Pablo J. Zarco-Tejada

Ecology · 2001–2020

A researcher in the Science corpus: 12 papers; trusts 13 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

Whom Pablo J. Zarco-Tejada trusts overall

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

  1. Toshihiro Sakamoto
  2. Thomas Blaschke
  3. Elías Fereres
  4. Jose A. Jiménez-Berni
  5. Xiuliang Jin
  6. Stephane Jacquemoud
  7. D. Sims
  8. Jose Luis Araus
  9. Zhenhai Li
  10. Mike R. James

Who trusts Pablo J. Zarco-Tejada overall

  1. Helge Aasen
  2. George Alan Blackburn
  3. Ramón Alberto Díaz-Varela
  4. Arko Lucieer
  5. Eija Honkavaara
  6. Jochem Verrelst
  7. Jinru Xue
  8. Ruizhi Chen
  9. A. Matese
  10. Luke Wallace

Papers from Pablo J. Zarco-Tejada's perspective

Ordered by how strongly the researchers Pablo J. Zarco-Tejada trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages
  2. Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture
  3. Thermal and Narrowband Multispectral Remote Sensing for Vegetation Monitoring From an Unmanned Aerial Vehicle (IEEE Transactions on Geoscience and Remote Sensing)
  4. ImageNet classification with deep convolutional neural networks
  5. A new technique for extracting the red edge position from hyperspectral data: The linear extrapolation method
  6. Recurrent Neural Network Regularization
  7. Spectral water indices for assessing yield in elite bread wheat genotypes under well-irrigated, water-stressed, and high-temperature conditions
  8. High throughput phenotyping of canopy water mass and canopy temperature in well-watered and drought stressed tropical maize hybrids in the vegetative stage
  9. Comparison of four radiative transfer models to simulate plant canopies reflectance: direct and inverse mode.
  10. Object based image analysis for remote sensing

Their papers