A spatially adaptive spectral mixture analysis for mapping subpixel urban impervious surface distribution

Remote Sensing of Environment

Volumn 133, Issue , 2013, Pages 62-70

  Deng, Chengbin ^a   Wu, Changshan ^a  

^a UNIVERSITY OF WISCONSIN MILWAUKEE   (United States)

Author keywords

Endmember extraction; Endmember variability; Spectral mixture analysis; Urban land cover; V I S model

Indexed keywords

CLASSIFICATION TREE METHOD; ENDMEMBER EXTRACTION; ENDMEMBER SELECTION; ENDMEMBER VARIABILITIES; ENDMEMBERS; HIGH PRECISION; IMPERVIOUS SURFACE; LAND COVER; LOCAL SEARCH; MEAN ABSOLUTE ERROR; OPTIMAL RESULTS; ROOT MEAN SQUARE ERRORS; SPATIAL INFORMATIONS; SPATIALLY ADAPTIVE; SPECTRAL MIXTURE ANALYSIS; SUB PIXELS; SUBPIXEL LEVELS; SYNTHETIC SPECTRA; URBAN ENVIRONMENTS; URBAN IMPERVIOUS SURFACES; URBAN LAND COVER; WITHIN CLASS;

MEAN SQUARE ERROR;

MIXTURES;

ACCURACY ASSESSMENT; LAND COVER; MAPPING METHOD; PIXEL; SPATIAL ANALYSIS; SPECTRAL ANALYSIS; URBAN AREA;

EID: 84874733862     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2013.02.005     Document Type: Article

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