The use of airborne hyperspectral data for tree species classification in a species-rich Central European forest area

International Journal of Applied Earth Observation and Geoinformation

Volumn 52, Issue , 2016, Pages 464-474

  Richter, Ronny ^a,b   Reu, Björn ^a,d   Wirth, Christian ^a,c   Doktor, Daniel ^b   Vohland, Michael ^a,c  

^a UNIVERSITY OF LEIPZIG   (Germany)

^b HELMHOLTZ CENTRE FOR ENVIRONMENTAL RESEARCH UFZ   (Germany)

^c GERMAN CENTRE FOR INTEGRATIVE BIODIVERSITY RESEARCH IDIV HALLE JENA LEIPZIG   (Germany)

^d UNIVERSIDAD INDUSTRIAL DE SANTANDER   (Colombia)

Author keywords

CARS; Hyperspectral data; PLS DA; RF; Sample selection; Spectral variable selection; SVM; Tree species classification

Indexed keywords

ACCURACY ASSESSMENT; AIRBORNE SENSING; ALGORITHM; BROAD-LEAVED FOREST; FLOODPLAIN FOREST; IMAGE CLASSIFICATION; LEAST SQUARES METHOD; SPECIES RICHNESS; SPECTRAL ANALYSIS; STAND DYNAMICS; TREE; VEGETATION CLASSIFICATION;

CENTRAL EUROPE;

EID: 84997604985     PISSN: 15698432     EISSN: 1872826X     Source Type: Journal    
DOI: 10.1016/j.jag.2016.07.018     Document Type: Article

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