I’m excited to announce that today we released Rapid v2.3 editor for OpenStreetMap! The Rapid team has been busy working on this for the past few months - here’s 4 new features that we hope you’ll love…

🔙 Esri Wayback imagery

The world never stops changing! We added a new background layer called “Esri Wayback” to let you view historical releases of the Esri World Imagery. This background source also has a date picker to help you choose from dates likely to show changes in the current map view. Open the Background pane to try it out!

🔄 Map Rotation

Take Rapid for a spin! Now you can rotate the map to make your editing easier (and avoid straining your neck!). Rapid supports rotating with option+click-drag or shift+←/→ arrows, just like other maps you’ve used before. A new bearing control displays a north arrow, and you can click it to reset the map back to North-up.

✅ MapRoulette Integration

You can now complete MapRoulette tasks without ever leaving Rapid. View active MapRoulette tasks in the current map view, or filter the results by challenge id. After making your edits, select the task and click “I fixed it!”, “Can’t Complete”, “Already Fixed”, and “Not an Issue”. When you save your edits, your changeset will automatically include a description about any MapRoulette tasks that you’ve completed.

🎨 GeoScribbles

GeoScribble is a new service that allows mappers to take field notes while surveying with the EveryDoorOSM mobile app. Your sketches and notes will be waiting for you when you get back to your computer and open Rapid.

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We’ve got lots more planned, and we’re excited to hear how the community is using Rapid to map more efficiently.

• ☝️ Make Rapid your OSM editor! Bookmark rapideditor.org/edit and make it your daily mapping tool of choice.
• ✌️ Want to help us make Rapid better? Follow us on Github at https://github.com/facebook/Rapid or find us on any of the various social media or OpenStreetMap community channels. We’d love to hear your thoughts!

Happy Mapping 👍

1. Introduce blocks that prevent editing in selected areas, e.g. a country, an administrative unit (editing controversial objects in the field), and not the entire world. Now I can’t improve my neighborhood due to controversial editions in Ukraine.
2. Comments on your profile should link to a page where your changeset comments are located, not to log comments.
3. The link to your first edits in OpenStreetMap is intended to understand the difficulties for a beginner editor.
4. Links to apps and websites related to OpenStreetMap from main page (with map) e.g.: MapRoulette, how did you contribute to OpenStreetMap?, osm-revert.

collaborative live mapping of regions affected by rain in Rio Grande do Sul - Brazil.

Today we are going to map the area that was affected by the rains in the state of Rio Grande do Sul, there will be a live broadcast at 7:00 pm where everyone can map and help with mapping the affected area.

task link. MAPPING OF ROADS IN THE AREA AFFECTED BY THE FLOOD OF THE PARDO RIVER IN CANDELÁRIA-RS https://tasks.hotosm.org/projects/16696

Youtube: https://www.youtube.com/watch?v=3Wm-nTnCRaQ&t=7s

organization: UFV youthmappers UMBRAOSM

live collaborative mapping in the affected areas of RS

Greetings!

We are thrilled to share some exciting news from OpenStreetMap Bangladesh (OSMBD). For the first time ever, the OSM Bangladesh community has successfully formed an elected Executive Committee, consisting of a team of dedicated individuals who will guide our community’s activities and initiatives.

We are proud to introduce the newly elected Executive Committee:

President: S M Sawan Shariar

Vice-President: Atikur Rahman

Secretary: Samsul Arafin

Treasurer: Nahid Ferdous

Member-at-large: Mehedi Hasan Ovi

Member-at-large: Afia Tahmin Jahin

Member-at-large: Laila Sharmin Nova

The committee is committed to upholding OSMBD’s core values of collaboration, community-driven initiatives, openness, and accessibility. Our focus is on promoting the use and development of OpenStreetMap in Bangladesh, building and maintaining a comprehensive map of Bangladesh that is freely accessible, and supporting OSM groups and initiatives through training, events, and more.

We would be delighted to collaborate with you on OSM-related projects in Bangladesh. If you need any assistance or guidance, or if you would like to collaborate on OSM-integrated activities, please do not hesitate to reach out to us at our central email communication address: info.osmbd@gmail.com

For ongoing updates and discussions, we invite you to subscribe to our Talk BD channel through the following link: https://lists.openstreetmap.org/listinfo/talk-bd

We appreciate your support and collaboration in advancing the use of OpenStreetMap in Bangladesh and look forward to working with you to achieve our shared goals.

