DESIS hyperspectral satellite data for mapping bark beetle infestation
Quantitative remote sensing of vegetation parameters (Q5)
- A suitable candidate would be interested in remote sensing and quantification of biophysical variables
- Fieldwork is not necessary; however, a possible field visit can be discussed with the supervisors if the student is interested.
The goal of this study is to detect and map bark beetle infestation in a temperate forest in Germany using DESIS hyperspectral satellite data. The student will benefit from the existing satellite images and field samples collected during the earlier campaigns in Bavarian Forest National Park, Germany. The hyperspectral images will be classified for species discrimination and to determine the areas under bark beetle green and red attack using spectral analysis. The student will benefit from the utilization of different spectral methods such as spectral indices, endmembers analysis and spectral unmixing. Spectral reflectance of healthy sample plots and those under bark beetle attack will be extracted from the images and further investigated to understand the effect of infestation on spectral signatures. The collected parameters which are counted as key indicators of plant physiological status and health, will be considered in relation to spectral reflectance. Based on the field measurements, the obtained results would then be validated and used to map the spatial patterns of infested areas.
Traditionally, monitoring of forests is undertaken by highly skilled staff, who sample and assess vegetation structure, condition and species through the forest. Statistics are then derived from these point samples. Remote sensing, especially hyperspectral imagery, can capture fast-moving infestations (such as bark beetle) and be utilized forunderstanding changes in vegetation structure and function, hence allowing rapid remedial actions. The new generation of hyperspectral satellites (e.g. PRISMA and DESIS) has opened a new ear for monitoring forest infestations. Of special relevance in the Bavarian National Park is the regeneration process after disastrous events associated with the ongoing bark beetle calamities and storm damage. The bark beetle outbreaks have been proven to substantially alter the structure and health of coniferous and mixed forest stands the Bavarian Forest. Therefore, this study aims to map bark-beetle attack and its effect on vegetation parameters. The study is the first attempt on using hyperspectral satellite images for mapping bark beetle infestation.
- Canopy chlorophyll content retrieved from time series remote sensing data as a proxy for detecting bark beetle infestation
- Sentinel-2 accurately maps green-attack stage of European spruce bark beetle (Ips typographus, L.) compared with Landsat-8
- Timing of red-edge and shortwave infrared reflectance critical for early stress detection induced by bark beetle (Ips typographus, L.) attack
- https://en.wikipedia.org/wiki/Bavarian_Forest_National_Park
No need for adaptation. The MSc topic addresses forest health and environmental degradation issues using data from the new generation of hyperspectral satellites.