Early detection of changes in health status of Norway spruce using hyperspectral data Markus Immitzer , Kathrin Einzmann , Wai-Tim Ng , Lea Henning , Nicole Pinnel , Adelheid Wallner , 4 5 3 1 Matthias Frost , Monika Kanzian , Rudolf Seitz and Clement Atzberger 1
1
1
2
2
1
3
2
University of Natural Resources and Life Sciences, Institute of Surveying, Remote Sensing and Land Information (IVFL), Austria; German Remote Sensing Data Center, German 3 4 Aerospace Center (DLR), Weßling, Germany; Bavarian State Institute of Forestry (LWF), Information Technology Freising, Germany; Bavarian State Forest enterprice (BaySF), 5 Information and Communication Technology, Munich, Germany; Austrian State Forest Enterprise (ÖBf), Research and Development, Purkersdorf, Austria Contact: Markus Immitzer;
[email protected]
Introduction
The spectral signature of a tree and its foliage provides valuable insights in its vitality. Moreover, leaf and needle spectral signatures facilitate a detailed assessment for the plant’s physiological status and enables tree species identification through remote sensing. Furthermore, the spectra are important for sensor design studies and various up-scaling tasks. However, collecting and analyzing representative leaf and
needle samples is a complex process, given the growth patterns of trees with a huge vertical extent and complicated 3D structures. For the comparison of stressed and unstressed trees, we artificially stressed some spurce trees and observed those trees over time, together with an equal number of (nonstressed) control trees. For analyzing the needle we used the approach described in Einzmann et al. (2014).
The aims of our study are: • collecting spectral data with portable spectroradiometers for monitoring the needle status of Norway spruce (Picea abies, L.) • compare the spectral behavior of unstressed and manual stressed trees • detecting the point in time of first changes in needle spectra
Material and Methods Study site and needle collection
Ring barking (girdling)
Needle sampling included: • sample retrieval by tree climbers • 16 sample trees (8 control, 8 ring barked) • 1 - 2 branches per tree • branches from the sun lit part of the crown • taken between the 12th and 16th whorl
Needle preparation
A strip of bark was completely removed at breast height at half of our sample trees (n=140), no changes at the second half (control trees).
Needles were collected seven times throughout the growing seasons 2013 and 2014 from two Norway spruce stands, located near Altötting, southeast Germany.
In the field the collected twigs were separated by the last four growing seasons (2010 - 2013) and refrigerated overnight in zip lock bags. Before running the spectral needle measurements: • 5 - 6 twigs were selected • needles removed from the twigs (approximate 5 g) • needles placed on a non-reflective plate
Contact probe
• ASD Fieldspec® Pro (Analytical Spectral Devices) Spectroradiometer • light source: integrated 100 W halogen reflectorized lamp • for each tree the needles of the four last needle age classes were measured separately • 30 spectra taken per sample and averaged afterwards • sample rearranged after every measurement • white reference run before starting a sample
Spectral correction, statistics and similarity measures
• manual removal of outliers and irregularities • spectralon and offset correction with the AS toolbox (Dorigo et al. 2006) • calculating mean values and standard deviations of spectra • calculating similarity measures (SAM, SID, DU, PCA) (Cho et al. 2010, Du et al. 2004, Einzmann et al. 2014, Henning 2014 and Kruse et al. 1993)
Results
Conclusions and Outlook
Needle spectra: • high variance in reflectance spectra between needle age classes – separation necessary • all used methods for comparing the needle spectra (various similarity measurements, PCA) showed the same trends • no major changes in needle spectra of stressed trees (ring barked) were detectable for nearly one year (Fig. 1) • changes could be seen beter (Fig. 1) in needles with higher age (3 and 4 year old needles) • trees that were ring barked and subsequently infested by bark beetle revealed major changes in spectra (Fig. 2a, b), caused by changes of chlorophyll content, cell structure and water content.
More detailed analysis of needle spectra are planned, including chemical analysis for better understanding of n eedle spectra. Also a comparison of the laboratory data with airborne hyperspectral data (HySpex), recorded as a dense time series (13 overflights), will be done in cooperation with DLR and LWF. These analysis will be carried out on individual tree level.
Measuring approach: The contact probe offers a user-friendly approach for measuring needles: no difference between measured spectra compared with fore optics could be observed. The contact probe can be applied both in field and in laboratory, performs fast and can handle small sample sizes and can be carried out in-situ independently of weather conditions (Einzmann et al. 2014).
Fig. 1: Spectral Angle Mapper comparison of sampling date 2 - 7 with the 1st sampling date
Acknowledgments
The study was part of the Project E 54 “VitTree: Automated assessment of forest tree vitality using up-to-date optical satellite data with enhanced spectral and spatial resolution” funded by the Bavarian State Ministry of Food, Agriculture and Forestry. The authors would like to thank the tree-climbing team, Alfred Wörle and his colleagues. Thanks to BaySF and ÖBf for providing the test sites.
The used method is a flexible and user-friendly approach for measuring needle reflectance. Contrary to our expectations spruce can handle artificially induced stress (ring barking at breast hight) for quite a long time. In the first year nearly no changes in the reflection of the needles were recognized. However, increased needle loss was observed, especially of older needles. This will probably directly influence the reflection of the tree crown. The weakening also raised the risk of bark beetle infestation. This additional stress increased both the changes in needle reflectance and the needle loss. Ring barking at a higher position as at breast heights - preferable near the crown - could possibly lead to a faster accumulation of assimilates in the needles. Due to that, an earlier shift in needle spectra would be achieved.
Fig. 2a: Needle spectra of one ring barked tree sample collected on the 4th sampling date (needle age class 2012)
References:
Cho, M.A., Debba, P., Mathieu, R., Naidoo, L., Van Aardt, J., & Asner, G.P. 2010. Improving discrimination of savanna tree species through a multiple-endmember spectral angle mapper approach: Canopy-level analysis. IEEE Transactions on Geoscience and Remote Sensing 48 (11): p. 4133–4142. Dorigo, W., Bachmann, M., & Heldens, W. 2006. AS Toolbox & Processing of field spectra. Wessling: DLR Team Applied Spectroscopy, Department Land Surface. Du, Y., Chang, C.-I., Ren, H., Chang, C.-C., Jensen, J.O., & D’Amico, F.M. 2004. New hyperspectral discrimination measure for spectral characterization. Optical Engineering 43 (8): p. 1777–1785.
Fig. 2b: Needle spectra of one ring barked tree sample collected on the 7th sampling date (needle age class 2012) Einzmann, K., Ng, W., Immitzer, M., Bachmann, M., Pinnel, N., & Atzberger, C. 2014. Method analysis for collecting and processing in-situ hyperspectral needle reflectance data for monitoring Norway spruce. Photogrammetrie - Fernerkundung - Geoinformation 2014 (5): p. 351–367. Henning, L. 2014. Early recognition of changes in the health status of Norway spruce with hyperspectral data. Master Thesis. Eberswalde. Kruse, F.A., Lefkoff, A.B., Boardman, J.W., Heidebrecht, K.B., Shapiro, A.T., Barloon, P.J., & Goetz, A.F.H. 1993. The spectral image processing system (SIPS)-interactive visualization and analysis of imaging spectrometer data. Remote Sensing of Environment 44( 2-3): p. 145–163.
