News of Heidelberg University’s GIScience Research Group.
Global Platform 2019 in Geneva
Creating maps helps humanity. Drawing maps together with communities is crucial for effective risk reduction interventions, ensuring no one is left behind.
The progress of the implementation of the targets set by the Sendai Framework for Disaster Risk Reduction (DRR) have been key discussion points during this years Global Platform in Geneva. [...]
Posted in Events on Apr 23rd, 2019
The 11th Information Communications Technology for Development (ICT4D) Conference brings together hundreds of public, private and civil society organizations, eager to share practical insights on applying digital technology to development, humanitarian, and conservation challenges. Participants share how they are using innovations in information and communications technology to increase impact in addressing humanitarian and development challenges. [...]
Posted in External Projects, Services on Mar 1st, 2019
Where is the next health center? What areas show less accessibility to health centers and are therefore the most vulnerable?
In 2018, the openrouteservice team already illustrated how these questions related to vulnerability can be addressed with openrouteservice APIs, at that time for disaster prone regions in Madagascar. Learn more here.
Also at that time our Missing [...]
HeiGIT members Melanie Eckle and Martin Hilljegerdes were invited to the “Digital in civil protection” congress of the Landesverband Westfalen-Lippe in Münster to share insights and to present current activities all around “Potentials of Open Data and Digital Humanitarians for civil protection“. They shared experiences and impacts of the collaborative efforts of the Missing Maps [...]
The GIScience group cordially invites everybody interested to our next open GIScience colloquium talk about:
Supporting the most vulnerable people before the disaster strikes – International Disaster Risk Reduction within the German Red Cross
Speakers are Stefanie Lux and Stefan Scholz from the German Red Cross (GRC, Generalsekretariat Berlin, International Coordination).
Monday 21.01.2019, 14:15 pm
Institute of Geography, Heidelberg University, [...]
The GIScience Research Group at Heidelberg University and the Heidelberg Institute for Geoinformation Technology (HeiGIT) are happy to share the their GIScience github repository contains now already over 50 open source repositories and it’s still growing. These contain results from several research projects and in particular also some very active long term activities. Most of the tools [...]
After the successful GeOnG conference 2018 in chambery we want to thank the organizers and all participants. We contributed in several ways, as already highlighed in our previous blogpost. Now, we also want to share our slides and workshop material with everyone interested.
Round table discussion:
Machine Learning, AI & satellite imagery: what impact on humanitarian mapping: [...]
Posted in Events on Nov 2nd, 2018
HeiGIT ran a workshop on geodata for sustainable development at the Sustainable Development in Action conference organized by the Heidelberg Center for Environment and Momentum Novum at Heidelberg University.
Our workshop provided an overview about the importance of geodata to tackle the sustainable development goals (SDG) of the United Nations, highlighted the importance of bridging [...]
Posted in Events on Oct 29th, 2018
Over the next couple of days, CartONG are again organizing the biannual GeOnG conference- a great occasion for humanitarian actors, volunteer communities and humanitarian and GIS service providers to mingle and exchange current ideas, challenges and lessons learned.
This year the main theme is ““Perfection” versus “Good Enough” in Information Management: Adjusting to context, scale, [...]
Posted in Publications on Oct 12th, 2018
Our paper about Deep Learning from Multiple Crowds: A Case Study of Humanitarian Mapping is available online now.
Satellite images are widely applied in humanitarian mapping which labels buildings, roads and so on for humanitarian aid and economic development. However, the labeling now is mostly done by volunteers. In a recently accepted study, we utilize deep learning [...]