Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

Exploring the potential to use in-between pixel variability for early detection of bark beetle attacked trees

Olsson, Per-Ola LU ; Bergman, Hugo and Piltz, Karl LU orcid (2023) 26th AGILE Conference on Geographic Information Science In AGILE GIScience Series 4(1).
Abstract
The European spruce bark beetle (Ips typographus L.) is a major disturbance agent in Norway spruce (Picea abies (L.) Karst) forests in Europe and it is estimated that a changing climate will result in more severe outbreaks in the future. To reduce the risk of large outbreaks it is important to have methods that enable early detection of bark beetle attacks to help forest managers to prevent population build-up, e.g by sanitary cutting. Several studies have been devoted to early detection of bark beetle attacks with Sentinel-2 data with a focus on spectral properties and vegetation indices for early detection with pixel-based methods. In this study we explore the potential to use changes in variability between pixels in windows of different... (More)
The European spruce bark beetle (Ips typographus L.) is a major disturbance agent in Norway spruce (Picea abies (L.) Karst) forests in Europe and it is estimated that a changing climate will result in more severe outbreaks in the future. To reduce the risk of large outbreaks it is important to have methods that enable early detection of bark beetle attacks to help forest managers to prevent population build-up, e.g by sanitary cutting. Several studies have been devoted to early detection of bark beetle attacks with Sentinel-2 data with a focus on spectral properties and vegetation indices for early detection with pixel-based methods. In this study we explore the potential to use changes in variability between pixels in windows of different sizes (3×3, 4×4 and 5×5 pixels). We compute the coefficient of variation for four vegetation indices (NDVI, NDWI, CCI and NDRS) in a time-series of Sentinel-2 data during a bark beetle outbreak in Sweden that was triggered by a drought in 2018. The results indicate that CCI is the most promising index for early detection and that the variability between pixels increase in windows with attacked trees from late July when the main swarming was the second week of May. (Less)
Please use this url to cite or link to this publication:
author
; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
bark beetle, early detection, in-between pixel variability, Sentinel-2
host publication
26th AGILE Conference on Geographic Information Science “Spatial data for design”
series title
AGILE GIScience Series
editor
van Oosterom, Peter ; Ploeger, Hendrik ; Mansourian, Ali ; Scheider, Simon ; Lemmens, Rob and van Loenen, Bastiaan
volume
4
issue
1
edition
35
conference name
26th AGILE Conference on Geographic Information Science
conference location
Delft, Netherlands
conference dates
2023-06-13 - 2023-06-16
DOI
10.5194/agile-giss-4-35-2023
language
English
LU publication?
yes
id
b2b3abcb-42b8-4bb0-9763-575fa9cf3aac
alternative location
https://agile-giss.copernicus.org/articles/4/35/2023/agile-giss-4-35-2023.pdf
date added to LUP
2023-06-19 13:35:16
date last changed
2025-04-04 13:59:59
@inproceedings{b2b3abcb-42b8-4bb0-9763-575fa9cf3aac,
  abstract     = {{The European spruce bark beetle (Ips typographus L.) is a major disturbance agent in Norway spruce (Picea abies (L.) Karst) forests in Europe and it is estimated that a changing climate will result in more severe outbreaks in the future. To reduce the risk of large outbreaks it is important to have methods that enable early detection of bark beetle attacks to help forest managers to prevent population build-up, e.g by sanitary cutting. Several studies have been devoted to early detection of bark beetle attacks with Sentinel-2 data with a focus on spectral properties and vegetation indices for early detection with pixel-based methods. In this study we explore the potential to use changes in variability between pixels in windows of different sizes (3×3, 4×4 and 5×5 pixels). We compute the coefficient of variation for four vegetation indices (NDVI, NDWI, CCI and NDRS) in a time-series of Sentinel-2 data during a bark beetle outbreak in Sweden that was triggered by a drought in 2018. The results indicate that CCI is the most promising index for early detection and that the variability between pixels increase in windows with attacked trees from late July when the main swarming was the second week of May.}},
  author       = {{Olsson, Per-Ola and Bergman, Hugo and Piltz, Karl}},
  booktitle    = {{26th AGILE Conference on Geographic Information Science “Spatial data for design”}},
  editor       = {{van Oosterom, Peter and Ploeger, Hendrik and Mansourian, Ali and Scheider, Simon and Lemmens, Rob and van Loenen, Bastiaan}},
  keywords     = {{bark beetle; early detection; in-between pixel variability; Sentinel-2}},
  language     = {{eng}},
  month        = {{06}},
  number       = {{1}},
  series       = {{AGILE GIScience Series}},
  title        = {{Exploring the potential to use in-between pixel variability for early detection of bark beetle attacked trees}},
  url          = {{http://dx.doi.org/10.5194/agile-giss-4-35-2023}},
  doi          = {{10.5194/agile-giss-4-35-2023}},
  volume       = {{4}},
  year         = {{2023}},
}