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Early detection of spruce vitality loss with hyperspectral data: Results of an experimental study in Bavaria, Germany

Einzmann, Kathrin and Atzberger, Clement and Pinnel, Nicole and Glas, Christina and Böck, Sebastian and Seitz, Rudolf and Immitzer, Markus (2021) Early detection of spruce vitality loss with hyperspectral data: Results of an experimental study in Bavaria, Germany. Remote Sensing of Environment, 266 (112676), pp. 1-18. Elsevier. doi: 10.1016/j.rse.2021.112676. ISSN 0034-4257.

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Official URL: https://www.sciencedirect.com/science/article/pii/S0034425721003965


Vitality loss of trees caused by extreme weather conditions, drought stress or insect infestations, are expected to increase with ongoing climate change. The detection of vitality loss at an early stage is thus of vital importance for forestry and forest management to minimize ecological and economical damage. Remote sensing instruments are able to detect changes over large areas down to the level of individual trees. The scope of our study is to investigate whether it is possible to detect stress-related spectral changes at an early stage using hyperspectral sensors. For this purpose, two Norway spruce (Picea abies) forest stands, both different in age and maintenance, were monitored in the field over two vegetation periods. In parallel, time series of airborne hyperspectral remote sensing data were acquired. For each stand 70 trees were artificially stressed (ring-barked) and 70 trees were used as control trees. The data collected in south-eastern Germany consists of measurements at multiple times and at different scales: (1) crown conditions were visually assessed in the field (2) needle reflectance spectra were acquired in the laboratory using a FieldSpec spectrometer, and (3) hyperspectral airborne data (HySpex) were flown at 0.5 m spatial resolution. We aimed for a simultaneous data acquisition at the three levels. This unique data set was investigated whether any feature can be discriminated to detect vitality loss in trees at an early stage. Several spectral transformations were applied to the needle and tree crown spectra, such as spectral derivatives, vegetation indices and angle indices. All features were examined for their separability (ring-barked vs. control trees) with the Random Forest (RF) classification algorithm. As result, the younger, well maintained forest stand only showed minor changes over the 2-year period, whereas changes in the older forest stand were observable both in the needle and in the hyperspectral tree crown spectra, respectively. These changes could even be detected before changes were visible by field observations. The tree spectral reactions to ring-barking were first noticeable 11 months after ring-barking and 6 weeks before they were visible by field inspection. The most discriminative features for separating the two groups were the reflectance spectra and the spectral derivatives, over the VIs or angle indices. The tree crown spectra of the two groups could be separated by the RF classifier with a 79% overall accuracy at the beginning of the second vegetation period and 1 month later with 92% overall accuracy with high kappa index. The results clearly demonstrate the great potential of hyperspectral remote sensing in detecting early vitality changes of stressed trees.

Item URL in elib:https://elib.dlr.de/144637/
Document Type:Article
Title:Early detection of spruce vitality loss with hyperspectral data: Results of an experimental study in Bavaria, Germany
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Pinnel, NicoleUNSPECIFIEDhttps://orcid.org/0000-0003-1978-3204UNSPECIFIED
Seitz, RudolfBayerische Landesanstalt für Wald und ForstUNSPECIFIEDUNSPECIFIED
Date:21 September 2021
Journal or Publication Title:Remote Sensing of Environment
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:Yes
Page Range:pp. 1-18
Keywords:Hyperspectral data; Forest health; Vitality loss; Random Forest; Ring-barking; HySpex;
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Remote Sensing and Geo Research, R - Optical remote sensing
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > International Ground Segment
Deposited By: Pinnel, Dr.rer.nat Nicole
Deposited On:22 Oct 2021 10:09
Last Modified:28 Jun 2023 13:18

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