Abstract Climate change increasingly threatens Central European forests through heat, drought, and pest outbreaks. Thuringia is particularly affected due to its extensive spruce and pine monocultures. Newly reforested areas, however, provide opportunities for continuous monitoring of young trees throughout their growth. This work explores automated, non-destructive monitoring using remote sensing on autonomous ground platforms to detect early forest stress and support long-term observation. Preliminary results on vegetation indices have enabled two stationary forest measurement systems: a bi-spectral camera and a multispectral setup with color and 3D-imaging. We present current results, discuss challenges, and outline future extensions toward mobile robotic data acquisition, including detecting resin as an indicator of bark damage or pest intrusion.
Richter et al. (Wed,) studied this question.
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