Nathalie Gorretta

Ecology · 2006–2017

A researcher in the Science corpus: 3 papers; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Nathalie Gorretta trusts overall

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

  1. Anatoly A. Gitelson
  2. Cédric Bacour
  3. Jan G. P. W. Clevers

Who trusts Nathalie Gorretta overall

  1. Nicola Caporaso
  2. S. Mahesh
  3. M. Whitworth

Papers from Nathalie Gorretta's perspective

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

  1. Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture
  2. Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages
  3. Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves. (Journal of plant physiology)
  4. Remote estimation of crop and grass chlorophyll and nitrogen content using red-edge bands on Sentinel-2 and -3 (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. A review on reflective remote sensing and data assimilation techniques for enhanced agroecosystem modeling (International Journal of Applied Earth Observation and Geoinformation)
  7. Three‐band model for noninvasive estimation of chlorophyll, carotenoids, and anthocyanin contents in higher plant leaves
  8. Unified Optical-Thermal Four-Stream Radiative Transfer Theory for Homogeneous Vegetation Canopies (IEEE Transactions on Geoscience and Remote Sensing)
  9. Optical remote sensing and the retrieval of terrestrial vegetation bio-geophysical properties - A review
  10. Using Hyperspectral Remote Sensing Data for Retrieving Canopy Chlorophyll and Nitrogen Content (IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing)

Their papers