Spectral mixture analysis for subpixel vegetation fractions in the urban environment: How to incorporate endmember variability?

Remote Sensing of Environment

Volumn 95, Issue 2, 2005, Pages 248-263

  Song, Conghe ^a  

^a University of North Carolina at Chapel Hill   (United States)

Author keywords

Bayes Theorem; Ikonos; Landsat; NDVI; Spectral mixture analysis; Urban remote sensing

Indexed keywords

BIOCHEMISTRY; COMPOSITION; IMAGE SENSORS; MIXTURES; PROBABILITY DISTRIBUTIONS; STATISTICAL METHODS; THEOREM PROVING; VEGETATION;

LANDSCAPES; SPECTRAL MIXTURE ANALYSIS (SMA); SURFACE BIOPHYSICAL PROCESSES; URBAN AREAS;

REMOTE SENSING;

IKONOS; IMAGE ANALYSIS; LANDSAT THEMATIC MAPPER; NDVI; PIXEL; REMOTE SENSING; SPECTRAL ANALYSIS; URBAN AREA;

EID: 14744289023     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2005.01.002     Document Type: Article

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