Abstract
The European spruce bark beetle (Ips typographus [L.]) is one of the most damaging pest insects of European spruce forests. A crucial measure in pest control is the removal of infested trees before the beetles leave the bark, which generally happens before the end of June. However, stressed tree crowns do not show any significant color changes in the visible spectrum at this early-stage of infestation, making early detection difficult. In order to detect the related forest stress at an early stage, we investigated the differences in radar and spectral signals of healthy and stressed trees. How the characteristics of stressed trees changed over time was analyzed for the whole vegetation season, which covered the period before attacks (April), early-stage infestation (‘green-attacks’, May to July), and middle to late-stage infestation (August to October). The results show that spectral differences already existed at the beginning of the vegetation season, before the attacks. The spectral separability between the healthy and infested samples did not change significantly during the ‘green-attack’ stage. The results indicate that the trees were stressed before the attacks and had spectral signatures that differed from healthy ones. These stress-induced spectral changes could be more efficient indicators of early infestations than the ‘green-attack’ symptoms.In this study we used Sentinel-1 and 2 images of a test site in southern Sweden from April to October in 2018 and 2019. The red and SWIR bands from Sentinel-2 showed the highest separability of healthy and stressed samples. The backscatter from Sentinel-1 and additional bands from Sentinel-2 contributed only slightly in the Random Forest classification models. We therefore propose the Normalized Distance Red & SWIR (NDRS) index as a new index based on our observations and the linear relationship between the red and SWIR bands. This index identified stressed forest with accuracies from 0.80 to 0.88 before the attacks, from 0.80 to 0.82 in the early-stage infestation, and from 0.81 to 0.91 in middle- and late-stage infestations. These accuracies are higher than those attained by established vegetation indices aimed at ‘green-attack’ detection, such as the Normalized Difference Water Index, Ratio Drought Index, and Disease Stress Water Index. By using the proposed method, we highlight the potential of using NDRS with Sentinel-2 images to estimate forest vulnerability to European spruce bark beetle attacks early in the vegetation season.
Highlights
During the last 50 years, the European spruce bark beetle (Ips typographus [L.]) has killed more than 150 million m3 forest in Europe (Schroeder and Cocos, 2018), where it is the most economically destructive insect pest of coniferous forests in Europe (Biedermann et al, 2019)
The separability of the individual bands could roughly be divided into three groups when considering the overall performance of all seasons: (1) Bands 11 and 12 from the short wave infra red (SWIR) bands obtained higher CAs for healthy and stressed pixels than the visible, red-edge and near infrared (NIR) bands
We investigated differences in radar and spectral signals between healthy trees and those attacked by spruce bark beetles
Summary
During the last 50 years, the European spruce bark beetle (Ips typographus [L.]) has killed more than 150 million m3 forest in Europe (Schroeder and Cocos, 2018), where it is the most economically destructive insect pest of coniferous forests in Europe (Biedermann et al, 2019). With the aggravation of global warming, several studies (Jakoby et al, 2019; Potterf et al, 2019) have predicted additional bark beetle generations, earlier spring swarming, more aggravated swarming, and more drought and storm events. These trends have been verified by the outburst of bark beetles in Sweden, which is located further north than the central European countries where bark beetle attacks first occurred. With the extremely warm summer of 2018, an additional generation of bark beetles occurred in August, increasing the amount of attacked Swedish forest to 7 million m3 in 2019 Such destruction of forest causes economic losses and forms a serious threat to the forest ecosystem (Huang et al, 2019)
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