Object-based classification of wetland vegetation using very high-resolution unmanned air system imagery

European Journal of Remote Sensing

Volumn 50, Issue 1, 2017, Pages 564-576

  Pande Chhetri, Roshan ^a   Abd Elrahman, Amr ^a   Liu, Tao ^a   Morton, Jon ^b   Wilhelm, Victor L ^c  

^a UNIVERSITY OF FLORIDA   (United States)

^b USACE   (United States)

^c US Army Corps of Engineers Jacksonville District   (United States)

Author keywords

object based classification; pixel based classification; Remote sensing; Support Vector Machine; UAS; wetland vegetation mapping

Indexed keywords

IMAGE CLASSIFICATION; MAPPING; MAXIMUM LIKELIHOOD; NEURAL NETWORKS; PIXELS; REMOTE SENSING; SUPPORT VECTOR MACHINES; UNMANNED AERIAL VEHICLES (UAV); VECTORS; VEGETATION; WETLANDS;

CLASSIFICATION PERFORMANCE; CLASSIFICATION SCHEME; OBJECT-BASED CLASSIFICATIONS; PIXEL BASED CLASSIFICATIONS; SUPPORT VECTOR MACHINE CLASSIFIERS; UNMANNED AIRCRAFT SYSTEM; VERY HIGH RESOLUTION; WETLAND VEGETATION;

IMAGE ENHANCEMENT;

ACCURACY ASSESSMENT; CLASSIFICATION; IMAGE CLASSIFICATION; IMAGERY; PERFORMANCE ASSESSMENT; PIXEL; REMOTE SENSING; SATELLITE IMAGERY; SUPPORT VECTOR MACHINE; UNMANNED VEHICLE; VEGETATION COVER; VEGETATION MAPPING; WETLAND;

EID: 85043535581     PISSN: None     EISSN: 22797254     Source Type: Journal    
DOI: 10.1080/22797254.2017.1373602     Document Type: Article

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