A manifold learning approach to urban land cover classification with optical and radar data

Landscape and Urban Planning

Volumn 172, Issue , 2018, Pages 11-24

  Zhang, Hongsheng ^a   Li, Jiang ^b   Wang, Ting ^a   Lin, Hui ^a   Zheng, Zezhong ^c   Li, Yu ^a   Lu, Yufeng ^c  

^a CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

^b OLD DOMINION UNIVERSITY   (United States)

^c UNIVERSITY OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA   (China)

Author keywords

Manifold learning; Multisource data fusion; Optical and SAR; Urban land covers

Indexed keywords

DATA FUSION; ECOLOGY; PIXELS; SYNTHETIC APERTURE RADAR;

INTRINSIC DIMENSIONALITIES; MANIFOLD LEARNING; METHODOLOGICAL FRAMEWORKS; MULTISOURCE DATA; OPTICAL AND SAR; PRINCIPLE COMPONENT ANALYSIS; URBAN LAND COVER; URBAN LAND COVER CLASSIFICATION;

LEARNING SYSTEMS;

ACCURACY ASSESSMENT; EXPERIMENTAL STUDY; LAND CLASSIFICATION; LAND COVER; LANDSCAPE ECOLOGY; LEARNING; OPTICAL METHOD; PRINCIPAL COMPONENT ANALYSIS; RADAR; SATELLITE DATA; URBAN AREA;

EID: 85043478107     PISSN: 01692046     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.landurbplan.2017.12.009     Document Type: Article

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