Twitter | Heidelberg Institute for Geoinformation Technology

Join our final “SocialMedia2Traffic” project presentation on March 22

Published: 14. March 2022 | Featured

Navigation services need time dependent information on traffic speed to generate suitable routes and yield accurate travel time estimations. However, this information is not available free of cost globally. Within the recently completed project SocialMedia2Traffic, we have developed a system … Read More

Tags: BMDV, centrality, GIScience, mFUND, OpenStreetMap, ORS, social media, Traffic, Twitter, Uber

meinGrün, Tradur und SocialMedia2Traffic bei der mFUND Konferenz 2021

Published: 29. October 2021 | Featured

Letzte Woche konnten wir bei der digitalen mFUND Konferenz drei unserer Projekte einem interessierten Publikum vorstellen. Im Fachforum “Die „15-Minuten-Stadt“ datenbasiert ermöglichen” haben wir gezeigt, wie die meinGrün App, das meinGrün Webportal und die angegliederten Dienste Städte dabei unterstützen könnten, … Read More

Tags: green routing, heigit, meinGrün, mFUND, openrouteservice, OSM, routing, SM2T, TARDUR, Twitter

Social Sensing Workshop at GIScience Conference 2021

Published: 27. September 2021 | Featured

On Monday , Sep. 27 our “Social Sensing Workshop” at the “11th International Conference on GIScience” 2021 will take place. We are also happy to make you aware of full paper related to MeinGrün project and openrouteservice at the main … Read More

Tags: geosocial media, GIScience, Twitter

OSM Missing Areas Identification paper is featured in August by ISPRS Journal of Photogrammetry and Remote Sensing

Published: 17. August 2020 | Featured

We are pleased that our article has been selected by the editors of ISPRS Journal of Photogrammetry and Remote Sensing as the featured Article in August 2020. This means it will be available open access for 1 year. Get your … Read More

Tags: clustering, deep learning, deep neural networks, Missing Maps, OSM, Twitter

Exploration of OpenStreetMap Missing Built-up Areas using Twitter Hierarchical Clustering and Deep Learning in Mozambique

Published: 8. June 2020 | Featured

Accurate and detailed geographical information digitizing human activity patterns plays an essential role in response to natural disasters. Volunteered geographical information, in particular OpenStreetMap (OSM), shows great potential in providing the knowledge of human settlements to support humanitarian aid, while … Read More

Tags: deep learning, deep neural networks, humanitarian, machine-learning, Open data, OpenStreetMap, OSM, remote sensing, settlement, social media, social sensing, Twitter

Jupyter Notebook: Combining Twitter Data and OpenRouteService Directions API

Published: 10. October 2018 | Featured

In the case of a disaster fast response is important and life saving. Information on blocked streets is crucial, but a the same time this infornations needs to be considered by routing engines in real-time. However, many routing engines use … Read More

Tags: disaster risk management, DisasterORS, openrouteservice, OSM, Twitter, VGI

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