Remote sensing of the plant pigment system

Vegetation-light Interactions, Biodiversity Measurement from Space

The varying radiation regime has an impact on plant growth. We use physically based models of soil-vegetation-atmosphere transfer (and their inverse) to assess ecosystem level vegetation structure (or architecture) and biochemistry. Focus is on using 1D and 3D radiative transfer models specializing on retrieval of plant pigments (Chl a/b, Carotenoids, Anthocyanin), non-pigments (leaf water), and structure (LAI, leaf inclination angle, etc.). We use in-situ, airborne and spaceborne instruments in combination with inverse modeling of those radiative transfer models to retrieve those parameters. We also improve models of NPP by using advanced Light Use Efficiency (LUE) proxies, including steady-state Chlorophyll fluorescence in the O2absorption line. We are interested in large scale changes of those parameters, allowing to model spatiotemporal changes of growth limiting factors, biochemistry and structure in a changing environment.


Recent Publications

  • Remotely sensed between-individual functional trait variation in a temperate forest
    Guillen-Escriba, Carla; Schneider, Fabian D.; Schmid, Bernhard; Tedder, Andrew; Morsdorf, Felix; Furrer, Reinhard; Hueni, Andreas; Niklaus, Pascal A.; Schaepman, Michael E
    Ecology And Evolution 10.1002/ece3.7758  AUG 2021
  • Uncertainty Analysis for Topographic Correction of Hyperspectral Remote Sensing Images
    Ma, Zhaoning; Jia, Guorui; Schaepman, Michael E.; Zhao, Huijie
    Remote Sensing  DOI: 10.3390/rs12040705, Published: FEB 2020
  • Simulating functional diversity of European natural forests along climatic gradients
    Thonicke, Kirsten; Billing, Maik; von Bloh, Werner; Sakschewski, Boris; Niinemets, Ulo; et al.
    Journal Of Biogeography 10.1111/jbi.13809 FEB 2020
  • Monitoring global changes in biodiversity and climate essential as ecological crisis intensifies
    O'Connor, Brian; Bojinski, Stephan; Roeoesli, Claudia; Schaepman, Michael E.
    Ecological Informatics,  DOI: 10.1016/j.ecoinf.2019.101033, Published: JAN 2020
  • From local to regional: Functional diversity in differently managed alpine grasslands
    Rossi, Christian; Kneubuler, Mathias; Schutz, Martin; Schaepman, Michael E.; Haller, Rudolf M.; et al.
    Remote Sensing Of Environment,  DOI: 10.1016/j.rse.2019.111415, JAN 2020
  • Tree species classification in a temperate mixed forest using a combination of imaging spectroscopy and airborne laser scanning
    Torabzadeh, Hossein; Leiterer, Reik; Hueni, Andreas; Schaepman, Michael E.; Morsdorf, Felix
    Agricultural And Forest Meteorology,  DOI: 10.1016/j.agrformet.2019.107744, DEC 15 2019
  • Linking Remote Sensing and Geodiversity and Their Traits Relevant to Biodiversity-Part I: Soil Characteristics
    Lausch, Angela; Baade, Jussi; Bannehr, Lutz; Borg, Erik; Bumberger, Jan; et al.
    Remote Sensing,  DOI: 10.3390/rs11202356, Published: OCT 2019
  • Optimal Timing Assessment for Crop Separation Using Multispectral Unmanned Aerial Vehicle (UAV) Data and Textural Features
    Bohler, JE; Schaepman, ME; Kneubuhler, M
    REMOTE SENSING, 11 (15):10.3390/rs11151780 AUG 2019
  • Land use change and the migration geography of Greater White-fronted geese in European Russia
    Grishchenko, M; Prins, HHT; Ydenberg, RC; Schaepman, ME; de Boer, WF; de Knegt, HJ
    ECOSPHERE, 10 (8):10.1002/ecs2.2754 AUG 2019
  • Ecosystem service change caused by climatological and non-climatological drivers: a Swiss case study
    Braun, D; de Jong, R; Schaepman, ME; Furrer, R; Hein, L; Kienast, F; Damm, A
    ECOLOGICAL APPLICATIONS, 29 (4):10.1002/eap.1901 JUN 2019
  • A Back-Projection Tomographic Framework for VHR SAR Image Change Detection
    Dominguez, EM; Magnard, C; Meier, E; Small, D; Schaepman, ME; Henke, D
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 57 (7):4470-4484; 10.1109/TGRS.2019.2891308 JUL 2019
  • Mapping the Irradiance Field of a Single Tree: Quantifying Vegetation-Induced Adjacency Effects
    Kukenbrink, D; Hueni, A; Schneider, FD; Damm, A; Gastellu-Etchegorry, JP; Schaepman, ME; Morsdorf, F
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 57 (7):4994-5011; 10.1109/TGRS.2019.2895211 JUL 2019
  • Spatial variation of human influences on grassland biomass on the Qinghai-Tibetan plateau
    Li, CX; de Jong, R; Schmid, B; Wulf, H; Schaepman, ME
    SCIENCE OF THE TOTAL ENVIRONMENT, 665 678-689; 10.1016/j.scitotenv.2019.01.321 MAY 15 2019
  • Quantifying 3D structure and occlusion in dense tropical and temperate forests using close-range LiDAR
    Schneider, FD; Kukenbrink, D; Schaepman, ME; Schimel, DS; Morsdorf, F
    AGRICULTURAL AND FOREST METEOROLOGY, 268 249-257; 10.1016/j.agrformet.2019.01.033 APR 15 2019
  • Minimizing soil moisture variations in multi-temporal airborne imaging spectrometer data for digital soil mapping
    Diek, S; Chabrillat, S; Nocita, M; Schaepman, ME; de Jong, R
    GEODERMA, 337 607-621; 10.1016/j.geoderma.2018.09.052 MAR 1 2019
  • Automated detection of individual clove trees for yield quantification in northeastern Madagascar based on multi-spectral satellite data
    Roth, SIB; Leiterer, R; Volpi, M; Celio, E; Schaepman, ME; Joerg, PC
    REMOTE SENSING OF ENVIRONMENT, 221 144-156; 10.1016/j.rse.2018.11.009 FEB 2019 


Michael Schaepman UZH

Prof. Dr. Michael Schaepman
University of Zurich
Department of Geography Remote Sensing Laboratories
8008 Zurich

Tel: +41 (0)44 635 51 60

Research topics

  • Remote sensing of the plant pigment system
  • Estimating net primary productivity using models of light interaction
  • Radiative transfer modeling to map composition and chemistry of species at large scales
  • Quantitatively assess the phylogenetic organization of plants from satellites
  • Measurement of structural and biochemical traits and their response to global change
  • Assess spatiotemporal changes of functional diversity of spatially dominant species



  • Ecological genomics (linking genetic and pigment diversity)
  • Phenomics
  • Spectranomics
  • Combination of light interactions with gas exchange models