Prediction of street tree morphological parameters using artificial neural networks

Computers and Electronics in Agriculture

Volumn 67, Issue 1-2, 2009, Pages 9-17

  Jutras, Pierre ^a,b   Prasher, Shiv O ^b   Mehuys, Guy R ^b  

^a R and D Arboriculture   (Canada)

^b MCGILL UNIVERSITY   (Canada)

Author keywords

LIDAR laser; Multilayer perceptron; Street tree inventory; Tree morphological parameters prediction; Urban ecological conditions

Indexed keywords

LIDAR LASER; MULTILAYER PERCEPTRON; STREET TREE INVENTORY; TREE MORPHOLOGICAL PARAMETERS PREDICTION; URBAN ECOLOGICAL CONDITIONS;

DISTRIBUTION OF GOODS; ECOLOGY; ELECTRIC LOADS; LASERS; MULTILAYERS; OPTICAL RADAR; PROBABILITY DISTRIBUTIONS; ROADS AND STREETS;

NEURAL NETWORKS;

ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; DATA ACQUISITION; DECIDUOUS TREE; INVENTORY; LIDAR; MEASUREMENT METHOD; MODEL TEST; MODEL VALIDATION; MORPHOLOGY; PARAMETERIZATION; PERFORMANCE ASSESSMENT; PREDICTION; RESOURCE MANAGEMENT; URBAN ECOSYSTEM;

ACER; ACER PLATANOIDES; ACER SACCHARINUM; CELTIS OCCIDENTALIS; FRAXINUS; FRAXINUS PENNSYLVANICA; GLEDITSIA; GLEDITSIA TRIACANTHOS; MALVACEAE; TILIA CORDATA; ULMUS; ULMUS PUMILA;

EID: 67349189445     PISSN: 01681699     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compag.2009.02.008     Document Type: Article

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