Thank you for standing with the OpenStreetMap Bangladesh community.

Cheers!

Sawan Shariar

President (Elected), OpenStreetMap Bangladesh

https://en.wikipedia.org/wiki/Web_colors

Hello OSM World,

Welcome to #WOSMinGhana 000

I am starting a series of OSM Diary posts title Worst of OSM in Ghana, inspired by best and worst of OSM posts I have seen. The idea is to share one photo per week (I hope I can keep up, feel free to share any you might have seen in Ghana too :D). i.e. Before and After (if I am able to improve or fix it)

Sometimes you come across very interesting mapping activities and data and you are out of words. Myself and other volunteer mappers have taken screenshots of worst contributions on OSM in Ghana over the years and then proceeded to improve them / notify mappers or organizations.

Why talk about the worst not the best? Highlighting these worst mappings might help create more awareness about what we put out there as part of individual or organized mapping activities.

This is purposely to help improve OSM data in Ghana in these areas by myself or other mappers and for us all to beware of when mapping.

Looking forward to the coming weeks.

Introduction

Humanitarian logistics is defined as the process of planning, implementing and controlling the efficient, cost-effective flow and storage of goods and materials, as well as related information, from the point of origin to the end of consumption to alleviate the suffering of vulnerable people

Its Extent and Impacts

The humanitarian logistics of peace operations in sub-Saharan Africa is one of the most challenging operations in the contemporary world. Faced with this reality, several scenarios challenge conventional logistical practices translated into humanitarian efforts on the African continent. Several events have led Africa to the current situation, whose conflicts have worsened the case in some countries. In this scenario, three countries stand out on the African continent: South Sudan (SS), the Central African Republic (CAR) and the Democratic Republic of Congo (DRC).

1.Positive Impacts

Data Collection and Mapping - GIS technology is used to collect, analyze, and visualize geospatial data. Humanitarian organizations in South Sudan leverage GIS to map various elements such as population distributions, events, infrastructure, health facilities, water sources, and more. This comprehensive mapping enables organizations to identify vulnerable areas and better understand the needs of the population.

Situation and Needs Assessment - OSM aids in conducting rapid situation assessments and needs analyses during crises and emergencies. Each region in South Sudan is prominently represented by one or the other ethnic and communal group, each with its own methods of action. By overlaying various data layers, including demographic, environmental, and public infrastructure, organizations can quickly identify areas that require immediate specialized attention and allocate resources accordingly.

Resource Allocation and Planning - OSM enables efficient resource allocation. Humanitarian agencies can determine the best locations for setting up relief distribution centers, medical clinics, or emergency shelters based on the data. This leads to more effective and targeted assistance.

2.Reccomendations

Collaborative efforts between various organizations and government agencies in Democratic Republic of Congo have to leverage Open Street Mapping for humanitarian work, contributing to more effective disaster response, and conflict mitigation. These partnerships have been crucial in addressing the complex challenges in the region.

Link

My profile

Keep removing my edits.. go ahead. I can just waste my time and add them back. I have no problem doing that.

Welcome to my fifth (and a half) OpenStreetMap NextGen development diary.
Tomorrow, I’m returning home and I’ll be able to resume work at full speed 🔥.

This is a short edition of the development diary.

🐙 This project is open-source and publicly available:
https://github.com/Zaczero/openstreetmap-ng

Intro

For the past 13 days I have been on a journey of finding a new place to rent. Without my home office, I wasn’t able to become productive. The place I’m staying at doesn’t have a good office spot and being on my laptop doesn’t help. However, I am now very motivated to get back to work and push even harder!

May Will Be Big

At the end of May, OpenStreetMap-NG will include necessary functionality to run on a testing server, as well as to invite new contributors into the project. Starting with 6th of May, I won’t have any time-consuming plans for this month so I’ll do my best to wrap everything up. What’s exactly left has been described in Diary #5 Short-Term Development Plan. I have already started to prepare the All-in-One Contributor Guide which will also be finished up (it currently lacks backend/frontend-specific guides). This is going to be the first major milestone of the project!

Project Sponsors 🏅

I was happily surprised to see new faces even during my lower activity period. I will do everything to deliver the promised results. As always, thank you for supporting the project, monetarily, and with staring the project on GitHub!

Currently, the project is sponsored by 13 people!
Five private and four public donors on Liberapay, and four public on GitHub Sponsors.

