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Citations

This is a partial list of key references in the field of Spectral Mixture Analysis.  Let us know if you know of citations which are missing form these lists and we will add them.
 
Selected Citations
Complete Citations List
 
Selected Citations:

  • Roberts, D.A., Dennison, P.E., Gardner, M., Hetzel, Y., Ustin, S.L., and Lee, C., 2003, Evaluation of the Potential of Hyperion for Fire Danger Assessment by Comparison to the Airborne Visible/Infrared Imaging Spectrometer, IEEE Trans. On Geosci. Remote Sens, 41 (6 Part 1): 1297-1310.
  • Dennison, P.E., and Roberts, D.A.,2003 Endmember Selection for Multiple Endmember Spectral Mixture Analysis using Endmember Average RSME, Remote Sens. Environ., 87(2-3), 123-135.
  • Dennison, P.E., and Roberts, D.A., 2003, The Effects of Vegetation Phenology on Endmember Selection and Species Mapping in Southern California Chaparral, Remote Sens. Environ., 87(2-3), 123-135.
  • Ustin, S.L., Roberts, D.A., Gamon, J.A., Asner, G.P., and Green, R.O., 2004, Using Imaging Spectroscopy to Study Ecosystem Processes and Properties, Bioscience, 54(6) 523-534.

 
Complete Citation List:

