Evaluation of alternative methods for using LiDAR to predict aboveground biomass in mixed species and structurally complex forests in northeastern North America

Mathematical and Computational Forestry and Natural-Resource Sciences

Volumn 7, Issue 2, 2015, Pages 49-65

  Hayashi, Rei ^a   Kershaw, John A ^b   Weiskittel, Aaron ^a  

^a UNIVERSITY OF MAINE   (United States)

^b UNIVERSITY OF NEW BRUNSWICK   (Canada)

Author keywords

Fixed radius plots; LiDAR; maine; New brunswick; Nonlinear mixed effects models; Random forest; Variableradius plots

Indexed keywords

DECISION TREES; EXTRACTION; FORESTRY; OPTICAL RADAR; PREDICTIVE ANALYTICS; RANDOM FORESTS; REMOTE SENSING; STATISTICAL METHODS;

FIXED-RADIUS PLOTS; MAINE; NEW BRUNSWICK; NONLINEAR MIXED EFFECTS; VARIABLERADIUS PLOTS;

FORECASTING;

ABOVEGROUND BIOMASS; BIOMASS BURNING; FOREST DYNAMICS; FOREST MANAGEMENT; LIDAR; REMOTE SENSING; SATELLITE DATA; SATELLITE IMAGERY;

NORTH AMERICA;

EID: 84949231973     PISSN: None     EISSN: 19467664     Source Type: Journal    
DOI: None     Document Type: Article

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