Early detection of bark beetle infestation using hyper-spectral imagery and tree-level transpiration measurements
Status: Active
Span: 2022-2023
Location: Skövde, Sweden
Contact: Langning Huo (Langning.Huo@slu.se)
Summary,
The objective of this project, is to develop early detection mechanisms for bark beetle attacks in Norway spruce, using hyper spectral images. We are monitoring tree-level transpiration using heat pulse sensors, record physical tree health (attack stage, number of attacks, tree response, etc.) and record hyper-spectral images using a drone. We are additionally monitoring trees under various site and environmental characteristics, including soil slope, site exposition, tree density, etc.
Initial results
The data from the figures above, corresponds to two sites where we had severe bark beetle infestation. We show the daily sum of the sap flux density, measured at three points inside the sapwood. In both figures, it is quite evident that not all trees respond the same way to bark beetle infestations. Some trees are able to recover, and others -unfortunately- die. Of the ones that die, some die faster than others… very interesting.
Video: Forest scanned using an hyper-spectral drone
