09195925282

1. Install Java Development Kit for ARM 64 processors https://www.oracle.com/java/technologies/downloads/#jdk17-mac

2. Download josm-tested.jar https://josm.openstreetmap.de/josm-tested.jar

3. Drag and drop josm-tested.jar into the Dock

4. Run JOSM!

Die Graphenintegrations-Plattform (GIP) enthält österreichweit eine Vielzahl an Verkehrsinfrastrukturdaten in hoher Detailliertheit. Die GIP beinhaltet Daten für alle Verkehrsformen inkl. Schiffe, U-Bahnen, Seilbahnen, Busse, KFZ, Radfahrer und Fußgänger. Die GIP ist kein fertiges Produkt, sondern wird laufend erweitert. Das betrifft sowohl Inhalt als auch Struktur.

Seit Anfang 2016 werden aktualisierte Datenauszüge der GIP als Open Goverment Data (OGD) in regelmäßigen Abständen veröffentlicht. Das Basisnetz wird in dem einfach zu verwendenden GeoPackage Format angeboten. Der detailreiche Routingexport ist nur im CSV-Format verfügbar.

Der Datenauszug „Routingexport“ ist besonders interessant, da er für das Routing in allen Verkehrsmodi die relevanten Informationen enthält. Unter anderem das routingfähige Netz, die Querschnittselements mit den Erlaubnissen und Verboten nach der StVO u.v.a.m.

Mich interessierten besonders die Daten für Radfahrer. Öfters gibt es Situationen wo die Befahrbarkeit für Radfahrer unklar ist. Beim Abwägen der Merkmale ist die behördliche Sicht natürlich auch ein Argument. Aber nicht mehr, von einer Richtigkeit gehe ich nicht aus.

Ein Blick in die Daten

SynerGIS [2] stellt eine Web-Applikation bereit, die eine kleine Auswahl der Rohdaten mit Raumbezug visualisiert. Der Datenstand wird mit Juli 2018 angegeben. Die Interpretation der Daten ist schwierig, da die Bit-Kodierungen nicht aufgelöst werden. Dennoch, eine nette App für einen ersten Blick auf die Daten.

Einige Länder-GIS [3] präsentieren auch GIP-Daten. Die GIS-Steiermark stellt z.B. bei aktivierten „Fußweg“ Lage und Typ des Nutzungsstreifens für den Langsamverkehr dar. Die Legende gibt dazu näher Auskunft. Bei der Interpretation ist Vorsicht angebracht: Typ des Nutzungsstreifen und Befahrbarkeit werden im GIP immer getrennt modelliert. Eine schmale Begleitstraße (<3 m) wird z.B. im GIP mit Typ 36 „Geh- und Radweg“ bezeichnet. Wer dort fahren darf ist damit nicht gesagt.

Datenimport und Visualisierung

Der Datenimport läuft in zwei Schritten ab: (1) Download der GIP-Daten (gezippte CSV-Files) und (2) Import einer Datenauswahl in ein SQL Spatial Datenbank (Abb 1). Als Frontend wird QGIS verwendet (Abb 2).

Abb 1: Datenfluss Import der Verkehrs-Infrastrukturdaten von GIP.at

Abb 2: Beispiel Visualisierung der GIP-Fahrerlaubnis Radfahrer mit QGIS

Leistungsdaten

Download und entzippen ( 0,5 GB –> 3,5 GB) benötigen ca. 5 min. Der Import von 1,7 GB in die SQL Datenbank (23 Mio Zeilen in 5 Tabellen) ist nach 3 min abgeschlossen. Die Konvertierung der lat/lon-Texte zu räumlichen Daten benötigt noch einmal 2,5 min.

Code

Code und Dokumentation sind auf GitHub verfügbar [4].

Datenqualität GIP vs OSM

Eine valide Bewertung der Datenqualität möchte ich mir nicht anmaßen, aber eine kleine Stichprobe ist sinnvoll, schon allein als vertrauensbildende Maßnahme in die eigene Auswertung. Dazu wurden je 6 Wege mit Fahrverboten für Radfahrer in Wien und Graz gesucht, für die OSM und GIP nicht übereinstimmen.

