Our projects
Ongoing Projects
MultiSat4SLOWS
Funding by: Helmholtz Artificial Intelligence Cooperation Unit (HAICU)
Funding period: 2020 – Present
Project partner: German Aerospace Center (DLR)
The main goal of this project is to develop a novel hybrid multi-scale data fusion approach that incorporates information from all satellite remote sensing sources including optical images and radar data for near real-time change detection and assessing landslide stability and early warning indicators. A deep-learning based multi-sensor data fusion is developed to integrate data from various temporal and spatial scales for improved and more robust change detection of the effects caused by landslides
Previous projects
AI4Flood
Funding by: Helmholtz Artificial Intelligence Cooperation Unit (HAICU)
Funding period: 01.10.2020-30.12.2022
Project partners: German Aerospace Center (DLR)
The main aim of the AI4flood project is to develop an automated system capable of extracting and detecting flooded areas in near-real time for generation of flood maps for rapid response activities in case of flood emergencies. The system will be built on the comprehensive methodological competences already existing at DLR and GFZ with the goal of combining Big Data management of SAR data and novel machine learning algorithms for automatic flood mapping in near-real time.
SAR4InFRA
Funding by: Federal Ministry of Transport and Digital Infrastructure
Funding period: 01.10.2020-30.09.2022
Project partner: Fern.Lab, IPI Hannover, and LBVSH
Through this research project, traditional monitoring on the ground is extended to a larger region through the use of radar remote sensing observations. Potential deformations of traffic structures will be detected by means of interferometric analysis of radar images from the Sentinel-1 satellite. For maximizing the density of the displacement information, different methods for time series analysis will be integrated.