Advanced

Near real-time monitoring of insect induced defoliation in subalpine birch forests with MODIS derived NDVI

Olsson, Per Ola LU ; Lindström, Johan LU and Eklundh, Lars LU (2016) In Remote Sensing of Environment 181. p.42-53
Abstract

Forestry and nature conservation can benefit from rapid on-line information on forest disturbances, such as insect attacks. This type of information would facilitate timely field studies and enable more rapid counter measures, as well as enable studies of the dynamics of an insect outbreak. In this study we developed a method based on MODIS derived NDVI for near real-time monitoring of insect induced forest defoliation in a subalpine birch forest in northern Sweden. The method is based on deviations from a seasonal trajectory of NDVI representing forest conditions without disturbances. A Kalman filter is applied to handle noise and satellite-derived NDVI observations of low quality, and cumulative sums (CUSUM) of the deviations from the... (More)

Forestry and nature conservation can benefit from rapid on-line information on forest disturbances, such as insect attacks. This type of information would facilitate timely field studies and enable more rapid counter measures, as well as enable studies of the dynamics of an insect outbreak. In this study we developed a method based on MODIS derived NDVI for near real-time monitoring of insect induced forest defoliation in a subalpine birch forest in northern Sweden. The method is based on deviations from a seasonal trajectory of NDVI representing forest conditions without disturbances. A Kalman filter is applied to handle noise and satellite-derived NDVI observations of low quality, and cumulative sums (CUSUM) of the deviations from the seasonal trajectory representing undisturbed forests are used to detect disturbances. An annual offset of the seasonal trajectory is introduced in CUSUM to handle inter-annual variability in the start of season. Evaluation of the method showed that 74% of the defoliation was detected with a misclassification of undisturbed areas of 39% in MODIS pixels with at least 50% birch forest cover. The ability of the method to detect defoliation can be adjusted to fit the purpose of a study; with a higher threshold applied, 100% of the defoliation in the evaluation data was detected with 56% of the undisturbed areas misclassified as defoliated. The method also facilitates studies of the intra-seasonal temporal dynamics of an insect outbreak, which is a major advantage compared to methods that classifies pixels into undisturbed or defoliated for an entire season. Furthermore, the method can be extended to monitor within-season refoliation after an insect outbreak.

(Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Insect defoliation monitoring, Kalman filter, MODIS, NDVI, Near real-time
in
Remote Sensing of Environment
volume
181
pages
12 pages
publisher
Elsevier
external identifiers
  • scopus:84962786755
  • wos:000377730200004
ISSN
0034-4257
DOI
10.1016/j.rse.2016.03.040
language
English
LU publication?
yes
id
3435f763-9d66-48c4-9256-8c738ccaa8c0
date added to LUP
2016-04-28 15:58:37
date last changed
2017-06-11 05:05:04
@article{3435f763-9d66-48c4-9256-8c738ccaa8c0,
  abstract     = {<p>Forestry and nature conservation can benefit from rapid on-line information on forest disturbances, such as insect attacks. This type of information would facilitate timely field studies and enable more rapid counter measures, as well as enable studies of the dynamics of an insect outbreak. In this study we developed a method based on MODIS derived NDVI for near real-time monitoring of insect induced forest defoliation in a subalpine birch forest in northern Sweden. The method is based on deviations from a seasonal trajectory of NDVI representing forest conditions without disturbances. A Kalman filter is applied to handle noise and satellite-derived NDVI observations of low quality, and cumulative sums (CUSUM) of the deviations from the seasonal trajectory representing undisturbed forests are used to detect disturbances. An annual offset of the seasonal trajectory is introduced in CUSUM to handle inter-annual variability in the start of season. Evaluation of the method showed that 74% of the defoliation was detected with a misclassification of undisturbed areas of 39% in MODIS pixels with at least 50% birch forest cover. The ability of the method to detect defoliation can be adjusted to fit the purpose of a study; with a higher threshold applied, 100% of the defoliation in the evaluation data was detected with 56% of the undisturbed areas misclassified as defoliated. The method also facilitates studies of the intra-seasonal temporal dynamics of an insect outbreak, which is a major advantage compared to methods that classifies pixels into undisturbed or defoliated for an entire season. Furthermore, the method can be extended to monitor within-season refoliation after an insect outbreak.</p>},
  author       = {Olsson, Per Ola and Lindström, Johan and Eklundh, Lars},
  issn         = {0034-4257},
  keyword      = {Insect defoliation monitoring,Kalman filter,MODIS,NDVI,Near real-time},
  language     = {eng},
  pages        = {42--53},
  publisher    = {Elsevier},
  series       = {Remote Sensing of Environment},
  title        = {Near real-time monitoring of insect induced defoliation in subalpine birch forests with MODIS derived NDVI},
  url          = {http://dx.doi.org/10.1016/j.rse.2016.03.040},
  volume       = {181},
  year         = {2016},
}