Die GIP-Fahrerlaubnis für Radfahrer wurde zusätzlich mit dem Routenplaner AnachB überprüft. Anschließend wurde vor Ort verifiziert, wer recht hat. Ergebnisse:

Ort (Anzahl Fälle)	GIP	OSM
Wien (6)	5x richtig	1x richtig
Graz (6)	1x richtig	5x richtig

Nicht uninteressant :-)

Referenzen

[1] GIP.at: Dokumentation Intermodales Verkehrsreferenzsystem Österreich, Datensatz-Beschreibung, http://www.gip.gv.at/#ogd

[2] SynerGIS Wien: Web-Applikation zur Graphenintegrations-Plattform GIP, https://synergis.maps.arcgis.com/apps/webappviewer/index.html?id=1b9896365b5443b1a7dd20d7fe9b70ad

[3] GIS-Steiermark: Digitaler Atlas – Basiskarte – Layer “Verkehr Steiermark” – Fußwege, https://gis.stmk.gv.at/wgportal/atlasmobile/map/Fachkarten/Verkehr

[4] robhubi: Import GIP.at Data (2021), GitHub repository, https://github.com/robhubi/GIPrva

After spending near a year to intermittently add destinations, directions, guideposts, whenever mapping/updating a road, a junctions, a roundabout, set out on a complicated road trip thru the region with my fav OSM maps based navigator and low and behold, it really worked… before every turn the display showed the next destinations/directions coming up, to include a typo I made, which proved the case: It was really my doing. Some direction signs are really abundant, 6-7 destinations on one way, one or more poles, all listed out in the order shown on the guideposts and entered. Something worth doing, while watching out for spelling mistakes. Gives drivers more confidence they’re on the right way ;P)

PS: destination:ref:backward/forward with the upcoming road numbers, and some signs showing the same destination in multiple directions adds to the fun. 👌

തൃശ്ശൂർ ജില്ലയിലെ ചരിത്ര പ്രാധാന്യമുള്ളനാടാണ് കൊടകര. ചാലക്കുടി നിയോജക മണ്ഡലത്തിലെ മലനിരകളും കുഞ്ഞരുവികളുമടങ്ങുന്ന ദൃശ്യമനോഹരമായ പ്രദേശം.വിവിധ ജാതി മതസ്ഥർ ഒരുമയോടെ വസിക്കുന്നു എന്നത് ചെറിയകാര്യമല്ല. കുന്നത്തറ ശ്രീ സുബ്രഹ്മണ്യ സ്വാമി ക്ഷേത്രം,ശിവക്ഷേത്രം,വിഷ്ണു ക്ഷേത്രം,തിരുത്തൂർ ശ്രീകൃഷ്ണ ക്ഷേത്രം,അച്ചങ്ങാടൻ ക്ഷേത്രം, പൂനിലർക്കാവ് ഭഗവതീ ക്ഷേത്രം എന്നിവയുംകൊടകര ക്രിസ്ത്യൻ വലിയ പള്ളിയും മുസ്ലിം ജുമാ മസ്ജിത്തും ഉൾക്കൊള്ളുന്നതാണ് ഇവിടുത്തെപ്രാർത്ഥനാ ദേവാലയങ്ങൾ.കൊടകര ഷഷ്ടിയും പൂനിലർക്കാവ് കാർത്തികയും അതിവിപുലമായ പള്ളി പെരുന്നാളും കൊടകരയിലെ മനം മയക്കുന്ന ആഘോഷങ്ങളാണ്.

If you’ve ever wondered how accurate road surface tags are in OpenStreetMap, I’ve compiled a review of the accuracy of surface tags (sealed vs unsealed) in Victoria, Australia.

https://littlemaps692810600.wordpress.com/2021/12/03/openstreetmap-on-australian-roads-how-accurate-are-road-surface-tags-in-victoria/

There’s lots of colorful maps and tables. Spoiler alert – Thanks to amazing work by hundreds of enthusiastic mappers, OpenStreetMap’s road surface tags in Victoria are extremely accurate, and provide an invaluable resource for users who want to select routes that stick to sealed or unsealed roads and tracks.

Medya

Medya olay TV TC

Para

Türkiye Avrupa

A yayıncılık

This year I had an amazing opportunity to participate in the HOT Data Quality Intership, being chosen to participate in these twelve weeks was the best thing that happened to me this year, I felt as if all my work on OpenStreetMap was recognized at that moment. I would like to thank everyone who shared their knowledge in the trainings and also to the project coordinators Sam and Becky thank you very much!

