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Detecting drought effects on tree mortality in forests of Franconia (Germany)

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<p>Central European forests face challenges with climate changing much faster than they can adapt. Extremely hot and dry summers like in 2018 deprive forests of soil moisture, leaving them with low ground water levels. While individuals with deep and well-established root systems survive, young individuals and shallow-rooted species perish.</p><p>In southern Germany, die-off of single trees or small groups got noticeable recently. Such effects of harsher conditions rarely occur over large areas, but more in a spotted, irregular manner. This makes the phenomenon difficult to detect and to estimate its extent. The share of trees lately deteriorated may be larger than expected and represent a considerable portion of forests. Therefore, we see the great need for monitoring. Remote sensing data is suitable to examine inaccessible areas at a large scale. To quantify mortality of individual trees among a majority of vital ones, sensor platforms and respective data have to fulfill certain criteria regarding spatial, temporal and spectral resolution. Dead trees can be distinguished from others due to discoloration and defoliation. This change in appearance affects the spectral response, even in pixels larger than the tree’s extent.</p><p>This study aims at recommending a suitable spatial scale for space-borne multispectral imagery products to achieve this task. We evaluate commercial and free remote sensing data products and their ability to estimate fractional cover of dead vegetation. Satellite data employed in this study comes from Landsat 8 (30 m), Sentinel-2 (10 m), RapidEye (6.5 m) and PlanetScope (3 m). Classification performance is tested against high-resolution multispectral aerial imagery (17 cm) acquired with a Micasense RedEdge-M camera.</p><p>High-resolution Micasense images are capable of detecting single dead trees, even after downgrading the resolution from 17 cm to 3 m. For all data products tested, fraction of dead trees per pixel did not differ significantly among land cover types (dead vegetation, vital vegetation, pavement, open soil). This indicates that individual dead trees may not be detectable in vital forest stands. The finding even seems to be valid for a resolution of 3 m (PlanetScope), which is identical to the downgraded Micasense data. In the near future the detection of this phenomenon might profit from technical developments towards even higher spatial detail of space-borne sensors. Alternatively, high resolution images from aerial campaigns, manned or unmanned, could bridge this gap when flight time and spatial coverage are increased significantly and facilitating policies are in place.</p>
Title: Detecting drought effects on tree mortality in forests of Franconia (Germany)
Description:
<p>Central European forests face challenges with climate changing much faster than they can adapt.
Extremely hot and dry summers like in 2018 deprive forests of soil moisture, leaving them with low ground water levels.
While individuals with deep and well-established root systems survive, young individuals and shallow-rooted species perish.
</p><p>In southern Germany, die-off of single trees or small groups got noticeable recently.
Such effects of harsher conditions rarely occur over large areas, but more in a spotted, irregular manner.
This makes the phenomenon difficult to detect and to estimate its extent.
The share of trees lately deteriorated may be larger than expected and represent a considerable portion of forests.
Therefore, we see the great need for monitoring.
Remote sensing data is suitable to examine inaccessible areas at a large scale.
To quantify mortality of individual trees among a majority of vital ones, sensor platforms and respective data have to fulfill certain criteria regarding spatial, temporal and spectral resolution.
Dead trees can be distinguished from others due to discoloration and defoliation.
This change in appearance affects the spectral response, even in pixels larger than the tree’s extent.
</p><p>This study aims at recommending a suitable spatial scale for space-borne multispectral imagery products to achieve this task.
We evaluate commercial and free remote sensing data products and their ability to estimate fractional cover of dead vegetation.
Satellite data employed in this study comes from Landsat 8 (30 m), Sentinel-2 (10 m), RapidEye (6.
5 m) and PlanetScope (3 m).
Classification performance is tested against high-resolution multispectral aerial imagery (17 cm) acquired with a Micasense RedEdge-M camera.
</p><p>High-resolution Micasense images are capable of detecting single dead trees, even after downgrading the resolution from 17 cm to 3 m.
For all data products tested, fraction of dead trees per pixel did not differ significantly among land cover types (dead vegetation, vital vegetation, pavement, open soil).
This indicates that individual dead trees may not be detectable in vital forest stands.
The finding even seems to be valid for a resolution of 3 m (PlanetScope), which is identical to the downgraded Micasense data.
In the near future the detection of this phenomenon might profit from technical developments towards even higher spatial detail of space-borne sensors.
Alternatively, high resolution images from aerial campaigns, manned or unmanned, could bridge this gap when flight time and spatial coverage are increased significantly and facilitating policies are in place.
</p>.

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