Predicting Species Cover of Marine Macrophyte and Invertebrate Species Combining Hyperspectral Remote Sensing, Machine Learning and Regression Techniques

PLoS ONE

Volumn 8, Issue 6, 2013, Pages

  Kotta, Jonne ^a   Kutser, Tiit ^a   Teeveer, Karolin ^a   Vahtmäe, Ele ^a   Pärnoja, Merli ^a  

^a UNIVERSITY OF TARTU   (Estonia)

Author keywords

[No Author keywords available]

Indexed keywords

SEA WATER;

ABIOTIC STRESS; AQUATIC SPECIES; ARTICLE; BALTIC SEA; BENTHOS; BOOSTED REGRESSION TREE MODELLING; ENVIRONMENTAL FACTOR; ENVIRONMENTAL MONITORING; INVERTEBRATE; MACHINE LEARNING; MACROPHYTE; MARINE ENVIRONMENT; NONHUMAN; PREDICTION; REMOTE SENSING; SPATIAL ANALYSIS; SPECIES COVER; STATISTICAL ANALYSIS; ANIMAL; ARTIFICIAL INTELLIGENCE; ECOSYSTEM; ESTONIA; GEOGRAPHY; PHYSIOLOGY; PRINCIPAL COMPONENT ANALYSIS; REGRESSION ANALYSIS; SEA; SPECIES DIFFERENCE;

INVERTEBRATA;

ANIMALS; AQUATIC ORGANISMS; ARTIFICIAL INTELLIGENCE; ECOSYSTEM; ESTONIA; GEOGRAPHY; INVERTEBRATES; OCEANS AND SEAS; PRINCIPAL COMPONENT ANALYSIS; REGRESSION ANALYSIS; REMOTE SENSING TECHNOLOGY; SPECIES SPECIFICITY;

EID: 84878640040     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0063946     Document Type: Article

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