EGU24-18582, updated on 11 Mar 2024
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Spectral signatures of submerged vegetation for remote sensing mapping and benthic coastal marine ecosystem quality assessment

Fabrizio Varini1, Alice Madonia2, Sergio Scanu2, Viviana Piermattei2, and Marco Marcelli1
Fabrizio Varini et al.
  • 1Laboratory of Experimental Oceanology Marine Ecology, Department of Ecological and Biological Sciences (DEB), University of Tuscia, 00053 Civitavecchia, Italy.
  • 2Global Coastal Ocean (GOCO) Division, Euro-Mediterranean Centre on Climate Change (C.M.C.C.), 73100 Lecce, Italy.

In the context of international guidelines for the protection and conservation of biodiversity in natural environments, the assessment of the effects of human pressure on marine ecosystems assumes a key role. The scientific community has recognised Macroalgae and marine phanerogams as useful bioindicators, thanks to their considerable biomass, permanence, spectral retrieval and ease of identification. Remote sensing technology provides spatially synoptic and near real-time measurements that can be effectively used to detect pollution phenomena. However, remote sensing techniques, especially if applied in coastal areas, need correction and validation through in situ data collection.

In the framework of the STOPP project “Strumenti e Tecniche di Osservazione della Terra in Prossimità e Persistenza” funded by Agenzia Spaziale Italiana (ASI), one of the main goals is the use of innovative aerial platforms, equipped with multispectral sensors, to monitor the impacts of anthropogenic pollution on benthic coastal marine ecosystems.

In this work, we present the advances of the experimental activities aimed at analyzing the changes of the spectral signatures in response to different pollutant exposures in laboratory-controlled conditions, identifying the optimized protocol to detect the "target wavelengths" on seagrasses and macroalgae species. These results are useful for evaluating the feasibility of an innovative methodology for monitoring and mapping marine submerged vegetation through remote sensing.

How to cite: Varini, F., Madonia, A., Scanu, S., Piermattei, V., and Marcelli, M.: Spectral signatures of submerged vegetation for remote sensing mapping and benthic coastal marine ecosystem quality assessment, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18582,, 2024.