• ~1847430, gileri (Eric G.), LaoshuBaby (快乐的老鼠宝宝), RedAuburn (Harry Bond), ~1819511, AurimasF (Aurimas Fišeras), edpichler (Edu), starsep

Disclaimer

This project is not affiliated with the OpenStreetMap Foundation. It’s an independent and community-sponsored initiative.

How do I make a map of a California county showing population density?

https://community.openstreetmap.org/t/south-australia-road-classification-proposal/112068

Highway, Building, Barrier, Tower, Area, Landuse, and more.

if you history user of 2 years form highways this finding. was edit errors has been yandex map.

There is a long discussion happening in the United States section of the community forum regarding where to draw the line between the “main” populated place node values, and specifically the place=* values of city and town in New England. I thought it would be useful to do a bit of analysis to see how these values are distributed across the database when compared to population. Through this analysis, I include all tags which have place values of city, town, village, hamlet, and isolated_dwelling. I also only include nodes that have a population tag.

My overpass query for each category looks like this:

[out:csv(::id,place,population;true;"|")][timeout:60];
node[place=city][population];
out;

One of the challenges of analyzing this key is that because it represents order-of-magnitude differences, its distribution is log-normal. In other words, it forms a bell curve provided that the X-axis is drawn logarithmically.

To look at this data logarithmically, I grouped the place nodes logarithmically, in steps of 1, 2, and 5 per 10x jump. When viewing the distribution of place=town, the log-normal shape comes out quite clearly. The number on the X axis represents the upper limit of each bin.

Now that we’ve assessed that the data is distributed log-normally, the next question we want to be able to as is, for a populated place with a certain population, how are the place values distributed? For this, we look across each logarithmic “bin” and determine the percentage of each place value in use:

We can assess, for example, that for places with a population between 500 and 1,000 (the bin labeled “1,000”), it’s tagged place=village over 90% of the time. The village blip at 10,000,000 is the result of a data error - a single remote place node being erroneously tagged with a high population in a bin of size n=19. Needless to say, on the far right of this graph, there are fewer and fewer nodes in each bin.

Lastly, we would like to know the mean and standard devation of each place category. However, since this is log normal, we need to compute the mean and standard deviation in the logarithmic domain, and then convert it back. The mean, and plus or minus two standard deviations are computed in the table below:

place=	-2σ	-1σ	μ	+1σ	+2σ
city	8,341	33,118	131,496	522,118	2,073,119
town	782	2,814	10,124	36,422	131,039
village	13	71	393	2,173	12,011
hamlet	2	8	36	165	763
isolated_dwelling	0	2	6	22	84

Thus, this means that 68% of place=town nodes – one standard deviation – that are tagged with a population tag, have a population= value between 2,814 and 36,422. Taking this out to two standard deviations, 95% of all place=city nodes have a population= tag value between 8,341 and 2,073,119.

Clearly, there is considerable overlap between each category, no doubt because of differences in tagging conventions between places, differences in accounting for population, and differences in place tagging in areas of different population density.

One of the most rewarding aspects of being an OpenStreetMap contributor is the surprise of discovering where your contributions will be displayed next.

“I put that obscure, forgotten place back on the map, and now they’re everywhere!”

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Researching toponyms is fun because I have to analyze the daily conversations among the locals and try to triangulate the place name centroid based on this conversations. Bonus point if my centroid triangulation somehow coincides with ancient, forgotten, historical maps.

Traces of Sepatan, Djati, and Rawa Roko can still be found on old historical maps, circa 1900. Locals still use these toponyms right now, despite the government’s refusal to acknowledge their existence in the official addressing system.

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It’s ‘forgotten’ in the sense that the local government over here has simplified the toponym system too much. Some toponyms have been upgraded to official administrative region names (and are now embedded in the official addressing system), while the rest have been left behind. People still use these ‘left-behind’ toponyms daily to refer to certain places, even though the government has somewhat ‘discouraged’ their use. (The colonial administration did it better, though. When I consulted the archives and library for old maps, all of these ‘left-behind’ toponyms were actually mapped quite well in the past.)

And this situation has led to mass confusion for people. Government-mandated addresses often don’t reflect reality. People still use all those ‘left-behind’ toponyms in their daily activities, yet they don’t appear on official, government-mandated maps and addressing systems.

That’s one of my personal missions right now: to put all those ‘left-behind’ toponyms back on the maps.

[Semi-automated translation of the Italian diary entry]

On OpenStreetMap, a tree can be represented as a natural=tree node.