  • Adams, JB, Smith, MO and Gillespie, AR .1993. Imaging spectrometry: interpretation based on spectral mixture analysis, In Pieters CM, Englert P, editors. Remote geochemical analysis: elemental and mineralogical composition. New York: Cambridge Univ. Press; 1993: p145-166. (Vol. 7).
  • Asner, G.P., M.M.C. Bustamante, and A.R. Townsend. 2003. Scale dependence of biophysical structure in deforested lands bordering the Tapajós National Forest, Central Amazon. Remote Sensing of Environment 87:507-520.
  • Asner, G.P., and Lobell, D. B., 2000,  A biogeophysical approach for automated SWIR unmixing of Soils and Vegetation, Remote Sens. Environ., 74, 99-112.
  • Ballantine, J-A C., Okin, G.S., Prentiss, D.E., and Roberts, D.A. 2005, Mapping African landforms using continental scale unmixing of MODIS imagery, Remote Sensing of Environment, 97, 470-483.
  • Bateson, A., and Curtiss, B., 1996, A method for manual endmember selection and spectral unmixing, Remote Sens. Environ., 55, 229-243.
  • Bateson, C.A., Asner, G.P., and Wessman, C., 2000, Endmember Bundles: A new approach to incorporating endmember variability into spectral mixture analysis. IEEE Trans. Geosci. Remote Sens., 38, 1083-1094.
  • Boardman, J.W., Kruse, F.A., and Green, R.O., 1995, Mapping target signatures via partial unmixing of AVIRIS data in Summaries of the 5th JPL Airborne Earth Science Workshop, JPL Publication 95-1, Vol 1, Jet Propulsion Laboratory, Pasadena, CA pp. 23-26.
  • Clark, M., 2005, An assessment of Hyperspectral and Lidar Remote Sensing for the Monitoring of Tropical Rain Forest Trees, PhD Dissertation, University of California, Santa Barbara, 319 pp.
  • Collins, E.F., Roberts, D.A., and Borel, C.C., 2001, Spectral Mixture Analysis of Simulated Thermal Infrared Spectrometry Data: an Initial Temperature Estimate Bounded TESSMA Search Approach, IEEE Trans. Geosci. Remote Sens 39(7) 1435-1446.
  • Dennison, P.E., Charoensiri, K., Roberts, D.A., Peterson, S.H., and Green, R.O., 2006, Wildfire temperature and Land Cover Modeling Using Hyperspectral Data, Remote Sensing of Environment, 100, 212-222.
  • Dennison, P.E., Halligan, K. Q., Roberts, D.A., 2004, A Comparison of Error Metrics and Constraints for Multiple Endmember Spectral Mixture Analysis and Spectral Angle Mapper, Remote Sens. Environ. 93, 359-367.
  • Dennison, P.E., and Roberts, D.A.,2003a, Endmember Selection for Multiple Endmember Spectral Mixture Analysis using Endmember Average RSME, Remote Sens. Environ., 87(2-3), 123-135.
  • Dennison, P.E., and Roberts, D.A., 2003b, The Effects of Vegetation Phenology on Endmember Selection and Species Mapping in Southern California Chaparral, Remote Sens. Environ., 87(2-3), 123-135.
  • Dennison, P.E., Roberts, D.A., and Peterson, S.H., 2007, Spectral shape-based temporal compositing algorithms for MODIS surface reflectance data.  Remote Sens. Environ. 109, 510-522
  • Elmore, A.J., Mustard, J.F., Manning, S.J., and Lobell, D.B., 2000, Quantifying vegetation change in semiarid environments: precision and accuracy of spectral mixture analysis and the normalized difference vegetation index, Remote Sens. Environ., 73, 87-102.
  • Gardner, M., 1997, Mapping chaparral with AVIRIS using Advanced Remote Sensing Techniques, Masters Thesis, University of California, Santa Barbara, 58 pp.
  • Green, R.O., Conel, J.E. and Roberts, D.A., 1993, Estimation of Aerosol Optical Depth, Pressure Elevation, Water Vapor and Calculation of Apparent Surface Reflectance from Radiance Measured by the Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) Using MODTRAN2, SPIE Conf. 1937, Imaging Spectrometry of the Terrestrial Environment, 2-5.
  • Halligan, K.Q., 2002, Multiple Endmember Spectral Mixture Analysis of Vegetation in the Northeast Corner of Yellowstone National Park, Masters Thesis, University of California, Santa Barbara, 64 pp.
  • Herold, M., Gardner, M., and Roberts, D.A., 2003, Spectral Resolution Requirements for Mapping Urban Areas, IEEE Trans. Geosci. Remote Sens. 41 (9 Part 1): 1907-1919.
  • Herold, M., Roberts, D.A., Gardner, M.E. and Dennison, P.E., 2004, Spectrometry for urban area remote sensing – Development and analysis of a spectral library from 350 to 2400 nm, Remote Sens. Environ. Vol 91 (3-4) 304-319.
  • Johnson, J.R., Staid, M.I., Titus, T.N., and Becker, K., 2006, Shocked plagioclase signatures in Thermal Emission Spectrometer Data of Mars, Icarus, 180: 60-74.
  • Li, L., USTIN, S.L. and LAY, M., 2005, Application of multiple endmember spectral mixture analysis (MESMA) to AVIRIS imagery for coastal salt marsh mapping: a case study in China Camp, CA, USA. International Journal of Remote Sensing, 26, 5193-5207.
