Characterizing Urban Subpixel Composition Using Spectral Mixture Analysis

Urban Remote Sensing: Monitoring, Synthesis and Modeling in the Urban Environment

Volumn , Issue , 2011, Pages 111-128

  Powell, Rebecca ^a  

^a UNIVERSITY OF DENVER   (United States)

Author keywords

Accuracy assessment one measure of model fit generated by SMA algorithm itself, and RMS error; Goal of EAR, representative spectrum material class in a library, and RMS error; Mapping fraction images; MESMA implementation quantifying V I S components of urban land cover; MESMA tests multiple models, identifying one "best fit" model, pixel based on selection criteria and measure of goodness of fit; Multiple end member spectral analysis (MESMA) technique mapping urban V I S components; SMA implementation method accounting for mixed pixels; SMA methodology case studies, flexibility of MESMA in mapping V I S components in different environments; SMA models, set of end members representing basic spectral components of landscape; Urban subpixel composition characterization using spectral mixture analysis

Indexed keywords

DEFORESTATION; MIXTURES; PIXELS; REMOTE SENSING; SPECTRUM ANALYSIS; VEGETATION;

BEST-FIT MODELS; CASE-STUDIES; ENDMEMBERS; FRACTION IMAGES; MIXED PIXEL; MODEL FIT; RMS ERRORS; SPECTRAL MIXTURE ANALYSIS; URBAN LAND COVER;

PHOTOMAPPING;

EID: 84870240054     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1002/9780470979563.ch8     Document Type: Chapter

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