Michael E. Schaepman

Ecology · 2006–2021

A researcher in the Science corpus: 18 papers; trusts 20 researchers and is trusted by 14 researchers here, as inferred from the citation graph.

Subfields

Whom Michael E. Schaepman trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. W. Verhoef
  2. Valerie C. E. Laurent
  3. Albert Tarantola
  4. David A. Landgrebe
  5. Michele Meroni
  6. Thomas Blaschke
  7. Anatoly A. Gitelson
  8. Antonio J. Plaza
  9. Jochem Verrelst
  10. Susan L. Ustin

Who trusts Michael E. Schaepman overall

  1. Valerie C. E. Laurent
  2. Jochem Verrelst
  3. W. Verhoef
  4. Jan G. P. W. Clevers
  5. Scott V. Ollinger
  6. Susan L. Ustin
  7. Luis Guanter
  8. Oliver Kiptoo Kirui

Papers from Michael E. Schaepman's perspective

Ordered by how strongly the researchers Michael E. Schaepman trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Leaf level detection of solar induced chlorophyll fluorescence by means of a subnanometer resolution spectroradiometer
  2. Characterizing canopy biochemistry from imaging spectroscopy and its application to ecosystem studies
  3. Remote sensing of solar-induced chlorophyll fluorescence: Review of methods and applications
  4. A review on reflective remote sensing and data assimilation techniques for enhanced agroecosystem modeling (International Journal of Applied Earth Observation and Geoinformation)
  5. Modeling the impact of spectral sensor configurations on the FLD retrieval accuracy of sun-induced chlorophyll fluorescence
  6. Third Radiation Transfer Model Intercomparison (RAMI) exercise: Documenting progress in canopy reflectance models
  7. Retrieval of foliar information about plant pigment systems from high resolution spectroscopy
  8. Object based image analysis for remote sensing
  9. Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages
  10. Inverse problem theory - and methods for model parameter estimation

Their papers