Integration of orthoimagery and lidar data for object-based urban thematic mapping using random forests

International Journal of Remote Sensing

Volumn 34, Issue 14, 2013, Pages 5166-5186

  Guan, Haiyan ^a   Li, Jonathan ^a,b   Chapman, Michael ^c   Deng, Fei ^d   Ji, Zheng ^d   Yang, X ^e  

^a UNIVERSITY OF WATERLOO   (Canada)

^b XIAMEN UNIVERSITY   (China)

^c RYERSON UNIVERSITY   (Canada)

^d WUHAN UNIVERSITY   (China)

^e Unit 63961 ^*  (China)

Author keywords

[No Author keywords available]

Indexed keywords

AERIAL PHOTOGRAPHY; ANTENNAS; DECISION TREES; FEATURE EXTRACTION; IMAGE ANALYSIS; IMAGE ENHANCEMENT; IMAGE SEGMENTATION; ITERATIVE METHODS; LEARNING ALGORITHMS; LEARNING SYSTEMS; MAPPING; OPTICAL RADAR; PIXELS;

CLASSIFICATION ACCURACY; CLASSIFICATION RESULTS; HIGH SPATIAL RESOLUTION; IMAGE SEGMENTATION PROCESS; ITERATIVE FEATURE ELIMINATIONS; OBJECT BASED IMAGE ANALYSIS; OBJECT-BASED CLASSIFICATIONS; PIXEL BASED CLASSIFICATIONS;

CLASSIFICATION (OF INFORMATION);

ACCURACY ASSESSMENT; ALGORITHM; IMAGE ANALYSIS; IMAGE CLASSIFICATION; IMAGERY; LANDSCAPE; LIDAR; MULTISPECTRAL IMAGE; PIXEL; SPATIAL RESOLUTION; THEMATIC MAPPING; URBAN AREA;

BADEN-WURTTEMBERG; CANADA; GERMANY; MANNHEIM; NIAGARA FALLS [(WTF) NORTH AMERICA];

EID: 84876300410     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/01431161.2013.788261     Document Type: Article

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