Federal Ministry for Education and Research (BMBF)


Funding code: 03G0890A

Funding priority: Früherkennung von Erdbeben und ihren Folgen

2020 - 2023


Project coordinator
Prof. Bernhard Höfle
Insitute of Geography, Heidelberg University

Project partners
Heidelberg University
Prof. Bernhard Höfle
Prof. Alexander Zipf

Aeromey GmbH
Heiko Mey

FZI Research Center for Information Technology
Dr. Katharina Glock

German Research Center for Geoscience (GFZ)
Dr. Danijel Schorlemmer

Karlsruhe Institute of Technology (KIT)
Prof. Lothar Stempniewski


Collaboration partners
Earthquake Research Institute
University of Tokyo, Japan

Institute of Geophysics
National Central University (NCU), Taiwan

Department of Geomatics
National Cheng Kung University (NCKU), Taiwan

Dipartimento di Scienze della Terra, dell’Ambiente e delle Risorse (DiSTAR)
Università di Napoli Federico II, Italy

Kathmandu Living Labs, Nepal

Arbeiter-Samariter-Bund Mannheim

Branddirektion Karlsruhe

Deutsches Rotes Kreuz Berlin

Feuerwehr Heidelberg

Technisches Hilfswerk Heidelberg


LOKI - Airborne Observation of Critical Infrastructures (Luftgestützte Observation Kritischer Infrastrukturen)


Find latest project updates in our extensive LOKI GitLab Wiki.
Follow further project updates on Twitter: #LOKI #BMBF.

New paper on automatic 3D damage classification: Check out our latest paper where we classify building-specific damage using a machine learnig model trained on virtual laser scanning data.


General Information

A full overview and detailed description of the LOKI project and the functionality of the developed modules is explained in the extensive LOKI Wiki. Code of the modules developed in LOKI is hosted and documented on GitLab.


The aim of the LOKI project is to develop an interdisciplinary system that enables fast and reliable airborne situation assessments following an earthquake. The system will serve to reduce longer-term damage after an earthquake by recording information on the current situation as efficiently as possible, thereby enabling remediation actions to be undertaken within appropriate timescales. A central focus is the timely overview and detailed recording of the damage to critical infrastructures, such as lifelines (bridges and roads), health care facilities and public institutions (e.g. schools). LOKI will improve the response time and reliability of information provided in the event of an earthquake, and enables better use of existing resources and emergency forces. The objectives will be met by combining existing expertise in earthquake research with a variety of new technologies and concepts, including machine learning, crowdsourcing, Unmanned Aerial Vehicles (UAVs, flying drones available for civil use) and 3D monitoring.


Core components of the LOKI research project and their interaction.

Project partners and their research focuses in the project

Heidelberg University serves as the coordinator of the research project, which is a collaboration between several project partners. Within this collaboration, components and services developed by the individual partners will be integrated into a single system.


Heidelberg University

Automatic damage detection: In order to determine the relevance of the detected damage, methods will be developed to combine:

  • image-based damage detection with 3D geometric damage detection.
  • machine learning with visual (semantic) interpretation by crowdsourcing.

Crowdsourcing and user-generated geoinformation: Methods developed for:

  • (3D) Micro-Mapping for damage mapping and evaluation of the generated information.
  • determining the influencing factors and the optimal combination with automatic, computer-based damage detection.


Aeromey GmbH

UAV-Infrastructure: Development of an ad-hoc network among UAVs, for smooth and fast communication even over longer distances.


FZI Research Center for Information Technology

Coordination mechanisms for UAV fleets: Coordination mechanisms for UAV fleets: Development of real-time capable and adaptive planning mechanisms for UAVs and investigation of decentralized coordination mechanisms, with which UAVs themselves coordinate the division of the area, the prioritization of targets and the route to be flown.


German Research Center for Geoscience (GFZ)

Exposure modelling: Integration of crowdsourcing and primary UAV overflights into building-specific (iterative) exposure modelling, as well as the adaptation of corresponding evaluation algorithms. This approach is capable of working with very heterogeneous data availability.


Karlsruhe Institute of Technology (KIT)

Earthquake engineering for damage classification: Development of damage interpretation rules and decision criteria for (semi-)automatic damage assessment using UAV flying and crowdsourcing.

Project Video

  • 3D Micro-Mapping: 3D Micro-Mapping of trees from profiles.
  • 3D-MAPP: 3D Micro-Mapping of Big 3D Geo-Datasets in the Web.
  • HELIOS++: Heidelberg LiDAR Operations Simulator.
  • HeiGIT: Heidelberg Institute for Geoinformation Technology.
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Latest Revision: 2023-07-17
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