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Comparing spectral differences between healthy and early infested spruce forests caused by bark beetle attacks using satellite images
Swedish University of Agricultural Sciences, Sweden.
Swedish University of Agricultural Sciences, Sweden.
Linnaeus University, Faculty of Technology, Department of Forestry and Wood Technology. Swedish University of Agricultural Sciences, Sweden. (DISA;DISA-WBT)ORCID iD: 0000-0002-7913-8592
Swedish University of Agricultural Sciences, Sweden.
2022 (English)In: IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, Hybrid Symposium, Kuala Lumpur, Malaysia, 17-21 July, 2022, IEEE, 2022, p. 7709-7712Conference paper, Published paper (Refereed)
Sustainable development
SDG 15: Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss
Abstract [en]

Detecting forest insect damage before the visible discoloration (green attacks) using remote sensing data is challenging, but important for damage control. In recent years, the European spruce bark beetle (Ips typographus, L.) has damaged large amounts of forest in Europe. However, it is still debatable how early the infestations can be detected with remote sensing data. Some studies showed a spectral difference between healthy and green-attacked spruce trees at the plot level, while others showed that spectral  differences existed before attacks. Therefore, a hypothesis is proposed that no spectral difference can be identified between green-attacked forests compared to healthy forests if the differences do not exist before the attacks. In this study, we tested this hypothesis using Sentinel-2 and WorldView-3 SWIR images on 24 healthy plots and 24 plots with mild, moderate, and severe attacks. In the results, the severely attacked plots did not show significant spectral differences in the Sentinel-2 images until August, and the sensitivity was found in the blue, red, red-edge, and SWIR band. Only the red band showed a significant difference between the healthy and moderately attacked plots in August, and only the blue, red, and SWIR band showed significant differences in September, October, and November. No significant differences were observed in the WorldView-3 images at the plot or individual tree level. We accepted the hypothesis that green attacks do not show spectral differences with the healthy forests when the differences do not exist before the attacks. We concluded that the SWIR bands were sensitive to attacks in the Sentinel-2 images with 10 m resolution, but not in the WorldView-3 images with 3.7 m resolution. Further studies are needed to explore the methodology of using WorldView-3 SWIR images for the early detection of forest infestation.

Place, publisher, year, edition, pages
IEEE, 2022. p. 7709-7712
National Category
Forest Science
Research subject
Technology (byts ev till Engineering), Forestry and Wood Technology; Environmental Science, Natural Resources Management
Identifiers
URN: urn:nbn:se:lnu:diva-120198DOI: 10.1109/IGARSS46834.2022.9883420Scopus ID: 2-s2.0-85140354350ISBN: 9781665427920 (electronic)ISBN: 9781665427937 (print)OAI: oai:DiVA.org:lnu-120198DiVA, id: diva2:1750248
Conference
IEEE International Geoscience and Remote Sensing Symposium, 17-22 July 2022, Kuala Lumpur, Malaysia
Available from: 2023-04-12 Created: 2023-04-12 Last updated: 2024-05-06Bibliographically approved

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Fransson, Johan

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