A novel semi-supervised method for obtaining finer resolution urban extents exploiting coarser resolution maps

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Volumn 7, Issue 10, 2014, Pages 4276-4287

  Li, Jun ^a   Gamba, Paolo ^b   Plaza, Antonio ^c  

^a SUN YAT SEN UNIVERSITY   (China)

^b UNIVERSITY OF PAVIA   (Italy)

^c UNIVERSITY OF EXTREMADURA   (Spain)

Author keywords

GlobCover product; Landsat data; Markov random fields (MRFs); Multinomial logistic regression (MLR); Semi supervised learning; Urban area mapping

Indexed keywords

IMAGE RESOLUTION; IMAGE SEGMENTATION; LEARNING ALGORITHMS; MAPPING; MARKOV PROCESSES; REGRESSION ANALYSIS; SAMPLING; STATISTICAL TESTS; SUPERVISED LEARNING;

GLOBCOVER; LANDSAT; MARKOV RANDOM FIELD; MULTINOMIAL LOGISTIC REGRESSION; SEMI- SUPERVISED LEARNING; URBAN AREAS;

CLASSIFICATION (OF INFORMATION);

LAND COVER; LANDSAT; LEARNING; MAP; MAPPING; MARKOV CHAIN; MULTIPLE REGRESSION; SATELLITE DATA; SPATIAL RESOLUTION; URBAN AREA;

BRAZIL; CHINA; GUANGDONG; GUANGZHOU; SAO PAULO [BRAZIL];

EID: 84920121030     PISSN: 19391404     EISSN: 21511535     Source Type: Journal    
DOI: 10.1109/JSTARS.2014.2355843     Document Type: Article

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