Insect outbreaks affect forests, causing the deaths of trees and high economic loss. In this study, we explored the detection of European spruce bark beetle (Ips typographus, L.) outbreaks at the individual tree crown level using multispectral satellite images. Moreover, we explored the possibility of tracking the progression of the outbreak over time using multitemporal data. Sentinel-2 data acquired during the summer of 2020 over a bark beetle–infested area in the Italian Alps were used for the mapping and tracking over time, while airborne lidar data were used to automatically detect the individual tree crowns and to classify tree species. Mapping and tracking of the outbreak were carried out using a support vector machine classifier with input vegetation indices extracted from the multispectral data. The results showed that it was possible to detect two stages of the outbreak (i.e., early, and late) with an overall accuracy of 83.4%. Moreover, we showed how it is technically possible to track the evolution of the outbreak in an almost bi-weekly period at the level of the individual tree crowns. The outcomes of this paper are useful from both a management and ecological perspective: it allows forest managers to map a bark beetle outbreak at different stages with a high spatial accuracy, and the maps describing the evolution of the outbreak could be used in further studies related to the behavior of bark beetles

Dalponte, M.; Solano-Correa, Y.T.; Frizzera, L.; Gianelle, D. (2022). Mapping a European spruce bark beetle outbreak using sentinel-2 remote sensing data. REMOTE SENSING, 14 (13): 3135. doi: 10.3390/rs14133135 handle: http://hdl.handle.net/10449/75896

Mapping a European spruce bark beetle outbreak using sentinel-2 remote sensing data

Dalponte, Michele
Primo
;
Frizzera, Lorenzo;Gianelle, Damiano
Ultimo
2022-01-01

Abstract

Insect outbreaks affect forests, causing the deaths of trees and high economic loss. In this study, we explored the detection of European spruce bark beetle (Ips typographus, L.) outbreaks at the individual tree crown level using multispectral satellite images. Moreover, we explored the possibility of tracking the progression of the outbreak over time using multitemporal data. Sentinel-2 data acquired during the summer of 2020 over a bark beetle–infested area in the Italian Alps were used for the mapping and tracking over time, while airborne lidar data were used to automatically detect the individual tree crowns and to classify tree species. Mapping and tracking of the outbreak were carried out using a support vector machine classifier with input vegetation indices extracted from the multispectral data. The results showed that it was possible to detect two stages of the outbreak (i.e., early, and late) with an overall accuracy of 83.4%. Moreover, we showed how it is technically possible to track the evolution of the outbreak in an almost bi-weekly period at the level of the individual tree crowns. The outcomes of this paper are useful from both a management and ecological perspective: it allows forest managers to map a bark beetle outbreak at different stages with a high spatial accuracy, and the maps describing the evolution of the outbreak could be used in further studies related to the behavior of bark beetles
Bark beetle
Sentinel-2
Multispectral
Individual tree crown
Settore BIO/07 - ECOLOGIA
2022
Dalponte, M.; Solano-Correa, Y.T.; Frizzera, L.; Gianelle, D. (2022). Mapping a European spruce bark beetle outbreak using sentinel-2 remote sensing data. REMOTE SENSING, 14 (13): 3135. doi: 10.3390/rs14133135 handle: http://hdl.handle.net/10449/75896
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