Martin Schlerf

Ecology · 2005–2013

A researcher in the Science corpus: 6 papers; trusts 12 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

Whom Martin Schlerf trusts overall

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

  1. Moses Azong Cho
  2. Warren B. Cohen
  3. Peng Gong
  4. Andrew K. Skidmore
  5. Prasad S. Thenkabail
  6. Vladimir Naumovich Vapnik
  7. Gregory P. Asner
  8. Chih-Jen Lin
  9. R. V. Rossel
  10. Thomas K. Maiersperger

Who trusts Martin Schlerf overall

  1. Roshanak Darvishzadeh
  2. Jochem Verrelst
  3. Clement Atzberger
  4. Andrew K. Skidmore
  5. Ruiliang Pu
  6. Saleem Ullah
  7. Lucie Homolová
  8. Kian Pang Tan
  9. Johannes Schumacher
  10. Abel Ramoelo

Papers from Martin Schlerf's perspective

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

  1. Hyperspectral Vegetation Indices and Their Relationships with Agricultural Crop Characteristics
  2. Comparison of four radiative transfer models to simulate plant canopies reflectance: direct and inverse mode.
  3. LIBSVM: A library for support vector machines
  4. Estimation of green grass/herb biomass from airborne hyperspectral imagery using spectral indices and partial least squares regression (International Journal of Applied Earth Observation and Geoinformation)
  5. A new technique for extracting the red edge position from hyperspectral data: The linear extrapolation method
  6. Estimating foliage nitrogen concentration from HYMAP data using continuum, removal analysis
  7. Retrieval of leaf area index in different vegetation types using high resolution satellite data
  8. Hyperspectral imaging for nondestructive determination of some quality attributes for strawberry
  9. Comparing regression methods in estimation of biophysical properties of forest stands from two different inventories using laser scanner data
  10. Modified Jack-knife estimation of parameter uncertainty in bilinear modelling by partial least squares regression (PLSR)

Their papers