2024-03-29T06:46:55Zhttp://doidb.wdc-terra.org/oaip/oaioai:doidb.wdc-terra.org:51362014-04-24T15:27:31ZDOIDBDOIDB.TR32DB
10.5880/TR32DB.KGA94.5
Drauschke, Martin
Bartelsen, Jan
Reidelstuerz, Patrick
Towards UAV-based Forest Monitoring
Geographisches Institut der Universität zu Köln - Kölner Geographische Arbeiten
2014
UAV
Remote Sensing
Environmental Monitoring
Airborne Measurements
Forest
550 Earth sciences
Bendig, Juliane
Bareth, Georg
CRC/TR32 Database (TR32DB)
University of Cologne, Regional Computing Centre (RRZK)
2014-04-14
eng
Workshop paper
12 Pages
2793 Kilobytes
application/pdf
Creative Commons Attribution 3.0 Unported (CC BY 3.0)
In this paper, we describe two experiments regarding the monitoring of a test site in the Bavarian Forest National Park using unmanned aerial vehicles (UAVs) and we show their results. In the first experiment, we show that it is possible to relatively orient the RGB images acquired by a small UAV in power glider configuration without any flight stabilisation and without integrated navigation system (INS) initial values. This enables a 3D scene reconstruction, i.e., we obtain a point cloud showing distinctive 3D points. A much denser point cloud showing trees with branches can be derived from dense image matching. In the second experiment, we demonstrate how multispectral imagery can be interpreted on demand, i.e., without producing an ortho-mosaic, but using reliable features and a powerful classifier. With our algorithm, we follow up the aim to detect bark beetle attack in an early infection stage in Sitka spruce, Picea sitchensis, in the Bavarian Forest National Park.