The browser you are using is not supported by this website. All versions of Internet Explorer are no longer supported, either by us or Microsoft (read more here: https://www.microsoft.com/en-us/microsoft-365/windows/end-of-ie-support).

Please use a modern browser to fully experience our website, such as the newest versions of Edge, Chrome, Firefox or Safari etc.

PerOla

Per-Ola Olsson

Researcher

PerOla

Examining the potential for early detection of spruce bark beetle attacks using multi-temporal Sentinel-2 and harvester data

Author

  • Sadegh Jamali
  • Per Ola Olsson
  • Arsalan Ghorbanian
  • Mitro Müller

Summary, in English

Forests are invaluable terrestrial ecosystems with considerable economic, ecological, and environmental benefits. Bark beetles have been recognized as one of the major causes of forest disturbance, and climate change can exacerbate their impact, leading to more tree mortality. Early detection of bark beetle attacks is vital to reduce forest loss and devastating consequences. This study examines the potential for early detection of European spruce bark beetle (Ips typographus L.) attacks in southeastern Sweden using comprehensive harvester data and time series of Sentinel-2 images, 2015–2021. Specifically, it aims at 1) determining the most pronounced wavelength bands and vegetation indices (VIs) of Sentinel-2 for early detection, 2) determining the number of attacked trees in a Sentinel-2 pixel required to enable detection, 3) testing three change detection approaches, Detecting Breakpoints and Estimating Segments in Trend (DBEST), Mean-Level-Shift (MLS), and Cumulative Sum (CUSUM) to investigate the potential for early detection of bark beetle attacks. The greatest separation in reflectance between healthy and attacked pixels, from first swarming peak (May 2018) till harvesting (April 2019), was observed in the SWIR1 (0.018) and SWIR2 (0.011) bands followed by red-edge (0.008), red (0.007), NIR (0.005), and the green band (0.004). The blue band showed the least separation (0.003). All VIs showed a change in their base level after the swarming and this was more prominent for NDRS with an increase of 0.14, followed by NDWI (-0.13), CCI (-0.11) and NDVI (-0.09), all with decreasing values. The observed responses of VIs in relation to the number of attacked trees in a Sentinel-2 pixel increased gradually for pixels having one to ten infested trees, with the strongest response observed for pixels with 9 to 14 attacked trees. Pixels including more than 14 attacked trees did not show any further substantial change in VIs. DBEST, on average, indicated that the infestation impact on VIs is detectable one month after the swarming peak with a 15–31 days precision. MLS and CUSUM with up to two months' accuracies were ranked next. NDRS and CCI showed superior detection performance compared to NDVI and NDWI. The detection was based on smoothed time series of Sentinel-2 data to reduce the influence of noise and missing data and cannot be directly applied to a near real-time detection method.

Department/s

  • Transport and Roads
  • Department of Technology and Society
  • Dept of Physical Geography and Ecosystem Science
  • BECC: Biodiversity and Ecosystem services in a Changing Climate
  • eSSENCE: The e-Science Collaboration
  • MERGE: ModElling the Regional and Global Earth system

Publishing year

2023

Language

English

Pages

352-366

Publication/Series

ISPRS Journal of Photogrammetry and Remote Sensing

Volume

205

Document type

Journal article

Publisher

Elsevier

Topic

  • Physical Geography

Keywords

  • Early change detection
  • European spruce bark beetle
  • Forest disturbance
  • Sentinel-2
  • Time series analysis

Status

Published

ISBN/ISSN/Other

  • ISSN: 0924-2716