Combining Environmental, Multispectral, and LiDAR Data Improves Forest Type Classification: A Case Study on Mapping Cool Temperate Rainforests and Mixed Forests

Combining Environmental, Multispectral, and LiDAR Data Improves Forest Type Classification: A Case Study on Mapping Cool Temperate Rainforests and Mixed Forests

Predictive vegetation mapping is an essential tool for managing and conserving high conservation-value forests. Cool temperate rainforests (Rainforest) and cool temperate mixed forests (Mixed Forest, i.e., rainforest spp. overtopped by large remnant <i>Eucalyptus</i> trees) are threatene...

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Bibliographic Details
Main Authors: Raphael Trouvé, Ruizhu Jiang, Melissa Fedrigo, Matt D. White, Sabine Kasel, Patrick J. Baker, Craig R. Nitschke
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Remote Sensing
Subjects:
Bayesian regularized regression
multi-source data fusion
remote sensing
sentinel
supervised learning
vegetation mapping
Online Access:https://www.mdpi.com/2072-4292/15/1/60

Internet

https://www.mdpi.com/2072-4292/15/1/60

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