Deep-learning-based canopy height model generation from sub-meter resolution panchromatic satellite imagery

Deep-learning-based canopy height model generation from sub-meter resolution panchromatic satellite imagery

Canopy height models (CHMs) with sufficient resolution to distinguish individual trees are useful for a variety of applications. However, standard techniques to acquire such data, such as airborne lidar surveying, are often prohibitively expensive. Deep learning techniques for generating CHMs from h...

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Bibliographic Details
Main Authors: Charles J Abolt, Javier E Santos, Adam L Atchley, Lucas Wells, Daithi Martin, Russell A Parsons, Rodman R Linn
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:Machine Learning: Science and Technology
Subjects:
forestry
optical
lidar
fire
CNN
Online Access:https://doi.org/10.1088/2632-2153/ada47e
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