Prediction and validation of foliage projective cover from Landsat-5 TM and Landsat-7 ETM+ imagery

Journal of Applied Remote Sensing

Volumn 3, Issue 1, 2009, Pages

  Armston, John D ^a   Denham, Robert J ^a   Danaher, Tim J ^b   Scarth, Peter F ^a   Moffiet, Trevor N ^c  

^a DEPARTMENT OF ENVIRONMENT AND RESOURCE MANAGEMENT   (Australia)

^b Information Sciences Branch   (Australia)

^c UNIVERSITY OF NEWCASTLE   (Australia)

Author keywords

airborne LiDAR; fractional cover; machine learning; regression; stand basal area

Indexed keywords

DECISION TREES; FORECASTING; FORESTRY; LEARNING SYSTEMS; LINEAR REGRESSION; MACHINE LEARNING; OPTICAL RADAR; PLANTS (BOTANY); SUPPORT VECTOR MACHINES;

AIRBORNE LIDAR; FOLIAGE PROJECTIVE COVERS; FRACTIONAL COVER; GENERALIZED LINEAR MODEL; MACHINE LEARNING MODELS; MULTIPLE LINEAR REGRESSIONS; REGRESSION; STAND BASAL AREA;

LITHIUM COMPOUNDS;

ARTIFICIAL INTELLIGENCE; BASAL AREA; DECISION MAKING; FORESTRY; PLANTS; RADAR; REGRESSION ANALYSIS;

EID: 72649085339     PISSN: None     EISSN: 19313195     Source Type: Journal    
DOI: 10.1117/1.3216031     Document Type: Article

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