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Development of a method for monitoring of insect induced forest defoliation – limitation of MODIS data in Fennoscandian forest landscapes

Olsson, Per-Ola LU ; Kantola, Tuula; Lyytikäinen-Saarenmaa, Päivi; Jönsson, Anna Maria LU and Eklundh, Lars LU (2016) In Silva Fennica 50(2). p.1-22
Abstract
We investigated if coarse-resolution satellite data from the MODIS sensor can be used for

regional monitoring of insect disturbances in Fennoscandia. A damage detection method based on

z-scores of seasonal maximums of the 2-band Enhanced Vegetation Index (EVI2) was developed.

Time-series smoothing was applied and Receiver Operating Characteristics graphs were used for

optimisation. The method was developed in fragmented and heavily managed forests in eastern

Finland dominated by Scots pine (Pinus sylvestris L.) (pinaceae) and with defoliation of European

pine sawfly (Neodiprion sertifer Geoffr.) (Hymenoptera: Diprionidae) and common pine sawfly

(Diprion pini L.) (Hymenoptera:... (More)
We investigated if coarse-resolution satellite data from the MODIS sensor can be used for

regional monitoring of insect disturbances in Fennoscandia. A damage detection method based on

z-scores of seasonal maximums of the 2-band Enhanced Vegetation Index (EVI2) was developed.

Time-series smoothing was applied and Receiver Operating Characteristics graphs were used for

optimisation. The method was developed in fragmented and heavily managed forests in eastern

Finland dominated by Scots pine (Pinus sylvestris L.) (pinaceae) and with defoliation of European

pine sawfly (Neodiprion sertifer Geoffr.) (Hymenoptera: Diprionidae) and common pine sawfly

(Diprion pini L.) (Hymenoptera: Diprionidae). The method was also applied to subalpine mountain

birch (Betula pubescens ssp. Czerepanovii N.I. Orlova) forests in northern Sweden, infested by

autumnal moth (Epirrita autumnata Borkhausen) and winter moth (Operophtera brumata L.).

In Finland, detection accuracies were fairly low with 50% of the damaged stands detected, and

a misclassification of healthy stands of 22%. In areas with long outbreak histories the method

resulted in extensive misclassification. In northern Sweden accuracies were higher, with 75% of

the damage detected and a misclassification of healthy samples of 19%. Our results indicate that

MODIS data may fail to detect damage in fragmented forests, particularly when the damage history

is long. Therefore, regional studies based on these data may underestimate defoliation. However,

the method yielded accurate results in homogeneous forest ecosystems and when long-enough

periods without damage could be identified. Furthermore, the method is likely to be useful for

insect disturbance detection using future medium-resolution data, e.g. from Sentinel‑2. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Silva Fennica
volume
50
issue
2
pages
1 - 22
publisher
Helsinki : Suomen metsätieteellinen seura, 1926-
external identifiers
  • scopus:84957827933
ISSN
2242-4075
DOI
10.14214/sf.1495
language
English
LU publication?
yes
id
25d699b4-2e31-4b99-8b1b-74c5519dc573 (old id 8859057)
alternative location
http://dx.doi.org/10.14214/sf.1495
date added to LUP
2016-03-17 12:46:21
date last changed
2017-10-22 03:30:29
@article{25d699b4-2e31-4b99-8b1b-74c5519dc573,
  abstract     = {We investigated if coarse-resolution satellite data from the MODIS sensor can be used for<br/><br>
regional monitoring of insect disturbances in Fennoscandia. A damage detection method based on<br/><br>
z-scores of seasonal maximums of the 2-band Enhanced Vegetation Index (EVI2) was developed.<br/><br>
Time-series smoothing was applied and Receiver Operating Characteristics graphs were used for<br/><br>
optimisation. The method was developed in fragmented and heavily managed forests in eastern<br/><br>
Finland dominated by Scots pine (Pinus sylvestris L.) (pinaceae) and with defoliation of European<br/><br>
pine sawfly (Neodiprion sertifer Geoffr.) (Hymenoptera: Diprionidae) and common pine sawfly<br/><br>
(Diprion pini L.) (Hymenoptera: Diprionidae). The method was also applied to subalpine mountain<br/><br>
birch (Betula pubescens ssp. Czerepanovii N.I. Orlova) forests in northern Sweden, infested by<br/><br>
autumnal moth (Epirrita autumnata Borkhausen) and winter moth (Operophtera brumata L.).<br/><br>
In Finland, detection accuracies were fairly low with 50% of the damaged stands detected, and<br/><br>
a misclassification of healthy stands of 22%. In areas with long outbreak histories the method<br/><br>
resulted in extensive misclassification. In northern Sweden accuracies were higher, with 75% of<br/><br>
the damage detected and a misclassification of healthy samples of 19%. Our results indicate that<br/><br>
MODIS data may fail to detect damage in fragmented forests, particularly when the damage history<br/><br>
is long. Therefore, regional studies based on these data may underestimate defoliation. However,<br/><br>
the method yielded accurate results in homogeneous forest ecosystems and when long-enough<br/><br>
periods without damage could be identified. Furthermore, the method is likely to be useful for<br/><br>
insect disturbance detection using future medium-resolution data, e.g. from Sentinel‑2.},
  author       = {Olsson, Per-Ola and Kantola, Tuula and Lyytikäinen-Saarenmaa, Päivi and Jönsson, Anna Maria and Eklundh, Lars},
  issn         = {2242-4075},
  language     = {eng},
  number       = {2},
  pages        = {1--22},
  publisher    = {Helsinki : Suomen metsätieteellinen seura, 1926-},
  series       = {Silva Fennica},
  title        = {Development of a method for monitoring of insect induced forest defoliation – limitation of MODIS data in Fennoscandian forest landscapes},
  url          = {http://dx.doi.org/10.14214/sf.1495},
  volume       = {50},
  year         = {2016},
}