There are currently several new technologies being used to generate digital elevation models that do not use photogrammetric techniques. For example, LiDAR (Laser Imaging Detection and Ranging) and RADAR (RAdio Detection And Ranging) can generate 3D points and reflectivity information of the surface without using a photogrammetric approach. In the case of LiDAR, the intensity level indicates the amount of energy that the object reflects after a laser pulse is transmitted. This energy mainly depends on the material and the wavelength used by LiDAR. This intensity level can be used to generate a synthetic image colored by this attribute (intensity level), which can be viewed as a RGB (red, green and blue) picture. This work presents the outline of an innovative method, designed by the authors, to generate synthetic pictures from point clouds to use in classical photogrammetric software (digital restitution or stereoscopic vision). This is conducted using available additional information (for example, the intensity level of LiDAR). This allows mapping operators to view the LiDAR as if it were stereo-imagery, so they can manually digitize points, 3D lines, break lines, polygons and so on.
How do the weather conditions typical of the polar maritime glaciers in the western Antarctic Peninsula region affect flight operations of fixed-wing drones and how should these be adapted for a successful flight? We tried to answer this research question through a case study for Johnsons and Hurd glaciers, Livingston Island, using a fixed-wing RPAS, in particular, a Trimble UX5 UAV with electric pusher propeller by brushless 700 W motor, chosen for its ability to fly long distances and reach inaccessible areas. We also evaluated the accuracy of the point clouds and digital surface models (DSM) generated by aerial photogrammetry in our case study. The results were validated against ground control points taken by differential GNSS techniques, showing an accuracy of 0.16 ± 0.12 m in the vertical coordinate. Various hypotheses were proposed and flight-tested, based on variables affecting the flight operation and the data collection, namely, gusty winds, low temperatures, battery life, camera configuration, and snow reflectivity. We aim to provide some practical guidelines that can help other researchers using fixed-wing drones under climatic conditions similar to those of the South Shetland Islands. Performance of the drone under harsh weather conditions, the logistical considerations, and the amount of snow at the time of data collection are factors driving the necessary modifications from those of conventional flight operations. We make suggestions concerning wind speed and temperature limitations, and avoidance of sudden fog banks, aimed to improve the planning of flight operations. Finally, we make some suggestions for further research.
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