GreenView
Innovative forest protection, powered by AI.
Together with EXCIT3D GmbH we're building a preventive forest-protection system. Drones carry multispectral and RGB sensors, we reconstruct a 3D model of the forest, and AI identifies drought-stressed trees before bark beetles arrive. That shifts foresters from reactive felling to targeted prevention.
Multispectral signatures reveal drought stress long before it becomes visible to the eye — and before bark beetles reach the weakened tree.
Automated flights survey entire stands in a short time: full coverage instead of spot checks, and without labour-intensive ground inspection.
The flights are turned into a 3D model of the forest in which neural networks segment individual trees and assess their condition.
Four narrow-band channels — red, green, red edge and near infrared — plus RGB provide the data basis for vegetation indices such as NDVI and NDRE.
Foresters receive prioritised maps of the areas at risk and can intervene precisely instead of felling reactively across large areas.
True-colour rendering as a visual reference: this is how the stand looks to the human eye — the baseline for comparing the individual spectral channels.
What the channels are used for
The individual channels are combined into vegetation indices (VI) that allow conclusions about plant health.
Detection of vegetation.
Channels required: NIR + red
Early stress indicator in vegetation.
Channels required: Red edge + NIR
From channel to index map
The same area in three renderings: the true-colour orthophoto as a reference and the index maps computed from it. Both indices normalise the difference between two channels to a value between −1 and +1, revealing differences that are not yet visible in the RGB image.
True-colour capture as a reference: field, meadow and tree stand are easy to tell apart — but the image says little about the condition of the individual plants.
Funded by the EU and the State of NRW
The project is funded as part of the NEXT.IN.NRW innovation competition by the European Regional Development Fund (ERDF) and the state government of North Rhine-Westphalia.
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