Abstract
Natural disturbances induced by insect outbreaks have increased in forestecosystems over the past decades. To minimize economic loss and prevent amass outbreak, early detection of bark beetle green attack–a period when treeshave yet to show visual signs of infestation stress–is therefore crucial to effec-tive and timely forest management. In this study, we evaluated the ability ofspectral vegetation indices extracted from Landsat-8 and Sentinel-2 imagery tomap bark beetle green attack using principal component analysis (PCA) andpartial least square discriminate analysis (PLS-DA). A recent infestation mapproduced through visual interpretation of high-resolution aerial photographsvalidated the final infestation output maps. Leaf spectral measurements along-side total chlorophyll and nitrogen concentration, leaf water content and leafdry matter content were measured to assess the impact of bark beetle greenattack on foliar properties. We observed that the majority of spectral vegetationindices (SVIs) calculated from Sentinel-2, particularly red-edge dependentindices (NDRE 2 and 3) and water-related indices (SR-SWIR, NDWI, DSWIand LWCI), were able to discriminate healthy from infested plots. In contrast,only the water-related indices (NDWI, DSWI and RDI) from Landsat-8 wereable to discriminate between healthy and infested plots efficiently. The totalnumber of pixels identified as harboring a green attack that matched withground truth data (aerial photography) was higher for Sentinel-2 (67%) thanfor Landsat-8 (36%) SVIs, indicating the elevated sensitivity of Sentinel-2 ima-gery to changes induced by bark beetle green attack. We also determined thatfoliar chlorophyll and leaf water content were significantly higher (P<0.05) inhealthy trees than in green-attacked trees. Our study highlights the potential ofSentinel-2 data for the early detection of bark beetle infestations and the pro-duction of reliable infestation maps at the green-attack stage.This study aims toevaluate the ability of different spectral vegetation indices from Sentinel-2 andLandsat-8 imagery to map and detect bark beetle infestation at the green-attackstage. We observed that the majority of Spectral Vegetation Indices (SVIs) cal-culated from Sentinel-2 were able to discriminate healthy from infested plots.In contrast, only the water-related indices (NDWI, DSWI, and RDI) fromLandsat-8 were able to discriminate between healthy and infested plots effi-ciently. The total number of pixels identified as harboring a green attack thatmatched with ground truth data (aerial photography) was higher for Sentinel-2(67%) than for Landsat-8 (36%) SVIs, indicating the elevated sensitivity of Sen-tinel-2 imagery to changes induced by bark beetle green attack. We also
determined that foliar chlorophyll and leaf water content were significantlyhigher (P<0.05) in healthy trees than in green-attacked trees. Our study high-lights the potential of Sentinel-2 data for the early detection of bark beetleinfestations and the production of reliable infestation maps at the green-attackstage.
Original language | English |
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Pages (from-to) | 87-106 |
Number of pages | 20 |
Journal | Remote sensing in ecology and conservation |
Volume | 5 |
Issue number | 1 |
Early online date | 25 Aug 2018 |
DOIs | |
Publication status | Published - Mar 2019 |
Keywords
- ITC-GOLD
- ITC-ISI-JOURNAL-ARTICLE