Retrieval of Forest Vertical Structure from PolInSAR Data by Machine Learning Using LIDAR-Derived Features

Retrieval of Forest Vertical Structure from PolInSAR Data by Machine Learning Using LIDAR-Derived Features

This paper presents a machine learning based method to predict the forest structure parameters from L-band polarimetric and interferometric synthetic aperture radar (PolInSAR) data acquired by the airborne UAVSAR system over the <i>R&#233;serve Faunique des Laurentides</i> in Qu&...

Full description

Bibliographic Details
Main Authors: Guillaume Brigot, Marc Simard, Elise Colin-Koeniguer, Alexandre Boulch
Format: Article
Language:English
Published: MDPI AG 2019-02-01
Series:Remote Sensing
Subjects:
synthetic aperture radar (SAR)
LIDAR
interferometry
polarimetry
machine learning
Above-Ground Biomass
canopy height
Online Access:https://www.mdpi.com/2072-4292/11/4/381

Similar Items

Similar Items