@article{WiegmannKerstenSenaratneetal.,
  author    = {Wiegmann, Matti and Kersten, Jens and Senaratne, Hansi and Potthast, Martin and Klan, Friederike and Stein, Benno},
  title     = {Opportunities and risks of disaster data from social media: a systematic review of incident information},
  series = {Natural Hazards and Earth System Sciences},
  volume    = {2021},
  journal   = {Natural Hazards and Earth System Sciences},
  number    = {Volume 21, Issue 5},
  publisher = {European Geophysical Society},
  address   = {Katlenburg-Lindau},
  doi       = {10.5194/nhess-21-1431-2021},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20210804-44634},
  pages     = {1431 -- 1444},
  abstract  = {Compiling and disseminating information about incidents and disasters are key to disaster management and relief. But due to inherent limitations of the acquisition process, the required information is often incomplete or missing altogether. To fill these gaps, citizen observations spread through social media are widely considered to be a promising source of relevant information, and many studies propose new methods to tap this resource. Yet, the overarching question of whether and under which circumstances social media can supply relevant information (both qualitatively and quantitatively) still remains unanswered. To shed some light on this question, we review 37 disaster and incident databases covering 27 incident types, compile a unified overview of the contained data and their collection processes, and identify the missing or incomplete information. The resulting data collection reveals six major use cases for social media analysis in incident data collection: (1) impact assessment and verification of model predictions, (2) narrative generation, (3) recruiting citizen volunteers, (4) supporting weakly institutionalized areas, (5) narrowing surveillance areas, and (6) reporting triggers for periodical surveillance. Furthermore, we discuss the benefits and shortcomings of using social media data for closing information gaps related to incidents and disasters.},
  subject      = {Katastrophe},
  language  = {en}
}
@inproceedings{KerstenRodehorst,
  author    = {Kersten, Jens and Rodehorst, Volker},
  title     = {TOWARDS STEREO VISION- AND LASER SCANNER-BASED UAS POSE ESTIMATION},
  series = {Digital Proceedings, International Conference on the Applications of Computer Science and Mathematics in Architecture and Civil Engineering : July 20 - 22 2015, Bauhaus-University Weimar},
  booktitle = {Digital Proceedings, International Conference on the Applications of Computer Science and Mathematics in Architecture and Civil Engineering : July 20 - 22 2015, Bauhaus-University Weimar},
  editor    = {G{\"u}rlebeck, Klaus and Lahmer, Tom},
  organization    = {Bauhaus-Universit{\"a}t Weimar},
  issn      = {1611-4086},
  doi       = {10.25643/bauhaus-universitaet.2807},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170314-28072},
  pages     = {7},
  abstract  = {A central issue for the autonomous navigation of mobile robots is to map unknown environments while simultaneously estimating its position within this map. This chicken-eggproblem is known as simultaneous localization and mapping (SLAM). Asctec's quadrotor Pelican is a powerful and flexible research UAS (unmanned aircraft system) which enables the development of new real-time on-board algorithms for SLAM as well as autonomous navigation. The relative UAS pose estimation for SLAM, usually based on low-cost sensors like inertial measurement units (IMU) and barometers, is known to be affected by high drift rates. In order to significantly reduce these effects, we incorporate additional independent pose estimation techniques using exteroceptive sensors. In this article we present first pose estimation results using a stereo camera setup as well as a laser range finder, individually. Even though these methods fail in few certain configurations we demonstrate their effectiveness and value for the reduction of IMU drift rates and give an outlook for further works towards SLAM.},
  subject      = {Angewandte Informatik},
  language  = {en}
}