The goal of SEVA is the development of a scalable exploration-tool that enables users to extract all land cover changes in big Sentinel-2 data and to identify all changes relevant to the user.
Funded by: Federal Ministry of Economic Affairs and Energy
Funding period: 01.11.2017 - 31.10.2019
The objective of ENAP project is the utilization of information that is provided by volunteers in social media (volunteered geographic information – VGI) for geoscientific questions. We develop novel methods in the two computer science fields of computer vision and visual analytics to find relevant VGI quickly and to assess their value in relation to other information.
Funded by: German Research Foundation
Funding period: 01.08.2016 - 31.10.2019
The goal of the Big Data system GeoMultiSens is to enable scientists to study changes of the Earth’s surface on high-resolution scenes. Therefore we develop an integrated processing pipeline supporting the analysis of petabyte data.
Funded by: Federal Ministry of Education and Research