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A comparison of four individual tree height prediction methods for forest inventory
Michael J Falkowski
, A. M.S. Smith
, A. T. Hudak
, P. E. Gessler
Forest Resources
Research output
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Contribution to conference
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peer-review
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Dive into the research topics of 'A comparison of four individual tree height prediction methods for forest inventory'. Together they form a unique fingerprint.
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Keyphrases
Forest Inventory
100%
Prediction Method
100%
Individual Tree Level
100%
Tree Height Estimation
100%
Unsampled
100%
LiDAR
75%
Tree Height
75%
Mixed-effects Model
50%
Statistical Model
25%
Forest Stand
25%
Remote Sensing Technology
25%
Land Managers
25%
Idaho
25%
Model Estimates
25%
Open Canopy
25%
Forest Environment
25%
Accurate Information
25%
Open Forest
25%
Separating Method
25%
Computer Science
Accurate Information
100%
Mixed Effect Model
100%
United States of America
100%
Earth and Planetary Sciences
Forest Inventory
100%
Optical Radar
100%
United States of America
33%
Idaho
33%
Remote Sensing
33%
Agricultural and Biological Sciences
Forest Inventory
100%
Lidar
100%
Forest Stands
33%
Mathematical Model
33%
Remote Sensing
33%