Semantic classification of urban buildings combining VHR image and GIS data: An improved random forest approach

ISPRS Journal of Photogrammetry and Remote Sensing

Volumn 105, Issue , 2015, Pages 107-119

  Du, Shihong ^a   Zhang, Fangli ^a   Zhang, Xiuyuan ^a  

^a PEKING UNIVERSITY   (China)

Author keywords

Object based image analysis (OBIA); Random forest; Semantic classification; Urban buildings; Very high resolution (VHR) images

Indexed keywords

BUILDINGS; CLASSIFIERS; DECISION TREES; IMAGE SEGMENTATION;

OBJECT BASED IMAGE ANALYSIS (OBIA); RANDOM FORESTS; SEMANTIC CLASSIFICATION; URBAN BUILDINGS; VERY HIGH RESOLUTION (VHR) IMAGE;

SEMANTICS;

BUILDING; ENVIRONMENTAL ISSUE; FOREST ECOSYSTEM; GIS; IMAGE ANALYSIS; IMAGE CLASSIFICATION; SATELLITE DATA; SEGMENTATION; URBAN AREA;

BEIJING [CHINA]; CHINA;

EID: 84927672061     PISSN: 09242716     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.isprsjprs.2015.03.011     Document Type: Article

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