Estimation of the Canopy Height Model From Multispectral Satellite Imagery With Convolutional Neural Networks

Estimation of the Canopy Height Model From Multispectral Satellite Imagery With Convolutional Neural Networks

The canopy height model (CHM) is a representation of the height of the top of vegetation from the surrounding ground level. It is crucial for the extraction of various forest characteristics, for instance, timber stock estimations and forest growth measurements. There are different ways of obtaining...

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Bibliographic Details
Main Authors: Svetlana Illarionova, Dmitrii Shadrin, Vladimir Ignatiev, Sergey Shayakhmetov, Alexey Trekin, Ivan Oseledets
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Artificial intelligence
artificial neural networks
computer vision
data analysis
digital elevation models
remote sensing
Online Access:https://ieeexplore.ieee.org/document/9739688/

Internet

https://ieeexplore.ieee.org/document/9739688/

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