Without a doubt it was an experience that I will take for life, I met incredible people from many different countries…

No doubt it is a unique program for OpenStreetMap mappers and helps the community to grow, giving this opportunity to inspire and support young people like me to learn more about OSM and the ecosystem around us is priceless, I imagine that like me my colleagues continued to contribute to OSM in their local communities…

Here I must emphasize the importance of programs like Data Quality Intership in being able to fund and impact local communities around the world, perhaps it would be interesting to expand the program to the mapping hubs.

The future of OSM is not in closed teams maintained by companies that often do not know the reality of what they are mapping, the future of OSM is in funding the work of young volunteers and their communities giving them the opportunity to learn and improve their skills, well structured local communities know what is missing on the map and what they want to map, they know the region better.

For the future I intend to continue to apply what I learned during these 12 weeks and help the Brazilian community, I intend to continue mapping with the projects in TaskManager, I am still planning to have a more solid base for 2022 but I intend to continue with my work mapping cities in my state.

Translated with www.DeepL.com/Translator (free version)

Esse ano tive uma oportunidade incrível de poder participar do HOT Data Quality Intership, ter sido escolhido para poder participar dessas doze semanas foi a melhor coisa que me aconteceu esse ano, eu senti como se todo meu trabalho no OpenStreetMap tivesse sido reconhecido naquele momento. Gostaria de agradecer a todos que compartilharam seus conhecimentos nos treinamentos e também para os coordenadores do projeto Sam e Becky muito obrigado!!

Sem duvida foi uma experiencia que levarei para a vida, conheci pessoas incríveis e de vários países diferentes…

Sem duvida é um programa único para mapeadores do OpenStreetMap e ajuda a comunidade a crescer, ao dar essa oportunidade de inspirar e dar suporte para que jovens como eu possam aprender mais sobre o OSM e o ecossistema em volta não tem preço, imagino que assim como eu meus colegas continuaram a contribuir para o OSM em suas comunidades locais…

Aqui devo ressaltar a importância de programas como Data Quality Intership em poder financiar e impactar as comunidades locais ao redor do mundo, talvez seria interessante expandir o programa para os hub de mapeamento. O futuro do OSM não está em equipes fechadas e mantidas por empresas que muitas vezes não conhecem a realidade do que estão mapeando, o futuro do OSM passa por financiamos o trabalho dos jovens voluntários e suas comunidades dando oportunidade de aprender e aperfeiçoar suas habilidades, comunidades locais bem estruturadas sabem o que falta no mapa e o que querem mapear, conhecem melhor a região.

Para o futuro pretendo continuar a aplicar o que eu aprendi durante essas 12 semanas e ajudar a comunidade brasileira, pretendo continuar a mapear com os projetos no TaskManager, ainda estou me planejando para ter uma base mais solida para 2022 mas pretendo continuar com meu trabalho mapeando cidades do meu estado.

As a Crowd2Map Volunteer I had the opportunity to attend the conference #StateOfMap2021, it was a unique experience where for the first time I could see many experts from various areas related to data in one place, I did not know that the mapping area was too large.

Well, many sessions marked me but in particular those involving development of solutions using programming language, I hardly knew that with the knowledge I have in Python and database could do a lot of things with data, for me it was a wake-up call. It was from this awakening that I decided to explore further this area of development of solutions using data, research more about what I can do with the mapping data here in Tanzania to help in the development. With regard to networking it was possible to create networking, for an exchange of experience in the area, where it was possible to have a view also of what I can do mapping.

Congratulations to the whole team, for the beautiful organization, was all very well organized from the sessions until the presentations made, it was very good to know that there are so many people or a united group in the area of mapping and for the development of solutions for society. One of the recommendations that maybe could leave is that next time presentations are made all in English so that we can all watch all the sessions, or to the sessions in a language other than English could be put subtitles do not know if is possible or the slide could be translated into English and then sent to the participants.

Ich hab letztens schon mein neues Tool vorgestellt, welches dabei hilft, OGD Datensätze mit Wikidata, Wikipedia Listen, Wikimedia Commons und OpenStreetMap abzugleichen.

