Innovative Drone-based Hyperspectral Detection of Heavy Metals (Ni, Zn, and Cu) in Plants cultivated for Phytomining
- 1Helmholtz Centre Potsdam, German Research Center for Geosciences (klos@gfz-potsdam.de)
- 2Brandenburg University of Technology Cottbus - Senftenberg, Chair of Geopedology and Landscape Development
Natural and anthropogenic activities can result in soil contamination and thus disturb their important functions for the abiotic and biotic environment, e.g. filtering, buffering or plant growth. Specific remediation measures are already taken for such environmental issues including phytoremediation using plants that are able to reduce heavy metal concentrations in the pedosphere and accumulate these heavy metals in their biomass. A fast monitoring system for a large-scale and area-wide mapping of metal contents in plants is still missing. However, such a monitoring system would be a very helpful tool to the recycling of heavy metals and supports the development of environmentally friendly processes for metal recovery. We present the concept of the innovative HyPhy project, which studies the possibility of monitoring heavy metal accumulation in hyperaccumulators with drone-based hyperspectral sensors. The phytoscreening considered here can be used to profitably mine raw materials such as nickel, zinc and copper using hyperaccumulating plants. Method will be validated using green house and field measurements based on hyperspectral sensors supported by drones. Two sensors will be used, the VNIR hyperspectral sensor from Cubert GmbH (450-950nm) and the SWIR hyperspectral sensor HySpex from the Norwegian company NEO (1000-2500nm). The two optical sensors are validated with the point spectrometer PSR+ from Spectral Evolution (350-2500nm). This presentation will show background, methods and first results of our project.
How to cite: Klos, F., Sut-Lohmann, M., Raab, T., and Hirsch, F.: Innovative Drone-based Hyperspectral Detection of Heavy Metals (Ni, Zn, and Cu) in Plants cultivated for Phytomining, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9370, https://doi.org/10.5194/egusphere-egu2020-9370, 2020.