Estimation of urban vegetation abundance by spectral mixture analysis

International Journal of Remote Sensing ◽

10.1080/01431160151144369 ◽

2001 ◽

Vol 22 (7) ◽

pp. 1305-1334 ◽

Author(s):

C. Small

Keyword(s):

Spectral Mixture Analysis ◽

Urban Vegetation ◽

Mixture Analysis ◽

Spectral Mixture

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Remote sensing of urban vegetation life form by spectral mixture analysis of high‐resolution IKONOS satellite images

International Journal of Remote Sensing ◽

10.1080/01431160600784176 ◽

2007 ◽

Vol 28 (5) ◽

pp. 985-1000 ◽

Author(s):

J. Nichol ◽

M. S. Wong

Keyword(s):

Remote Sensing ◽

High Resolution ◽

Satellite Images ◽

Life Form ◽

Spectral Mixture Analysis ◽

Urban Vegetation ◽

Mixture Analysis ◽

Spectral Mixture

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Improvement of linear spectral mixture analysis and experimentation in estimation of urban vegetation fraction

Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS '05. ◽

10.1109/igarss.2005.1525405 ◽

2005 ◽

Author(s):

Wenze Yue ◽

Jianhua Xu ◽

Jiawei Wu

Keyword(s):

Spectral Mixture Analysis ◽

Urban Vegetation ◽

Mixture Analysis ◽

Vegetation Fraction ◽

Linear Spectral Mixture Analysis ◽

Spectral Mixture

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Estimation and vicarious validation of urban vegetation abundance by spectral mixture analysis

Remote Sensing of Environment ◽

10.1016/j.rse.2005.10.023 ◽

2006 ◽

Vol 100 (4) ◽

pp. 441-456 ◽

Author(s):

Christopher Small ◽

Jacqueline W.T. Lu

Keyword(s):

Spectral Mixture Analysis ◽

Urban Vegetation ◽

Mixture Analysis ◽

Spectral Mixture

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Extracting urban vegetation characteristics using spectral mixture analysis and decision tree classifications

Remote Sensing of Environment ◽

10.1016/j.rse.2008.10.005 ◽

2009 ◽

Vol 113 (2) ◽

pp. 398-407 ◽

Author(s):

Thoreau Rory Tooke ◽

Nicholas C. Coops ◽

Nicholas R. Goodwin ◽

James A. Voogt

Keyword(s):

Decision Tree ◽

Spectral Mixture Analysis ◽

Urban Vegetation ◽

Mixture Analysis ◽

Vegetation Characteristics ◽

Spectral Mixture

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Bayesian Spectral Mixture Analysis for Urban Vegetation

Urban Remote Sensing ◽

10.1201/9781315166612-12 ◽

2018 ◽

pp. 107-124

Keyword(s):

Spectral Mixture Analysis ◽

Urban Vegetation ◽

Mixture Analysis ◽

Spectral Mixture

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Monitoring spatiotemporal changes of urban vegetation abundance by normalized spectral mixture analysis (NSMA): the case study of Nanjing, China

10.1117/12.614717 ◽

2005 ◽

Author(s):

Su Li ◽

Dafang Zhuang ◽

Zhiqiang Gao ◽

Shunyan Hou

Keyword(s):

Spectral Mixture Analysis ◽

Urban Vegetation ◽

Mixture Analysis ◽

Spatiotemporal Changes ◽

Spectral Mixture

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Assessing and monitoring of urban vegetation using multiple endmember spectral mixture analysis

10.1117/12.2027500 ◽

2013 ◽

Author(s):

M. A. Zoran ◽

R. S. Savastru ◽

D. M. Savastru

Keyword(s):

Spectral Mixture Analysis ◽

Urban Vegetation ◽

Mixture Analysis ◽

Spectral Mixture

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Mapping two Eucalyptus subgenera using multiple endmember spectral mixture analysis and continuum-removed imaging spectrometry data

Remote Sensing of Environment ◽

10.1016/j.rse.2010.12.012 ◽

2011 ◽

Vol 115 (5) ◽

pp. 1115-1128 ◽

Author(s):

Kara N. Youngentob ◽

Dar A. Roberts ◽

Alex A. Held ◽

Philip E. Dennison ◽

Xiuping Jia ◽

...

Keyword(s):

Spectral Mixture Analysis ◽

Mixture Analysis ◽

Imaging Spectrometry ◽

Spectral Mixture

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Estimating wetland vegetation abundance based on spectral mixture analysis: a comparison between LSMA and FCM classification methods

International Journal of Remote Sensing ◽

10.1080/01431161.2013.866292 ◽

2013 ◽

Vol 35 (1) ◽

pp. 189-203 ◽

Author(s):

Zhaoning Gong ◽

Tianxiang Cui ◽

Huili Gong

Keyword(s):

Wetland Vegetation ◽

Spectral Mixture Analysis ◽

Classification Methods ◽

Mixture Analysis ◽

Spectral Mixture

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High spatial resolution spectral mixture analysis of urban reflectance

Remote Sensing of Environment ◽

10.1016/j.rse.2003.04.008 ◽

2003 ◽

Vol 88 (1-2) ◽

pp. 170-186 ◽

Author(s):

Christopher Small

Keyword(s):

Spatial Resolution ◽

High Spatial Resolution ◽

Spectral Mixture Analysis ◽

Mixture Analysis ◽

Spectral Mixture

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