The HAInich: A multidisciplinary vision data-set for a better understanding of the forest ecosystem

2023 | journal article. A publication with affiliation to the University of Göttingen.

Jump to:Cite & Linked | Documents & Media | Details | Version history

Cite this publication

​The HAInich: A multidisciplinary vision data-set for a better understanding of the forest ecosystem​
Milz, S.; Wäldchen, J.; Abouee, A.; Ravichandran, A. A.; Schall, P.; Hagen, C. & Borer, J. et al.​ (2023) 
Scientific Data10(1).​ DOI: 

Documents & Media

document.pdf2.91 MBAdobe PDF


GRO License GRO License


Milz, Stefan; Wäldchen, Jana; Abouee, Amin; Ravichandran, Ashwanth A.; Schall, Peter; Hagen, Chris; Borer, John; Lewandowski, Benjamin; Wittich, Hans-Christian; Mäder, Patrick
Abstract We present a multidisciplinary forest ecosystem 3D perception dataset. The dataset was collected in the Hainich-Dün region in central Germany, which includes two dedicated areas, which are part of the Biodiversity Exploratories - a long term research platform for comparative and experimental biodiversity and ecosystem research. The dataset combines several disciplines, including computer science and robotics, biology, bio-geochemistry, and forestry science. We present results for common 3D perception tasks, including classification, depth estimation, localization, and path planning. We combine the full suite of modern perception sensors, including high-resolution fisheye cameras, 3D dense LiDAR, differential GPS, and an inertial measurement unit, with ecological metadata of the area, including stand age, diameter, exact 3D position, and species. The dataset consists of three hand held measurement series taken from sensors mounted on a UAV during each of three seasons: winter, spring, and early summer. This enables new research opportunities and paves the way for testing forest environment 3D perception tasks and mission set automation for robotics.
Issue Date
Scientific Data 
Fakultät für Forstwissenschaften und Waldökologie ; Burckhardt-Institut ; Abteilung Waldbau und Waldökologie der gemäßigten Zonen 



Social Media