  • Li, L., and Mustard, J.F., 2003, Highland contamination in lunar mare soils: Improved mapping with multiple end-member spectral mixture analysis, J. Geophys. Res. 108, doi: 10.1029/2002JE001917.5033
  • Okin, G.S., Roberts, D.A., Murray, B., and Okin, W.J., 2000, Practical limits on hyperspectral vegetation discrimination in arid and semiarid environments, Remote Sens. Env., 77(2): 212-225.
  • Painter, T.H., Dozier, J., Roberts, D.A., Davis, R.E., and Green, R.O., 2003, Retrieval of Subpixel Snow-covered Area and Grain Size from Imaging Spectrometer Data, Remote Sens. Environ., 85, 64-77.
  • Painter, T.H., Roberts, D.A., Green, R.O., and Dozier, J., 1998, The Effect of Grain Size on Spectral Mixture Analysis of Snow-covered Area from AVIRIS Data, Rem. Sens. Environ. 65:320-332.
  • Powell, R., 2006, Long-Term Monitoring of Urbanization in the Brazilian Amazon Using Remote Sensing, Unpublished UCSB PhD Dissertation, 257 p
  • Powell, R., D.A. Roberts, P.E. Dennison and L.L. Hess, 2007. Sub-pixel mapping of urban land cover using multiple endmember spectral mixture analysis: Manaus, Brazil, Remote Sens. Environ., 106: 253-267
  • Rashed, T.,  Weeks, J.R., Roberts, D., Rogan, J., and Powell, R., 2003, Measuring the Physical Composition of Urban Morphology using Multiple Endmember Spectral Mixture Models, Photogramm. Eng. Remote Sens. 69(9) 1011-1020.
  • Roberts, D.A., Adams, J.B., and Smith, M.O., 1993, Discriminating Green Vegetation, Non-Photosynthetic Vegetation and Soils in AVIRIS Data,  Rem. Sens. Environ., 44: 2/3 255-270.
  • Roberts, D.A., Batista, G., Pereira, J., Waller, E., and Nelson, B. 1998, Change Identification using Multitemporal Spectral Mixture Analysis: Applications in Eastern Amazonia, Chapter 9 in Remote Sensing Change Detection: Environmental Monitoring Applications and Methods, (Elvidge, C. and Lunetta R., Eds.), Ann Arbor Press, Ann Arbor, MI, pp. 137-161.
  • Roberts, D.A., Brown, K.J., Green, R., Ustin, S., and Hinckley, T., 1998, Investigating the relationship between liquid water and leaf area in clonal Populus, Proc. 7th AVIRIS Earth Science Workshop JPL 97-21, Pasadena, CA 91109, 335-344.
  • Roberts, D.A., Dennison, P.E., Gardner, M., Hetzel, Y., Ustin, S.L., and Lee, C., 2003,  Evaluation of the Potential of Hyperion for Fire Danger Assessment by Comparison to the Airborne Visible/Infrared Imaging Spectrometer, IEEE Trans. On Geosci. Remote Sens, 41 (6 Part 1): 1297-1310.
  • Roberts, D.A., Gardner, M., Church, R., Ustin, S.L., and Green, R.O., 1997, Optimum Strategies for Mapping Vegetation using Multiple Endmember Spectral Mixture Models, in SPIE Conf. Vol 3118, Imaging Spectrometry III, 108-119., San Diego, CA July 27-Aug 1, 1997.
  • Roberts, D.A., Gardner, M., Church, R., Ustin, S., Scheer, G.,and Green, R.O., 1998, Mapping Chaparral in the Santa Monica Mountains using Multiple Endmember Spectral Mixture Models, Rem. Sens. Environ. 65: 267-279.
  • Roberts, D.A., Green, R.O., and Adams, J.B., 1997,Temporal and Spatial Patterns in Vegetation and Atmospheric Properties from AVIRIS, Remote Sens. Environ 62: 223-240.
  • Roberts, D.A. and Herold, M. 2004. Imaging Spectrometry of Urban Materials, in Molecules to Planets: Infrared Spectroscopy in Geochemistry, Exploration Geochemistry and Remote Sensing (P. King, M. Ramsey and G. Swayze, Ed)., Mineral Association of Canada, 155-183.
  • Roberts, D.A., Numata, I., Holmes, K.W., Batista, G., Krug, T., Monteiro, A., Powell, B., and Chadwick, O., 2002, Large area mapping of land-cover change in Rondônia using multitemporal spectral mixture analysis and decision tree classifiers, J. Geophys. Res. Atm., 107 (D20), 8073, LBA 40-1 to 40-18.
  • Roberts, D.A., Ustin, S.L., Ogunjemiyo, S., Greenberg, J., Dobrowski,S.Z., Chen, J. and Hinckley, T.M., 2004, Spectral and structural measures of Northwest forest vegetation at leaf to landscape scales, Ecosystems, 7:545-562.
  • Sonnetag, O., Chen, J.M., Roberts, D.A., Talbot, J., Halligan, K.Q., and Govind, A., 2007, Mapping tree and shrub leaf area indices in an ombrotrophic peatland through multiple endmember spectral unmixing, Remote Sens. Environ. 109, 342-360.
  • Settle, J.J. and Drake, N.A., 1993, Linear mixing and the estimation of ground cover proportions, Int. J. Remote Sens., 14(6), 1159-1177.
  • Tompkins, S., Mustard J.F., Pieters, C.M., and Forsyth, D.W., 1997, Optimization of endmembers for spectral mixture analysis. Remote Sens. Environ. 59, 472-489.
  • Ustin, S.L., Roberts, D.A., Gamon, J.A., Asner, G.P., and Green, R.O., 2004, Using Imaging Spectroscopy to Study Ecosystem Processes and Properties, Bioscience, 54(6) 523-534.