Sentinel-2 accurately maps green-attack stage of European spruce bark beetle (Ips typographus, L.) compared with Landsat-8

Haidi Abdullah (Corresponding Author), A.K. Skidmore, R. Darvishzadeh, Marco Heurich

Research output: Contribution to journalArticleAcademicpeer-review

3 Citations (Scopus)
45 Downloads (Pure)

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 languageEnglish
Pages (from-to)87-106
Number of pages20
JournalRemote sensing in ecology and conservation
Volume5
Issue number1
Early online date25 Aug 2018
DOIs
Publication statusPublished - Mar 2019

Fingerprint

Ips typographus
bark beetles
Landsat
bark
Picea
beetle
Chlorophyll
Water content
Aerial photography
vegetation index
Pixels
aerial photography
Water
chlorophyll
imagery
water content
Forestry
leaves
Principal component analysis
pixel

Keywords

  • ITC-GOLD

Cite this

@article{e0c01e2753804ed887d80030603f08a3,
title = "Sentinel-2 accurately maps green-attack stage of European spruce bark beetle (Ips typographus, L.) compared with Landsat-8",
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.",
keywords = "ITC-GOLD",
author = "Haidi Abdullah and A.K. Skidmore and R. Darvishzadeh and Marco Heurich",
note = "emerging sources",
year = "2019",
month = "3",
doi = "10.1002/rse2.93",
language = "English",
volume = "5",
pages = "87--106",
journal = "Remote sensing in ecology and conservation",
issn = "2056-3485",
publisher = "Wiley-Blackwell",
number = "1",

}

Sentinel-2 accurately maps green-attack stage of European spruce bark beetle (Ips typographus, L.) compared with Landsat-8. / Abdullah, Haidi (Corresponding Author); Skidmore, A.K.; Darvishzadeh, R.; Heurich, Marco.

In: Remote sensing in ecology and conservation, Vol. 5, No. 1, 03.2019, p. 87-106.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Sentinel-2 accurately maps green-attack stage of European spruce bark beetle (Ips typographus, L.) compared with Landsat-8

AU - Abdullah, Haidi

AU - Skidmore, A.K.

AU - Darvishzadeh, R.

AU - Heurich, Marco

N1 - emerging sources

PY - 2019/3

Y1 - 2019/3

N2 - 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.

AB - 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.

KW - ITC-GOLD

UR - https://ezproxy2.utwente.nl/login?url=https://webapps.itc.utwente.nl/library/2018/ref/skidmore_rem.pdf

U2 - 10.1002/rse2.93

DO - 10.1002/rse2.93

M3 - Article

VL - 5

SP - 87

EP - 106

JO - Remote sensing in ecology and conservation

JF - Remote sensing in ecology and conservation

SN - 2056-3485

IS - 1

ER -