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

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.