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휴식을 취하고 거북섬을 지도에 표시했습니다.

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한국어

저는 건물 중 2층에 난간을 생성하고 싶었는데, f4map demo에서 보니 난간이 엉뚱하게 1층에 생성되어 있었습니다. 2층에 난간을 생성하려면 어떻게 해야 하나요? (참고로 2층은 테라스입니다) 참고 사진: https://ifh.cc/v-x6kwaD

English(by Google translator)

I wanted to create a railing on the second floor of a building, but in the f4map demo, the railing was created on the first floor. How can I create a railing on the second floor? (For reference, the second floor is a terrace.) Reference photo: https://ifh.cc/v-x6kwaD

Map update during Summer Holidays mostly using StreetComplete, Osmand, JOSM

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Hello!
I’ve been mapping in OpenStreetMap for a few years now, and I believe the current method of mapping routes is quite painful and wastes hours of editors’ times to just upkeep it, So, here is my idea on how we could fix it.

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The Idea

In essence, it is to have just one start node and one end node, the router (using the bus profile) then calculates the route deterministically, with additional points in between added only as needed to achieve the desired path.

For example, in the case above, the route can be simplified from 123 ways down to just 5 nodes representing the path. (In reality there would be nodes at every station, so it wouldn’t be as few as 5)

This approach is;

• Resilient to edits,

• So many times easier to maintain.

I’ve compiled Valhalla on Linux and created a quick proof of concept program showing this can already be implemented (unofficially) in custom code.

… See full entry

Riau: Empat Sungai Raksasa

Pembukaan

Dua hingga tiga abad sebelum kita mengenal provinsi yang bernamakan Riau, dahulu para pelaut mengetahui daerah ini sesuai dengan nama sungai besar yang ada. Sungai Rokan, Siak, Kampar, dan Indragiri, terkenal dengan sumber daya yang mereka bawa ke berbagai pusat perdagangan di Selat Melaka. Kedatangan Portugis ke Melaka dianggap sebagai titik mula nama ‘Riau’ terdengar, karena kata ‘Sungai’ dalam bahasa Portugis adalah ‘Rio’. Mungkin penjajah Portugis pada zaman itu tidak bisa mengucapkan nama-nama sungai tersebut dengan baik, dan perubahan simpel dengan merujuk mereka sebagai ‘orang-orang sungai’ lebih mudah bagi mereka untuk diingat.

Tiap sungai ini mempunyai sejarah & ciri khas-nya tersendiri, dan diary ini akan mencoba untuk menjelaskan secara singkat tentang keberadaan empat sungai besar yang ada di Riau.

Rokan: Sungai Kejayaan

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My OSM Wiki

About Me

I am Brazil Singh, an open mapping advocate, digital innovator, web developer, and community leader from Bangladesh. As an Open Mapping Guru at the Open Mapping Hub Asia-Pacific, I equip communities with practical and impactful mapping skills. I play a key role in managing social media for the OSMF, and actively contribute as a volunteer in the OSMF Local Chapters and Communities Working Group (LCCWG).

As a dedicated mapper, trainer, community organizer, and advocate, I have worked with the OSM ecosystem at local, regional, and international levels. From mapping in flood-affected areas of Thailand to mentoring YouthMappers across Asia and beyond, to volunteering with HOT and the OSMF Communication Working Group, I have seen firsthand how collaboration can create meaningful impact.

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State of Michigan

• Harrisville (from 2011 to now)
• Harrisville State Park (from 2011 to now)
• Sault Ste. Marie (2021)
• Tahquamenon Falls State Park (unknown)
• Pictured Rocks National Lakeshore (2021)

State of North Carolina

• Lake Lure (2022)
• Chimney Rock (2022)

State of Wyoming

• Yellowstone National Park (2020)