Corrigendum to: Comparison of support vector machine, random forest and neural network classifiers for tree species classification on airborne hyperspectral APEX images (European Journal of Remote Sensing, (2017), 50, 1, (144-154), 10.1080/22797254.2017.1299557);Comparison of support vector machine, random forest and neural network classifiers for tree species classification on airborne hyperspectral APEX images

European Journal of Remote Sensing

Volumn 50, Issue 1, 2017, Pages 144-154

  Raczko, Edwin ^a   Zagajewski, Bogdan ^a  

^a UNIVERSITY OF WARSAW   (Poland)

Author keywords

artificial neural networks; classification; hyperspectral data; random forest; Support vector machines

Indexed keywords

CLASSIFICATION (OF INFORMATION); DECISION TREES; FORESTRY; IMAGE CLASSIFICATION; RANDOM FORESTS; REMOTE SENSING; SUPPORT VECTOR MACHINES; VECTORS;

AIRBORNE HYPERSPECTRAL DATA; AIRBORNE PRISM EXPERIMENTS; BEECH (FAGUS SYLVATICA L.); CLASSIFICATION ALGORITHM; HYPERSPECTRAL DATA; NEURAL NETWORK CLASSIFIER; NONPARAMETRIC CLASSIFICATION; TREE SPECIES COMPOSITION;

NEURAL NETWORKS;

ACCURACY ASSESSMENT; AIRBORNE SENSING; ARTIFICIAL NEURAL NETWORK; COMMUNITY STRUCTURE; COMPARATIVE STUDY; DECIDUOUS TREE; IMAGE CLASSIFICATION; SATELLITE IMAGERY; SATELLITE SENSOR; SPECTRAL RESOLUTION; SUPPORT VECTOR MACHINE;

ALNUS; BETULA PENDULA; FAGUS; FAGUS SYLVATICA; LARIX; LARIX DECIDUA; PICEA;

EID: 85022191954     PISSN: None     EISSN: 22797254     Source Type: Journal    
DOI: 10.1080/22797254.2017.1309510     Document Type: Erratum

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