EGU22-2203
https://doi.org/10.5194/egusphere-egu22-2203
EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Automotive lidar in the Arctic: 3D monitoring and mapping

Birgit Schlager1,2, Thomas Goelles1,3, Stefan Muckenhuber1,3, Tobias Hammer1,3, Kim Senger4, Rüdiger Engel5, Christian Bobrich5, and Daniel Watzenig1,2
Birgit Schlager et al.
  • 1Virtual Vehicle Research GmbH, Graz, Austria (birgit.schlager@v2c2.at, thomas.goelles@v2c2.at, stefan.muckenhuber@v2c2.at, daniel.watzenig@v2c2.at)
  • 2Institute of Automation and Control, Graz University of Technology, Graz, Austria (birgit.schlager@tugraz.at, daniel.watzenig@tugraz.at)
  • 3Department of Geography and Regional Science, University of Graz, Graz, Austria (thomas.goelles@uni-graz.at, stefan.muckenhuber@uni-graz.at, hammer.tobias@gmx.de)
  • 4Arctic Geology, The University Centre in Svalbard, Longyearbyen, Norway (kims@unis.no)
  • 5FURUNO DEUTSCHLAND GmbH, Rellingen, Germany (r.engel@furuno.de, c.bobrich@furuno.de)

We enable exciting and novel mapping and monitoring use cases for automotive lidar technologies in the Arctic. Originally, these lidar technologies were developed for enabling environment perception of automated vehicles with high spatial resolution and accuracy. Therefore, these lidar sensors have several advantages for mobile mapping applications in the Arctic compared to commonly used technologies like time-lapse cameras and satellite or aerial photogrammetry that suffer from lower accuracy of 3-dimensional (3D) data than the proposed automotive lidar sensors. At present, terrestrial laser scanners (TLS), like the Riegl VZ-6000, are commonly used in the Arctic. However, especially for mobile use cases, the automotive lidar provides a lot of advantages compared to TLS, for instance lower cost, more robust, smaller, and lighter and thus more portable. Therefore, automotive lidar sensors open the door for new mobile mapping and monitoring applications in the Arctic.

The data acquisition hardware consists of a sensor unit, a data logger, and batteries. The sensor unit integrates an automotive lidar, the Ouster OS1-64 Gen1, a ublox multi-band active global navigation satellite system (GNSS) antenna, and a Xsens 9-axis inertial measurement unit (IMU) with a gyroscope, an accelerometer, and a magnetometer. Furthermore, a long-term evolution (LTE) stick is integrated for retrieving real time kinematic (RTK) data. In a post-processing step, collected point clouds and IMU data can be used by a simultaneous localization and mapping (SLAM) algorithm for point cloud stitching with one big point cloud and the trajectory of the mapping sensor as a result, i.e., a map of the scanned environment. Optionally, the differential global positioning system (DGPS) data can be used additionally by the SLAM algorithm. The setup can be mounted in multiple ways to support a wide variety of new applications, e.g., on a handle, car, ship, or snowmobile.

We used the introduced setup for several applications and successfully mapped glacier caves and surrounding glacier surfaces on Longyearbreen and Larsbreen in Svalbard as one example of a novel Arctic use case. Furthermore, we showed that the setup is working on a ship scanning a harbor in Croatia. In this measurement campaign, we used a multi-beam sonar from Furuno in addition to our mapping setup which made it possible to map the coast above and below the water surface.

Therefore, we suggest several new applications of automotive lidar sensors in the Arctic, e.g., monitoring coastal erosions due to permafrost thawing and mapping glacier fronts. In this way, accurate outlines and structures of coasts and calving glacier fronts can be generated. Such data will be relevant for future development of glacier calving models. Furthermore, the setup can be used for monitoring glacier fronts over a period of several years. Further research may also include merging the gained 3D map with photogrammetry data to generate highly accurate 3D models of a glacier front with textural details. Another novel Arctic use case could be time-lapse scans of infrastructure, e.g., runway, roads, or cultural heritage, that is affected by the thawing permafrost to track its changes and movements cost-effectively.

How to cite: Schlager, B., Goelles, T., Muckenhuber, S., Hammer, T., Senger, K., Engel, R., Bobrich, C., and Watzenig, D.: Automotive lidar in the Arctic: 3D monitoring and mapping, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2203, https://doi.org/10.5194/egusphere-egu22-2203, 2022.

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