Predicting Carbon Accumulation in Temperate Forests of Ontario, Canada Using a LiDAR-Initialized Growth-and-Yield Model

Predicting Carbon Accumulation in Temperate Forests of Ontario, Canada Using a LiDAR-Initialized Growth-and-Yield Model

Climate warming has led to an urgent need for improved estimates of carbon accumulation in uneven-aged, mixed temperate forests, where high uncertainty remains. We investigated the feasibility of using LiDAR-derived forest attributes to initialize a growth and yield (G&Y) model in complex st...

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Bibliographic Details
Main Authors: Paulina T. Marczak, Karin Y. Van Ewijk, Paul M. Treitz, Neal A. Scott, Donald C.E. Robinson
Format: Article
Language:English
Published: MDPI AG 2020-01-01
Series:Remote Sensing
Subjects:
growth-and-yield
lidar
carbon stock
carbon accumulation
fvs<sup>ontario</sup>
Online Access:https://www.mdpi.com/2072-4292/12/1/201

Internet

https://www.mdpi.com/2072-4292/12/1/201

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