Forests4Future – Training on determining forest biomass using drones
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AI-based forest monitoring
February 22, 2023
The Bavarian State Ministry for Economic Affairs, Regional Development and Energy (StMWi) is funding a new research project by RSS as part of the Bavarian Joint Research Program (BayVFP). In cooperation with the Peatland Science Center (PSC) of the University of Applied Sciences Weihenstephan – Triesdorf (HSWT), RSS is developing new methods for monitoring the renaturation of peatlands in Bavaria. The aim of the project is to be able to better quantify the rewetting success of drained peatlands and the associated emission savings.
Peatlands have great potential to reduce CO2 emissions and at the same time to preserve and enhance biodiversity. In Germany, Bavaria has a large proportion (9.5%, approx. 220,000 ha) of peatland and the aim of Bavarian politics is to rewet and restore a substantial part of these peatlands (55,000 ha). Precise monitoring of the measures and the associated CO2 savings is essential in order to be able to monitor success.
Field surveys
The aim of the project is to scale existing methods for assessing the condition of peatlands and for planning and monitoring the success of renaturation in example areas and to improve the accuracy of the data basis. So far, spot-like in situ measurements of the water level and the vegetation types have been carried out and the water levels have been scaled to the area using vegetation proxies. Based on this, a model-based Bavarian peatland water level map is currently being developed in the KliMoBay project. Using new remote sensing data (EnMAP, Sentinel-1/2, multispectral aerial images) and methods, it should be possible to collect important indicator data across the board and at high frequency and to monitor the state of degraded, renatured and natural moor areas in Bavaria on a regular basis and thus, among other things, to validate the water level map. In the project, the network coordinator Remote Sensing Solutions GmbH (RSS) is responsible for the development of the remote sensing methods.
