Predicting categorical forest variables using an improved k-Nearest Neighbour estimator and Landsat imagery

Remote Sensing of Environment

Volumn 113, Issue 3, 2009, Pages 500-517

  Tomppo, Erkki O ^a   Gagliano, Caterina ^b   De Natale, Flora ^b   Katila, Matti ^a   McRoberts, Ronald E ^c  

^a FINNISH FOREST RESEARCH INSTITUTE   (Finland)

^b Planning Research Unit   (Italy)

^c USDA FOREST SERVICE   (United States)

Author keywords

Categorical variables; Genetic algorithm; ik NN; National Forest Inventory

Indexed keywords

FORESTRY; FUNCTION EVALUATION; GENETIC ALGORITHMS; PARAMETER ESTIMATION; VECTORS;

ACCURACY MEASURES; CATEGORICAL VARIABLES; DATA SETS; DISTANCE METRIC; ESTIMATION PARAMETERS; FEATURE SPACES; FINNISH; FITNESS FUNCTIONS; FOREST TYPES; IK-NN; LANDSAT IMAGERIES; NATIONAL FOREST INVENTORY; OPTIMISATION; POSITIVE EFFECTS; PREDICTION ACCURACIES; PREDICTION TECHNIQUES; SATELLITE IMAGES; SPECTRAL DATUMS; TEST SITES; TREE SPECIES; WEIGHT VECTORS;

FORECASTING;

DATA SET; FITNESS; FOREST INVENTORY; GENETIC ALGORITHM; LANDSAT; OPTIMIZATION; PIXEL; SATELLITE IMAGERY;

ALGORITHMS; DATA PROCESSING; FORECASTS; FORESTS; INVENTORY CONTROL; OPTIMIZATION; PARAMETERS; SPECIES IDENTIFICATION;

EID: 58249137246     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2008.05.021     Document Type: Article

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