Converting local spectral and spatial information from a priori classifiers into contextual knowledge for impervious surface classification

ISPRS Journal of Photogrammetry and Remote Sensing

Volumn 66, Issue 5, 2011, Pages 579-587

  Luo, Li ^a   Mountrakis, Giorgos ^a  

^a STATE UNIVERSITY OF NEW YORK   (United States)

Author keywords

Contextual classification; Hybrid classifiers; Impervious surfaces; Landsat ETM+; Partial classification

Indexed keywords

BACK PROPAGATION NEURAL NETWORKS; CLASSIFICATION MODELS; CLASSIFICATION TASKS; CLASSIFIED INFORMATION; CONTEXTUAL CLASSIFICATION; CONTEXTUAL INFORMATION; CONTEXTUAL KNOWLEDGE; DATA SETS; HYBRID CLASSIFIERS; IMPERVIOUS SURFACE; KAPPA STATISTIC; LANDSAT; LANDSAT ETM+; MISCLASSIFICATIONS; NEW YORK; POSTERIORI; SCENE CLASSIFICATION; SPATIAL CORRELATIONS; SPATIAL INFORMATIONS; SPECIFIC KNOWLEDGE; SPECTRAL REPRESENTATIONS;

ALGORITHMS; NEURAL NETWORKS; PIXELS;

CLASSIFICATION (OF INFORMATION);

ALGORITHM; BACK PROPAGATION; DATA SET; IMAGE CLASSIFICATION; LANDSAT; PIXEL; PRIORITIZATION; SPATIOTEMPORAL ANALYSIS; SPECTRAL ANALYSIS;

NEW YORK [UNITED STATES]; UNITED STATES;

EID: 80052804477     PISSN: 09242716     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.isprsjprs.2011.03.002     Document Type: Article

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