Leaf type 🌿

leaf_type is the most common tree-related tag in the database, this is because it is easily verifiable and is supported with a quest by StreetComplete. The values are broadleaved and needleleaved. Some argue that palms should not be tagged as broadleaved but with a value of their own, =palm.

Leaf cycle 🍂

This tag describes whether a tree is deciduous or evergreen. Most needleleaved tree species are evergreen, but this is not always the case, so do not infer this value automatically. You can add this value easily if you know the species, or more simply if it is autumn/winter. If not, you can try to see if satellite or street-level imagery taken at those times are available.

Genus and species 🌳

If you are not an expert, there are tools that can help you recognise the genus/species of a plant, such as Pl@ntNet and iNaturalist, both of which also exist as mobile apps. On OpenStreetMap there are many trees with species (or species:wikidata or species:xx) that do not have leaf_type or leaf_cycle. These values are of course identical for each species (and also for many genus) and can therefore be easily deduced. There are two lists on the OSM wiki that contain these values for genus and species.

MapComplete has a dedicated tree theme that can be used to enter the species while SCEE has a dedicated quest (“What is the genus or species of this tree?”).

Monumental trees 🏛️

Monumental trees can be mapped adding denotation=natural_monument. In Italy they are recorded by the Ministry of Agriculture, Food Sovereignty and Forests (Masaf) with annual updates. You can map them by adding ref:masaf, which is a unique code assigned by the ministry.

In Poland they are recorded by the ‘Generalna Dyrekcja Ochrony Środowiska’ (GDOŚ) (you can find many of them with a query natural=tree+ref:inspire=*), in Serbia many zapis (sacred trees) are mapped with ref:zapis while b-unicycling has recently documented the place_of_worship=sacred_tree tag to map rag trees in Ireland and Scotland.

Rendering 🎨

Trees are rendered on Carto as green circles with a brown dot in their centre, regardless of their attributes.

The Straßenraumkarte Neukölln renderer shows the trees differently according to leaf_type, circumference and diameter_crown. However, the web map only works for the Berlin district of the same name.

F4 Map and Streets GL (no longer updated) are 3D renderers that use the height tag. F4 Map distinguishes trees by foliage type and also supports some values to differentiate palm trees. Esri also has a 3D map that uses OSM data, and which should support height and also some genus values.

On the IMAGICO.De blog, there is an interesting article that goes into detail on possible renderings to highlight the various attributes.

QA 🛠️

There are more than 20,000 mapped trees, but QA tools are still few. That is why I created this MapRoulette project: Tree Validation.

There are challenges that compare values in the database with the largest values ever recorded in nature, for example trees taller than Hyperion. Other challenges concern uncommon or incorrect values of denotation, species, genus, leaf_cycle or leaf_type.

The hope is that in the future more and more tools will check on tree tagging. For now there is at least one open issue for Name Suggestion Index and one for Osmose/JOSM.

If you want to discuss trees on OSM, you can use the “tree” tag on the OpenStreetMap Community Forum.

Have fun mapping!

I’ve finished (for a second time!) mapping all the paths in my local cemetery. The first time another mapped decided that concrete or gravel ways designed for walking on weren’t “paths” and deleted them all. He also seemed to have strong feelings about people cycling in cemeteries, which is odd as The Greater Metropolitan Cemeteries Trust actually endorse it as a use of their land. As my daughter is buried in the cemetery I feel some ownership of the place, and do love it and Merlynston creek that flows through it. I’m hoping no one vandalises my work again.

I received a request to update my previous list of people who map every single day. The top 3 places remain the same, with Aurimas Fišeras passing the 10 year mark of non-stop mapping! Congratulations on an amazing accomplishment, and a big thank you to all of these dedicated mappers!

