Guangman Song
Orcid: 0000-0002-2896-048X
According to our database1,
Guangman Song
authored at least 10 papers
between 2021 and 2024.
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Bibliography
2024
Non-Destructive Estimation of Deciduous Forest Metrics: Comparisons between UAV-LiDAR, UAV-DAP, and Terrestrial LiDAR Leaf-Off Point Clouds Using Two QSMs.
Remote. Sens., February, 2024
2023
Reshaping Leaf-Level Reflectance Data for Plant Species Discrimination: Exploring Image Shape's Impact on Deep Learning Results.
Remote. Sens., December, 2023
Validating and Developing Hyperspectral Indices for Tracing Leaf Chlorophyll Fluorescence Parameters under Varying Light Conditions.
Remote. Sens., October, 2023
Species classification from hyperspectral leaf information using machine learning approaches.
Ecol. Informatics, September, 2023
Estimation of leaf photosynthetic capacity parameters using spectral indices developed from fractional-order derivatives.
Comput. Electron. Agric., September, 2023
Fractional-Order Derivative Spectral Transformations Improved Partial Least Squares Regression Estimation of Photosynthetic Capacity From Hyperspectral Reflectance.
IEEE Trans. Geosci. Remote. Sens., 2023
2022
Reshaping Hyperspectral Data into a Two-Dimensional Image for a CNN Model to Classify Plant Species from Reflectance.
Remote. Sens., 2022
Developing Hyperspectral Indices for Assessing Seasonal Variations in the Ratio of Chlorophyll to Carotenoid in Deciduous Forests.
Remote. Sens., 2022
Genetic Algorithm Captured the Informative Bands for Partial Least Squares Regression Better on Retrieving Leaf Nitrogen from Hyperspectral Reflectance.
Remote. Sens., 2022
2021
Including Leaf Traits Improves a Deep Neural Network Model for Predicting Photosynthetic Capacity from Reflectance.
Remote. Sens., 2021