In einem neuen Screencast hab ich beschrieben, wie man das Tool selber installiert und dann eigene Datensätze hinzufügen kann: https://www.youtube.com/watch?v=4PKUCjS2HL8

Außerdem gibt es einen neuen Datensatz: die öffentlichen Toilettenanlagen in Wien!

Estoy validando en el proyecto 8942 y por casualidad descubro que hay otros dos proyectos activos que actúan sobre una parte de la misma zona. No es la primera vez que veo que hay proyectos que cubren zonas ya mapeadas en otros proyectos. Creo que debería existir algún tipo de coordinación o al menos de conocimiento del mapeo de una zona en la que se planea un nuevo proyecto. Quizá también debería existir alguna forma de ver el historial de mapeo en una zona.

Son ideas para aprovechar mejor el esfuerzo de mapeadores y validadores.

To gain first- hand experience of OSM, mapping was done in Mhow subdivision of Indore district in Madhya Pradesh, India. There are 10 subdivisions in the district. Total area of the district is nearly 3900 sq. km with total and rural population of nearly 3.28 and 0.8 million respectively. Nearly 679 sq. km area is under forest cover. Indore city is commercial capital of Madhya Pradesh and has a population of nearly 2 million and has been ranked the cleanest city in India for five consecutive cleanliness surveys from 2017 to 2021. Dr Ambedkar Nagar (Mhow), the headquarter of the subdivision is an important cantonment town. The town is located 23 km south-west of Indore city and has a population of nearly 85 thousand. Four training institutes of Indian Army and Border Security Force and two premier educational institutes namely Indian Institute of Management (IIM) and Indian Institute of Technology (IIT) are also located in the subdivision. National Highways NH52, NH347BG and State Highways SH38, SH38A and SH40, IIM Road and Main District Road pass through the subdivision. Important tourist locations are Choral dam, Patal Pani waterfall, Mhow Fort and Bhim Janmbhumi (birthplace of Dr Bhimrao Ambedkar). Other nearby attractions are Ralamandal Wildlife Sanctuary, Jam Dwar (Jam Gate) etc.

The mapping was done over a period of nearly two and half months. Mostly ESRI World Imagery (Clarity) Beta was chosen as data source. Additionally, Bing aerial imagery was also used. A Cake diagram was drawn with 16 slices. iD editor was used for nearly 94% changes. Other editors used were JOSM and Vespucci. Total changesets and changes were nearly 200 and 5700 respectively. More than 80% and 1% changes were newly created and deleted ones respectively. Changes for features namely roads, buildings, and others were nearly 66, 27 and 7% respectively. Several tertiary, unclassified and residential highway features were created. Editing was needed where two way primary and secondary highways were shown as single ways in OSM. Mostly only large building features were created. Several water bodies and a canal feature were created. River feature was edited to improve its quality near bridges and settlement etc. Dams, weir, aqueduct and bridge and quarry features were created. Leisure and amenities features, namely swimming pools, basketball courts, playground, stadium, stadium buildings, hostel were created. The highway features were reclassified after their creation to suitable subclass based in their importance. This was done by visualizing the ESRI World Imagery in Vespucci editor. Mining area, existing and historic (abandoned) could not be interpreted on imageries and thus no sub classification was done. Brick kiln could not be interpreted and the feature is also a proposed feature and thus was not created. Main District Roads (MDR) were not assigned names. The lesson learnt are as follows:

• Bing aerial imagery had higher water spread area for waterbodies and was a better data source for this feature.
• Buildings are seen in a perspective view in the imageries. To create the feature, first top of the building be mapped and then the feature be moved to overlap the bottom of the building.
• For connecting highways with different importance (e.g. primary and secondary highways), a node be first created for highway of higher importance and then two highways be connected.
• The magic of the ALT key in iD editor (learnt halfway) be remembered while creating a feature close to another existing feature, to avoid creating duplicate nodes.

Maps.me led me onto via 35 although part of this road is still under construction, so I ended up in the middle of nowhere at a bridge which was still under construction. The part from Florencia to Naranjo will only be finished in 2025! https://en.wikipedia.org/wiki/National_Route_35_(Costa_Rica)

Started with Street Complete fixes in Renningen, Bawü, Germany in Sep 2021.

Currently (Dez 21) about 30% done.

In fact this motivated me again a lot to do some OSM mapping.

Kio