Consecutive Days	First Day of Streak	User
3672	2014-04-03	Aurimas Fišeras
2810	2014-08-09	vichada
2687	2016-10-22	ika-chan!
2256	2018-02-17	LidaCity
2106	2018-07-17	Algebre gama
1943	2018-06-02	thetornado76
1943	2018-12-27	hendrik-17
1894	2014-06-15	roschitom
1860	2017-04-13	looniverse
1837	2019-04-12	bxl-forever
1828	2019-04-21	JJIglesias
1755	2019-07-03	Sammyhawkrad
1674	2019-09-22	Zrop
1631	2019-11-04	mstock
1629	2018-06-26	phiphou
1583	2018-10-06	fx99
1544	2018-10-29	BCNorwich
1501	2014-06-26	RoadGeek_MD99
1467	2017-11-04	dvdhoven
1450	2018-02-16	alkushi
1392	2019-10-25	marczoutendijk
1346	2017-10-28	piotrS
1336	2020-08-25	NieWnen
1318	2020-09-12	Strubbl
1305	2020-09-25	mindedie
1292	2017-12-11	vincent_95
1291	2020-10-09	Leonius_Bad
1286	2020-10-14	Grass-snake
1259	2020-11-10	SekeRob
1240	2020-11-29	seattlefyi
1211	2015-01-28	lodde1949
1159	2017-02-05	futurumspes
1153	2019-02-10	jmapb
1149	2021-02-28	MJabot
1092	2019-03-21	mmahmud
1070	2016-06-15	mindedie
1064	2018-08-12	ikiya
1063	2017-12-02	下り専門
1055	2019-07-22	Nesim
1031	2021-06-26	vincent_95
1026	2015-09-25	Nesim

SotM Latam 2024 - Belém/Pará - Brasil.

The State of the Map Latam 2024 will take place in the city of Belém, Brazil, from December 6 to 8, 2024 at the Instituto Federal do Pará, this being the sixth edition of the ‘Latin American OpenStreetMap Conference’ and aiming to promote the use of OpenStreetMap (OSM), and the integration of OSM mappers, developers, open data communities, free and open source software communities, students, researchers, geoinformation professionals, non-governmental organizations, companies and public institutions.

SotM Latam 2024 After the voting period for choosing the SotM Latam 2024 logo has concluded, I am pleased to announce that the chosen option is 1.

You can see the results and voting details in the document shared above: https://docs.google.com/document/d/15Kbotyc6UCcWQ2K7apPOnfqXSSDFfvlDQtZxM_Nkag4/edit

Website: http://2024.osmlatam.org

https://wiki.openstreetmap.org/wiki/ES:LatAm/Eventos/State_of_the_Map_Latam_2024

You can see the voting results and details in the previously shared document: https://lnkd.in/dQcDDFCv

an organization of UMBRAOSM Union of Brazilian mappers from Openstreetmap, Latam Community and Foss4g

SotM Latam 2024 organizing committee

Contact: state@osmlatam.org

http://www.umbraosm.com.br

Years ago when searching for a viewpoint from an old photo where I wanted to do rail photography I managed to locate the exact cliffside overlook and discovered a somewhat hidden gem of trail network in the process.

Though there is an official dirt road in the canyon below and a few desire paths offshooting from it the hills above remained relatively unmapped not showing up in the otherwise void of an area.

With the understatement of the local forecast for the afternoon/evening I packed my beloved eTrex 20x in the camera bag along with my trusty Nikon D700 planning to take in some of the views while there in between tracing runs expecting no more than some cloudiness and a light sprinkling.

I had originally planned to do some averaging as well to mark down 3 of my favorite spots on the cliff to photograph the scenery below but just as I reached the overlook the light rain that had accompanied me on most of my journey up started to thicken and become slanted. Just as I positioned myself on the side of the ledge for my first point reading spot the wind had picked up considerably to near constant 70kph gusts. The eTrex wobbled fiercely atop the perching rock and I had to scrap my plans of more photos just to hold it still for fear it may fall to it’s death below as my other hand clinged to the rockface hoping to avoid a similar fate.

After 5 minutes to allow a good average I quickly hit save and climbed back up to grab my gear bag and make my way back down the path for the second tracing run in the opposite direction to help iron out anomalies when mapping from the trace. As I set off the steadily increasing rainfall now started to turn to almost sideways hail from every direction as the many rockfaces perturbed the wind. Though hectic as it may seem the eTrex managed to maintain it’s nice 8 foot accuracy throughout most of the trip and likewise I was similarly high spirits.

In an almost serene state of mind while walking the trails my attention drew to the contrast between the dramatic weather and environment and the life which springs forth from otherwise dead plains because of it. Many cacti once shriveled from the dry winter were now stuffed with water, their beautiful flowers blooming brightly pink which would soon bear fruit. The normally tan plains dead with brush now teeming with fluorescent wildflowers of all colors in every direction. In that moment I remembered who I was when escaping here 11 years ago, hurt and tired of the chaos and sterility of the urban design seeking to hide from the world and in the process discovering a new one all to myself.

It’s these things the fuel my passion for exploring and desire to document what’s around me, the eTrex always at my side as a faithful companion for so long now. The amount of memories and many long adventure it holds being priceless to me.