Intra-and-inter species biomass prediction in a plantation forest: Testing the utility of high spatial resolution spaceborne multispectral rapideye sensor and advanced machine learning algorithms

Sensors (Switzerland)

Volumn 14, Issue 8, 2014, Pages 15348-15370

  Dube, Timothy ^a   Mutanga, Onisimo ^a   Elhadi, Adam ^a,b   Ismail, Riyad ^a  

^a UNIVERSITY OF KWAZULU NATAL   (South Africa)

^b UNIVERSITY OF THE WITWATERSRAND   (South Africa)

Author keywords

Bag fraction; Biosphere atmospheric interactions; High resolution rapideye imagery; Learning rate; Tree complexity; Variable importance and variable selection

Indexed keywords

ADAPTIVE BOOSTING; ALGORITHMS; ARTIFICIAL INTELLIGENCE; DECISION TREES; FORECASTING; FORESTRY; LEARNING SYSTEMS; REMOTE SENSING; BIOMASS; CARBON; STOCHASTIC MODELS; STOCHASTIC SYSTEMS;

BAG FRACTION; LEARNING RATES; RAPIDEYE; TREE COMPLEXITY; VARIABLE SELECTION; ATMOSPHERIC INTERACTION;

BIOMASS; LEARNING ALGORITHMS;

ALGORITHMS; BIOMASS; FORESTRY; REMOTE SENSING; FORESTS; PLANTATIONS;

EID: 84919824337     PISSN: 14248220     EISSN: None     Source Type: Journal    
DOI: 10.3390/s140815348     Document Type: Article

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