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Multi-sensor data acquisition for assessing the condition of vegetation

 
: Stemmler, Simon; Wiedenmann, Dominic

:
Postprint urn:nbn:de:0011-n-6404066 (1.7 MByte PDF)
MD5 Fingerprint: 3c7033b5b3bf972e0092dc9160cd4516
Copyright Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
Erstellt am: 16.9.2021


Neale, C.M.U. ; Society of Photo-Optical Instrumentation Engineers -SPIE-, Bellingham/Wash.:
Remote Sensing forAgriculture, Ecosystems, and Hydrology XXIII : SPIE Remote Sensing, 13-18 September 2021
Bellingham, WA: SPIE, 2021 (Proceedings of SPIE 11856)
Paper 118560L, 8 S.
Remote Sensing Digital Forum <2021, Online>
Englisch
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IPM ()
Multi-Sensor; UAV; Laser Scanning; Photogrammetry; Data Fusion

Abstract
The pressure on vegetation, whether forests, meadows or cultivated areas, is becoming increasingly greater. Climate change, extreme weather and ever higher yields taking place at the same time are creating enormous challenges for areas under cultivation. Drought stress, heavy rains and cultivation of monocultures stress both, the soil and the crops themselves. Regular monitoring of the crops or trees as well as soil condition is essential for a sustainable land use. The use of unmanned aerial vehicles (UAVs) for aerial structural surveys, the recording of soil parameters such as soil temperature, soil moisture and gas exchange have so far mostly been carried out independently of each other. Combining these measurement techniques, a holistic picture of the state of these ecosystems becomes possible. The Fraunhofer-Institute for Physical Measurement Techniques IPM presents a coherent process chain for the fully comprehensive recording of ecosystems. A recording by means of LiDAR systems from the ground, multispectral aerial images, terrestrial laser scans and the recording of nitrous oxide emission. Thus, we obtain a full structural image of the ecosystem enriched with metadata on plant condition and soil parameters. This forms the basis of an analysis of the overall condition of the full ecosystem. We present the results of the different sensors and the fused data of a first measurement campaign.

: http://publica.fraunhofer.de/dokumente/N-640406.html