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Monitoring selective logging in a pine dominated forest in Central Germany with repeated drone flights utilizing a low cost RTK quadcopter

Thiel, Christian und Müller, Marlin und Christian, Berger und Felix, Cremer und Dubois, Clémence und Hese, Sören und Baade, Jussi und Klan, Friederike und Pathe, Carsten (2020) Monitoring selective logging in a pine dominated forest in Central Germany with repeated drone flights utilizing a low cost RTK quadcopter. Remote Sensing, Seiten 1-26. Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/drones4020011. ISSN 2072-4292.

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Kurzfassung

There is no doubt that unmanned aerial systems (UAS) will play an increasing role in Earth observation in the near future. The field of application is very broad and includes aspects of environmental monitoring, security, humanitarian aid, or engineering. In particular drones with camera systems are already widely used. The capability to compute ultra-high resolution orthomosaics and 3D point clouds from UAS imagery generates a wide interest in such systems in the science community but also in industry and agencies. In particular forestry sciences benefit from ultrahigh structural and spectral information as regular tree level-based monitoring becomes feasible. There is a great need for this kind of information as, for example, due to the spring and summer droughts in Europe in the years 2018/2019, large quantities of individual trees were damaged or even died. This study focuses on selective logging at the level of individual trees using repeated drone flights. Using the new generation of UAS, which allows for sub-decimeter-level positioning accuracies, a change detection approach based on bi-temporal UAS acquisitions was implemented. In comparison to conventional UAS, the effort of implementing repeated drone flights in the field was low because no ground control points needed to be surveyed. As shown in this study, the geometrical offset between the two collected datasets was below 10 cm across the site, which enabled a direct comparison of both datasets without the need for post-processing (e.g., image matching). For the detection of logged trees, we utilized the spectral and height difference between both acquisitions. For their delineation, an object-based approach was employed which was proven to be highly accurate (precision = 97.5%; recall = 91.6%). Due to the ease of use of such new generation, off-the-shelf consumer drones, their decreasing purchase costs, the quality of available workflows for data processing, and the convincing results presented here, UAS-based data can and should complement conventional forest inventory practices.

elib-URL des Eintrags:https://elib.dlr.de/139894/
Dokumentart:Zeitschriftenbeitrag
Titel:Monitoring selective logging in a pine dominated forest in Central Germany with repeated drone flights utilizing a low cost RTK quadcopter
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Thiel, ChristianChristian.Thiel (at) dlr.dehttps://orcid.org/0000-0001-5144-8145NICHT SPEZIFIZIERT
Müller, MarlinDLR JenaNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Christian, BergerStadt JenaNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Felix, CremerDLR JenaNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Dubois, ClémenceFSU JenaNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Hese, SörenFSU JenaNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Baade, JussiFriedrich-Schiller-Universität JenaNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Klan, FriederikeFriederike.Klan (at) dlr.dehttps://orcid.org/0000-0002-1856-7334NICHT SPEZIFIZIERT
Pathe, CarstenDLR JenaNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Datum:9 April 2020
Erschienen in:Remote Sensing
Referierte Publikation:Ja
Open Access:Ja
Gold Open Access:Ja
In SCOPUS:Ja
In ISI Web of Science:Ja
DOI:10.3390/drones4020011
Seitenbereich:Seiten 1-26
Verlag:Multidisciplinary Digital Publishing Institute (MDPI)
ISSN:2072-4292
Status:veröffentlicht
Stichwörter:UAS, RTK quadcopter; structure from motion; repeated flights; change detection; forestry, selective logging, forest degradation
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Raumfahrt
HGF - Programmthema:keine Zuordnung
DLR - Schwerpunkt:Raumfahrt
DLR - Forschungsgebiet:R - keine Zuordnung
DLR - Teilgebiet (Projekt, Vorhaben):R - keine Zuordnung
Standort: Jena
Institute & Einrichtungen:Institut für Datenwissenschaften > Bürgerwissenschaften
Hinterlegt von: Thiel, Christian
Hinterlegt am:07 Jan 2021 14:26
Letzte Änderung:25 Okt 2023 08:13

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