Comparing pixel- and object-based approaches in effectively classifying wetland-dominated landscapes

Remote Sensing

Volumn 10, Issue 1, 2018, Pages

  Berhane, Tedros M ^a   Lane, Charles R ^b   Wu, Qiusheng ^c   Anenkhonov, Oleg A ^d   Chepinoga, Victor V ^e,f   Autrey, Bradley C ^b   Liu, Hongxing ^g  

^a PEGASUS TECHNICAL SERVICES INC   (United States)

^b U S ENVIRONMENTAL PROTECTION AGENCY   (United States)

^c BINGHAMTON UNIVERSITY   (United States)

^d INSTITUTE OF GENERAL AND EXPERIMENTAL BIOLOGY   (Russian Federation)

^e V B SOCHAVA INSTITUTE OF GEOGRAPHY   (Russian Federation)

^f IRKUTSK STATE UNIVERSITY   (Russian Federation)

^g UNIVERSITY OF CINCINNATI   (United States)

Author keywords

Lake Baikal; Maximum likelihood; Near infrared; Quickbird; Random forest; Segmentation

Indexed keywords

AQUATIC ECOSYSTEMS; CATCHMENTS; DECISION TREES; ECOLOGY; ECOSYSTEMS; IMAGE SEGMENTATION; INFRARED DEVICES; ITERATIVE METHODS; LAKES; MAXIMUM LIKELIHOOD; MAXIMUM LIKELIHOOD ESTIMATION; MOBILE TELECOMMUNICATION SYSTEMS; REMOTE SENSING; STATISTICAL TESTS; VEGETATION; WETLANDS;

ITERATIVE SELF-ORGANIZING DATA ANALYSIS TECHNIQUES; LAKE BAIKAL; NEAR INFRARED; OBJECT BASED IMAGE ANALYSIS (OBIA); PIXEL- AND OBJECT-BASED CLASSIFICATION; QUICKBIRD; RANDOM FORESTS; STATISTICALLY SIGNIFICANT DIFFERENCE;

PIXELS;

EID: 85040678879     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs10010046     Document Type: Article

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