Shezhou Luo

Orcid: 0000-0002-2535-5188

According to our database1, Shezhou Luo authored at least 16 papers between 2016 and 2021.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Links

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Bibliography

2021
Study on Local to Global Radiometric Balance for Remotely Sensed Imagery.
Remote. Sens., 2021

Maize and soybean heights estimation from unmanned aerial vehicle (UAV) LiDAR data.
Comput. Electron. Agric., 2021

2020
Simulation-Based Evaluation of the Estimation Methods of Far-Red Solar-Induced Chlorophyll Fluorescence Escape Probability in Discontinuous Forest Canopies.
Remote. Sens., 2020

Angular effect in proximal sensing of leaf-level chlorophyll content using low-cost DIY visible/near-infrared camera.
Comput. Electron. Agric., 2020

2019
Assessing the Impacts of Various Factors on Treetop Detection Using LiDAR-Derived Canopy Height Models.
IEEE Trans. Geosci. Remote. Sens., 2019

Estimating the Aboveground Biomass for Planted Forests Based on Stand Age and Environmental Variables.
Remote. Sens., 2019

Estimating forest aboveground biomass using small-footprint full-waveform airborne LiDAR data.
Int. J. Appl. Earth Obs. Geoinformation, 2019

2018
Exploring the Influence of Various Factors on Slope Estimation Using Large-Footprint LiDAR Data.
IEEE Trans. Geosci. Remote. Sens., 2018

A Continuous Wavelet Transform Based Method for Ground Elevation Estimation Over Mountainous Vegetated Areas Using Satellite Laser Altimetry.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2018

Comparative Performances of Airborne LiDAR Height and Intensity Data for Leaf Area Index Estimation.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2018

Comparison of Seven Inversion Models for Estimating Plant and Woody Area Indices of Leaf-on and Leaf-off Forest Canopy Using Explicit 3D Forest Scenes.
Remote. Sens., 2018

2017
Estimating the Biomass of Maize with Hyperspectral and LiDAR Data.
Remote. Sens., 2017

Retrieving aboveground biomass of wetland Phragmites australis (common reed) using a combination of airborne discrete-return LiDAR and hyperspectral data.
Int. J. Appl. Earth Obs. Geoinformation, 2017

2016
Estimating Leaf Area Index of Maize Using Airborne Discrete-Return LiDAR Data.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2016

Fusion of Airborne Discrete-Return LiDAR and Hyperspectral Data for Land Cover Classification.
Remote. Sens., 2016

Forest above Ground Biomass Inversion by Fusing GLAS with Optical Remote Sensing Data.
ISPRS Int. J. Geo Inf., 2016


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