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

DOI

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 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.

The satellite data can be downloaded from USGS (open access ) . These are the image ID:LANDSAT_SCENE_ID = "LC81920262016240LGN00 (27-08-2016)LANDSAT_SCENE_ID = "LC81920262016192LGN00" (10-07-2016)LANDSAT_SCENE_ID = "LC81920262016128LGN00" (07-05-2016)

Identifier
DOI https://doi.org/10.17026/dans-24k-ydsj
Metadata Access https://phys-techsciences.datastations.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.17026/dans-24k-ydsj
Provenance
Creator HAIDI Abdullah
Publisher DANS Data Station Phys-Tech Sciences
Contributor M Th Koelen
Publication Year 2019
Rights DANS Licence; info:eu-repo/semantics/closedAccess; https://doi.org/10.17026/fp39-0x58
OpenAccess false
Contact M Th Koelen (Faculty of Geo-Information Science and Earth Observation)
Representation
Resource Type Dataset
Format application/octet-stream; application/dbf; application/prj; application/sbn; application/sbx; application/shp; text/xml; application/shx; application/zip; application/matlab-mat
Size 5; 915; 571; 132; 116; 140636; 16068; 108; 22370; 1520; 286; 2248
Version 2.0
Discipline Agricultural Sciences; Agriculture, Forestry, Horticulture, Aquaculture; Agriculture, Forestry, Horticulture, Aquaculture and Veterinary Medicine; Life Sciences