Comparing echo-based and canopy height model-based metrics for enhancing estimation of forest aboveground biomass in a model-assisted framework

Remote Sensing of Environment

Volumn 174, Issue , 2016, Pages 1-9

  Chirici, Gherardo ^a   McRoberts, Ronald E ^b   Fattorini, Lorenzo ^c   Mura, Matteo ^d   Marchetti, Marco ^d  

^a UNIVERSITY OF FLORENCE   (Italy)

^b USDA FOREST SERVICE   (United States)

^c UNIVERSITY OF SIENA   (Italy)

^d UNIVERSITY OF MOLISE   (Italy)

Author keywords

Airborne laser scanning metrics; Forest biomass; K Nearest Neighbors; Model assisted estimator; Tessellation stratified sampling

Indexed keywords

BIOMASS; FORECASTING; FORESTRY; LASER APPLICATIONS; MOTION COMPENSATION; NEAREST NEIGHBOR SEARCH; POPULATION STATISTICS; SURFACE ANALYSIS;

ABOVEGROUND BIOMASS; AIRBORNE LASER SCANNING; CANOPY HEIGHT MODELS; FOREST BIOMASS; K-NEAREST NEIGHBORS; NON-PARAMETRIC MODEL; PREDICTION TECHNIQUES; STRATIFIED SAMPLING;

PARAMETER ESTIMATION;

ABOVEGROUND BIOMASS; AIRBORNE SENSOR; ALGORITHM; CANOPY ARCHITECTURE; COMPARATIVE STUDY; ECHO SOUNDING; ESTIMATION METHOD; FOREST INVENTORY; LASER METHOD; PARAMETERIZATION; SAMPLING; THREE-DIMENSIONAL MODELING;

ITALY; MOLISE;

EID: 84949495982     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2015.11.010     Document Type: Article

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