Hierarchical Multiple Endmember Spectral Mixture Analysis (MESMA) of hyperspectral imagery for urban environments

[1]  R. Colwell.  Remote sensing of the environment , 1980, Nature.

[2]  Paul E. Johnson,et al.  Spectral mixture modeling: A new analysis of rock and soil types at the Viking Lander 1 Site , 1986 .

[3]  Paul E. Johnson,et al.  Spectral mixture modeling: A new analysis of rock and soil types at the Viking Lander 1 Site , 1986 .

[4]  John B. Adams,et al.  Quantitative subpixel spectral detection of targets in multispectral images. [terrestrial and planetary surfaces] , 1992 .

[5]  John B. Adams,et al.  Quantitative subpixel spectral detection of targets in multispectral images. [terrestrial and planetary surfaces] , 1992 .

[6]  J. Boardman,et al.  Mapping target signatures via partial unmixing of AVIRIS data: in Summaries , 1995 .

[7]  M. Ridd.  Exploring a V-I-S (vegetation-impervious surface-soil) model for urban ecosystem analysis through remote sensing: comparative anatomy for cities , 1995 .

[8]  S. Tompkins,et al.  Optimization of endmembers for spectral mixture analysis , 1997 .

[9]  N. Bryant,et al.  Investigation of the integration of AVIRIS and IFSAR for urban analysis , 1998 .

[10]  Margaret E. Gardner,et al.  Mapping Chaparral in the Santa Monica Mountains Using Multiple Endmember Spectral Mixture Models , 1998 .

[11]  Thomas H. Painter,et al.  The Effect of Grain Size on Spectral Mixture Analysis of Snow-Covered Area from AVIRIS Data , 1998 .

[12]  Thomas H. Painter,et al.  The Effect of Grain Size on Spectral Mixture Analysis of Snow-Covered Area from AVIRIS Data , 1998 .

[13]  R. Jenssen,et al.  1 THE HYMAP TM AIRBORNE HYPERSPECTRAL SENSOR : THE SYSTEM , CALIBRATION AND PERFORMANCE , 1998 .

[14]  G. F. Hepner,et al.  Investigation of imaging spectroscopy for discriminating urban land covers and surface materials. , 2001 .

[15]  Hermann Kaufmann,et al.  Automated differentiation of urban surfaces based on airborne hyperspectral imagery , 2001, IEEE Trans. Geosci. Remote. Sens..

[16]  Hermann Kaufmann,et al.  Automated differentiation of urban surfaces based on airborne hyperspectral imagery , 2001, IEEE Trans. Geosci. Remote. Sens..

[17]  C. Small.  Estimation of urban vegetation abundance by spectral mixture analysis , 2001 .

[18]  Eyal Ben-Dor,et al.  A spectral based recognition of the urban environment using the visible and near-infrared spectral region (0.4-1.1 µm). A case study over Tel-Aviv, Israel , 2001 .

[19]  C. Small,et al.  A global analysis of urban reflectance , 2005 .

[20]  R. Richter,et al.  Geo-atmospheric processing of airborne imaging spectrometry data. Part 2: Atmospheric/topographic correction , 2002 .

[21]  R. Richter,et al.  Geo-atmospheric processing of airborne imaging spectrometry data. Part 2: Atmospheric/topographic correction , 2002 .

[22]  Daniel Schläpfer,et al.  Geo-atmospheric processing of airborne imaging spectrometry data. Part 1: Parametric orthorectification , 2002 .

[23]  C. Small.  High spatial resolution spectral mixture analysis of urban reflectance , 2003 .

[24]  Martin Herold,et al.  Spectral resolution requirements for mapping urban areas , 2003, IEEE Trans. Geosci. Remote. Sens..

[25]  Susan L. Ustin,et al.  Evaluation of the potential of Hyperion for fire danger assessment by comparison to the Airborne Visible/Infrared Imaging Spectrometer , 2003, IEEE Trans. Geosci. Remote. Sens..

[26]  John R. Weeks,et al.  Measuring the Physical Composition of Urban Morphology Using Multiple Endmember Spectral Mixture Models , 2003 .

[27]  Martin Herold,et al.  The spatiotemporal form of urban growth: measurement, analysis and modeling , 2003 .

[28]  D. Roberts,et al.  Endmember selection for multiple endmember spectral mixture analysis using endmember average RMSE , 2003 .

[29]  D. Roberts,et al.  Endmember selection for multiple endmember spectral mixture analysis using endmember average RMSE , 2003 .

[30]  D. Roberts,et al.  A comparison of error metrics and constraints for multiple endmember spectral mixture analysis and spectral angle mapper , 2004 .

[31]  D. Roberts,et al.  A comparison of error metrics and constraints for multiple endmember spectral mixture analysis and spectral angle mapper , 2004 .

[32]  Margaret E. Gardner,et al.  Spectrometry for urban area remote sensing—Development and analysis of a spectral library from 350 to 2400 nm , 2004 .

[33]  M. Herold,et al.  Spectral characteristics of asphalt road aging and deterioration: implications for remote-sensing applications. , 2005, Applied optics.

[34]  Johannes R. Sveinsson,et al.  Classification of hyperspectral data from urban areas based on extended morphological profiles , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[35]  Conghe Song,et al.  Spectral mixture analysis for subpixel vegetation fractions in the urban environment: How to incorporate endmember variability? , 2005 .

[36]  Patrick Hostert,et al.  Correcting brightness gradients in hyperspectral data from urban areas , 2006 .

[37]  Dar A. Roberts,et al.  Multispectral Satellites - Imaging Spectrometry - LIDAR: Spatial - Spectral Tradeoffs in Urban Mapping , 2006 .

[38]  Dar A. Roberts,et al.  Multispectral Satellites - Imaging Spectrometry - LIDAR: Spatial - Spectral Tradeoffs in Urban Mapping , 2006 .

[39]  D. Roberts,et al.  Sub-pixel mapping of urban land cover using multiple endmember spectral mixture analysis: Manaus, Brazil , 2007 .

[40]  D. Roberts,et al.  Mapping tree and shrub leaf area indices in an ombrotrophic peatland through multiple endmember spectral unmixing , 2007 .

[41]  Dar A. Roberts,et al.  Characterizing Variability of the Urban Physical Environment for a Suite of Cities in Rondônia, Brazil , 2008 .

[42]  J. R. Jensen,et al.  Remote Sensing of Urban/Suburban Infrastructure and Socio‐Economic Attributes , 2011 .