The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume XLVI-1/W1-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-1/W1-2021, 49–55, 2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-1/W1-2021, 49–55, 2022
11 Feb 2022
11 Feb 2022


J. Pacheco-Labrador1, U. Weber1, X. Ma2, M. D. Mahecha3, N. Carvalhais1, C. Wirth4, A. Huth5,6,7, F. J. Bohn5, G. Kraemer3, U. Heiden8, FunDivEUROPE members9, and M. Migliavacca10,1 J. Pacheco-Labrador et al.
  • 1Max Planck Institute for Biogeochemistry, Jena, Germany
  • 2College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, Gansu, China
  • 3Remote Sensing Center for Earth System Research Research, University of Leipzig, Leipzig, Germany
  • 4Systematic Botany and Functional Biodiversity, University of Leipzig, Leipzig, Germany
  • 5Department of Ecological Modelling, Helmholtz Centre for Environmental Research–UFZ, Leipzig, Germany
  • 6Institute of Environmental Systems Research, University of Osnabrück, Osnabrück, Germany
  • 7German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
  • 8Earth Observation Center (EOC), German Aerospace Center (DLR), Weßling, Germany
  • 9Albert-Ludwigs-Universitaet Freiburg (ALU-FR), Freiburg, Germany
  • 10European Commission, Joint Research Centre (JRC), Ispra, Italy

Keywords: Functional diversity, taxonomical diversity, spectral diversity, DESIS, FunDivEUROPE

Abstract. Tackling the accelerated human-induced biodiversity loss requires tools able to map biodiversity and its changes globally. Remote sensing (RS) offers unique capabilities of characterizing Earth surfaces; therefore, it could map plant biodiversity continuously and globally. This approach is supported by the Spectral Variation Hypothesis (SVH), which states that spectra and species (taxonomic and trait) diversities are linked through environmental heterogeneity. In this work, we evaluate the capability of the DESIS hyperspectral imager to capture plant diversity patterns as measured in dedicated plots of the network FunDivEUROPE. We computed functional and taxonomical diversity metrics from field taxonomic, structural, and foliar measurements in vegetation plots sampled in Spain and Romania. In addition, we also computed functional diversity metrics both from the DESIS reflectance factors and from vegetation parameters estimated via inversion of a radiative transfer model. Results showed that only metrics computed from spectral reflectance were able to capture taxonomic variability in the area. However, the lack of sensitivity was related to the insufficient plot size and the lack of spatial match between remote sensing and field data, but also the differences between the information contained in the field traits and remote sensing data, and the potential uncertainties in the remote estimates of vegetation parameters. Thus, while DESIS showed some sensitivity to plant diversity, further efforts are needed to deploy suitable biodiversity evaluation and validation plots and networks that support the development of biodiversity remote sensing products.