Sensitivity of Landsat-8 OLI and TIRS Data to Foliar Properties of Early Stage Bark Beetle (Ips typographus, L.) Infestation



In this study, the early stage of European spruce bark beetle (Ips typographus, L.) infestation (so-called green attack) is investigated using Landsat-8 optical and thermal data. We conducted an extensive field survey in June and the beginning of July 2016, to collect field data measurements from a number of infested and healthy trees in the Bavarian Forest National Park (BFNP), Germany. In total, 157 trees were selected, and leaf traits (i.e. stomatal conductance, chlorophyll fluorescence, and water content) were measured. Three Landsat-8 images from May, July, and August 2016 were studied, representing early stage, advanced stage, and post-infestation, respectively. Spectral vegetation indices (SVIs) sensitive to the measured traits were calculated from the optical domain (VIS, NIR and SWIR), and canopy surface temperature (CST) was calculated from the thermal infrared band using the Mono-window algorithm. The leaf traits were used to examine the impact of bark beetle infestation on the infested trees and to explore the link between these traits and remote sensing data (CST and SVIs). The differences between healthy and infested samples regarding measured leaf traits were assessed using the Student’s t-test. The relative importance of the CST and SVIs for estimating measured leaf traits was evaluated based on the variable importance of the projection (VIP) obtained from the partial least square regression (PLSR) analysis. A temporal comparison was then made for SVIs with a VIP > 1, including CST, using boxplot. Finally, the clustering method using a principal components analysis (PCA) was used to visually examine how well the two groups of sample plots (healthy and infested) are separated in 2-D space based on principal component scores. The results revealed that all measured leaf traits were significantly different (p <0.05) between healthy versus infested samples, and CST was found to has a stronger correlation with all measured leaf traits compared to SVIs. Moreover, the study showed that CST was superior to the SVIs in detecting subtle canopy changes due to bark beetle infestation for the three months considered in this study. Results showed that CST is an essential variable for estimating measured leaf traits VIP > 1, improving the results of clustering when used with other SVIs. The new insight offered by this study is that the stress induced by the early stage of bark beetle infestation is more pronounced by Landsat-8 thermal bands than the SVIs calculated from its optical bands. The potential of CST in detecting the green attack stage would have positive implications for the forest practice.

Date made available23 Jun 2019
PublisherDATA Archiving and Networked Services (DANS)
Temporal coverageMay 2016 - Aug 2016
Date of data production15 Feb 2019

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