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Handheld lidar sensors can accurately measure aboveground biomass
David H. Atkins
, Ryan C. Blackburn
, Daniel C. Laughlin
, Margaret M. Moore
,
Andrew J. Sánchez Meador
Forestry, School of
Ecological Restoration Institute (ERI)
Research output
:
Contribution to journal
›
Article
›
peer-review
1
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Keyphrases
Aboveground Biomass
100%
Handheld
100%
LiDAR Sensor
100%
IPad
50%
Mobile Laser Scanner
37%
Normalized Root-mean-square Error (NRMSE)
37%
LiDAR
25%
Modeling Approaches
25%
Arizona
12%
Rangeland
12%
Prediction Accuracy
12%
Elevational Gradient
12%
Data Collection Methods
12%
Simple Random
12%
Modeling Techniques
12%
IPhone
12%
Linear Regression Model
12%
Random Forest Regression
12%
Remote Sensing System
12%
Remote Sensing Techniques
12%
Remote Sensing Technology
12%
Affect Prediction
12%
Remote Sensing Approach
12%
Stepwise Regression
12%
Structural Variables
12%
Field-based Data
12%
Handheld Sensor
12%
Non-destructive Sampling
12%
Analog Method
12%
Linear Forest
12%
Via Minimization
12%
Random Forest Model
12%
Flagstaff
12%
Least Absolute Shrinkage and Selection Operator (LASSO)
12%
Spectral Variables
12%
Earth and Planetary Sciences
Aboveground Biomass
100%
Optical Radar
100%
Remote Sensing
50%
Root-Mean-Square Error
37%
Arizona
12%
United States of America
12%
Rangeland
12%
Agricultural and Biological Sciences
Aboveground Biomass
100%
Lidar
100%
Remote Sensing
50%
Random Forest
25%
Rangeland
12%
Feature Selection
12%
Medicine and Dentistry
Remote Sensing
100%
Linear Regression Analysis
25%