Complex Situational Picture

RESITEK: Complex Situational Picture
Within the RESITEK project data from satellites, drones, sensors, and a variety of other data sources are combined into a central situational picture that supports emergency responders and rescue teams in making fast, well-founded decisions.
Image: 1/1, Credit:
DownloadDownload

An up-to-date, comprehensive situational picture is the basis for fast and well-founded decisions in the event of a disaster. One of the challenges faced here is the aggregation of diverse data sources and presenting them in a coherent way. The central situational picture in the RESITEK project aims to overcome that challenge by integrating satellite, drone, sensor, and various other data in such a way that emergency responders and decision-makers can access relevant, analyzed, and processed information at any time to further aid in the decision-making process.

Together, the various data from the institutes of the DLR create the basis for a comprehensive, up-to-date and dependable situational picture that optimally supports emergency responders and decision-makers in disaster protection.

German Remote Sensing Data Center

Combines and analyzes geodata from various sources (satellite, aerial and drone imagery, traffic information, authority data, meteorological data, terrain information) for a comprehensive, up-to-date situational picture. Develops automated process chains for the integration, visualization, and evaluation of relevant information. Presents the collected and integrated information in a continuously updated situational picture that can be accessed at any time. Depending on the scenario and use case, different priorities can be set.

Institute for AI Safety and Security

Responsible for the cross-cutting topic of data quality and provenance in the complex situational picture, as well as the analysis of the trustworthiness of AI methods. Develops and implements data quality measures for heterogeneous data types, designs a blockchain-based tool to ensure data provenance, and provides ethical guidance for the project with regard to the use of AI in disaster response.

Institute of Space Research

We integrate real-time technologies provided by the Modular Aerial Camera System (MACS) into operational use in collaboration with participating security authorities and organizations. We conduct research and development on innovative and, above all, operationally viable methods for real-time aerial mapping of incident areas - as a key element of a comprehensive situational picture. Real-time mapping results are made available via standard-compliant data interfaces, enabling their use in virtually all existing geoinformation and incident command systems. A particular focus of our work is the universal and demand-driven deployment of MACS payloads on both manned and unmanned aircraft - especially on so-called Vertical Take-Off and Landing (VTOL) drones.