Abstract
Cambiophagous insects, fires and windthrow cause significant forest disturbances, generating ecological changes and economical losses. The bark beetle (Ips typographus L.), inhabiting coniferous forests and eliminating weakened trees, plays a key role in posing a threat to tree stands, which are dominated by Norway spruce (Picea abies) and covers a large part of mountain areas, as well as the lowlands of Northern, Central and Eastern Europe. Due to the dynamics of the phenomena taking place, the EU recommends constant monitoring of forests in terms of large-area disturbances and factors affecting tree stands’ susceptibility to destruction. The right tools for this are multispectral satellite images, which regularly and free of charge provide up-to-date information on changes in the environment. The aim of this study was to develop a method of identifying disturbances of spruce stands, including the identification of bark beetle outbreaks. Sentinel 2 images from 2015–2018 were used for this purpose; the reference data were high-resolution aerial images, satellite WorldView 2, as well as field verification data. Support Vector Machines (SVM) distinguished six classes: deciduous forests, coniferous forests, grasslands, rocks, snags (dieback of standing trees) and cuts/windthrow. Remote sensing vegetation indices, Multivariate Alteration Detection (MAD), Multivariate Alteration Detection/Maximum Autocorrelation Factor (MAD/MAF), iteratively re-weighted Multivariate Alteration Detection (iMAD) and trained SVM signatures from another year, stacked band rasters allowed us to identify: (1) no changes; (2) dieback of standing trees; (3) logging or falling down of trees. The overall accuracy of the SVM classification oscillated between 97–99%; it was observed that in 2015–2018, as a result of the windthrow and bark beetle outbreaks and the consequences of those natural disturbances (e.g., sanitary cuts), approximately 62.5 km2 of coniferous stands (29%) died in the studied area of the Tatra Mountains.
Highlights
The current paper focuses on methodical and application objectives; in the first case, it is an assessment of the multitemporal Sentinel-2 images (2015–2018) for the identification of coniferous and deciduous forests, grasslands, rocks, snags and cuts or windthrows
The coniferous forests layer served as a reference mask for the analyzes from the following years (2016–2018) and the assessment of the pace and extent of bark beetle outbreaks in the
The achieved results allow us to assess the usefulness of Sentinel-2 satellite images and Support Vector Machines (SVM)-supervised classification for spruce bark beetle outbreak with high accuracies; in our case the worst results oscillated around 94%
Summary
Due to the rapid growth of biomass and low requirements of a habitat, Norway spruce (Picea abies) has played a leading role in forestry in the European mountain areas since the 18th century; for this reason, it was often planted in places inconsistent with its habitat, i.e., where deciduous and mixed forests previously grew [1,2]. The flat and horizontally developed root system of Picea abies prefers a cool and humid climate, not tolerating soil dryness and overheating [1]. With the aging of the stand, Picea abies becomes susceptible to attacks by insects (mainly spruce bark beetle Ips typhographus) and fungi [3,4]. Progressive climate changes, manifested by higher air temperatures and reduced rainfall, allows Ips typographus to start reproducing earlier, reaching more
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