Endmember selection for multiple endmember spectral mixture analysis using endmember average RMSE

Remote Sensing of Environment

Volumn 87, Issue 2-3, 2003, Pages 123-135

  Dennison, Philip E ^a   Roberts, Dar A ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Endmember selection; Imaging spectroscopy; Spectral mixture analysis; Vegetation mapping

Indexed keywords

ECOSYSTEMS; ERROR ANALYSIS; INFRARED IMAGING; SOILS; SPECTRUM ANALYSIS; VEGETATION;

ENDMEMBER AVERAGE ROOT (EAR) MEAN SQUARE ERRORS; MULTIPLE ENDMEMBER SPECTRAL MIXTURE ANALYSIS (MESMA); SPECTRAL LIBRARY;

MIXTURES;

AVIRIS; IMAGE ANALYSIS; LAND CLASSIFICATION; PIXEL; SPECTRAL ANALYSIS; VEGETATION MAPPING;

EID: 2942522160     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0034-4257(03)00135-4     Document Type: Article

References (53)

1. Adams, J. B., Smith, M. O., & Gillespie, A. R. (1993). Imaging spectroscopy: Interpretation based on spectral mixture analysis. In C. M. Pieters, P. A. J. Englert (Eds.), Remote geochemical analysis: Elemental and mineralogical composition (pp. 145-166). Cambridge, England: Press Syndicate of Univ. of Cambridge.
2. Adams, J. B., Smith, M. O., & Johnson, P. E. (1986). Spectral mixture modeling: A new analysis of rock and soil types at the Viking Lander I site. Journal of Geophysical Research, 91, 8098-8812.
3. Asner, G. P., Bateson, C. A., Privette, J. L., Elsaleous, N., & Wessman, C. A. (1998). Estimating vegetation structural effects on carbon uptake using satellite data fusion and inverse modeling. Journal of Geophysical Research - Atmospheres, 103, 28839-28853.
4. Bateson, A., & Curtiss, B. (1996). A method for manual endmember selection and spectral unmixing. Remote Sensing of Environment, 55, 229-243.
5. Bateson, C. A., Asner, G. P., & Wessman, C. A. (2000). Endmember bundles: A new approach to incorporating endmember variability into spectral mixture analysis. IEEE Transactions on Geoscience and Remote Sensing, 38, 1083-1094.
6. Bell, J. F., Farrand, W. H., Johnson, J. R., & Morris, R. V. (2002). Low abundance materials at the Mars Pathfinder landing site: An investigation using spectral mixture analysis and related techniques. Icarus, 158, 56-71.
7. Boardman, J. W. (1993). Automating spectral unmixing of AVIRIS data using convex geometry concepts. Summaries of the Fourth Annual JPL Airborne Geoscience Workshop (pp. 11-14). Pasadena, CA: Jet Propulsion Laboratory.
8. Boardman, J. W., Kruse, F. A., & Green, R. O. (1995). Mapping target signatures via partial unmixing of AVIRIS data. Summaries of the Fifth Annual JPL Airborne Geoscience Workshop (pp. 23-26). Pasadena, CA: Jet Propulsion Laboratory.
9. Borel, C. C., & Gerstl, S. A. W. (1994). Nonlinear spectral mixing models for vegetative and soil surfaces. Remote Sensing of Environment, 47, 403-416.
10. Church, R., & Revelle, C. (1974). The maximal covering location problem. Papers of the Regional Science Association, 32, 101-118.
11. Cohen, J. (1960). A coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20, 37-46.
12. Congalton, R. (1991). A review of assessment the accuracy of classifications of remotely sensed data. Remote Sensing of Environment, 37, 35-46.
13. Crist, E. P. (1985). ATM tasseled cap equivalent transformation for reflectance factor data. Remote Sensing of Environment, 17, 301-306.
14. Cross, A. M., Settle, J. J., Drake, N. A., & Paivinen, R. T. M. (1991). Subpixel measurement of tropical forest cover using AVHRR data. International Journal of Remote Sensing, 12, 1119-1129.
15. Dennison, P. E., Roberts, D. A., & Regelbrugge, J. (2000). Characterizing chaparral fuels using combined hyperspectral and synthetic aperture radar. Proceedings of the Ninth JPL Airborne Earth Science Workshop (pp. 119-124). Pasadena, CA: Jet Propulsion Laboratory.
16. Elmore, A. J., Mustard, J. F., Manning, S. J., & Lobell, D. B. (2000). Quantifying vegetation change in semiarid environments: Precision and accuracy of spectral mixture analysis and the normalized difference vegetation index. Remote Sensing of Environment, 73, 87-102.
17. Garcia, M., & Ustin, S. L. (2001). Detection of interannual vegetation responses to climatic variability using AVIRIS data in a coastal savanna in California. IEEE Transactions on Geoscience and Remote Sensing, 39, 1480-1490.
18. Gillespie, A. R., Smith, M. O., Adams, J. B., Willis, S. C., Fischer, A. F., & Sabol, D. E. (1990). Interpretation of residual images: spectral mixture analysis of AVIRIS images, Owens Valley, California. Proceedings of the Second Airborne Imaging Spectrometer Data Analysis Conference (pp. 243-270). Pasadena, CA: Jet Propulsion Laboratory.
19. Golub, G. H., & Van Loan, C. F. (1989). Matrix computations. Baltimore, MD: Johns Hopkins Univ. Press.
20. Green, R., Conel, J., & Roberts, D. (1993). Estimation of aerosol optical depth and additional atmospheric parameters for the calculation of apparent surface reflectance from radiance as measured by the Airborne Visible-Infrared Imaging Spectrometer (AVIRIS). Summaries of the Fourth Annual JPL Airborne Geosciences Workshop (pp. 73-76). Pasadena, CA: Jet Propulsion Laboratory.
21. Green, R. O., Eastwood, M. L., Sarture, C. M., Chrien, T. G., Aronsson, M., Chippendale, B. J., Faust, J. A., Pavri, B. E., Chovit, C. J., Solis, M., Olah, M. R., & Williams, O. (1998). Imaging spectroscopy and the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). Remote Sensing of Environment, 65, 227-248.
22. Haboudane, D., Bonn, F., Royer, A., Sommer, S., & Mehl, W. (2002). Land degradation and erosion risk mapping by fusion of spectrally-based information and digital geomorphometric attributes. International Journal of Remote Sensing, 23, 3795-3820.
23. Hall, F. G., Shimabukuro, Y. E., & Huemmrich, K. F. (1995). Remote sensing of forest biophysical structure using mixture decomposition and geometric reflectance models. Ecological Applications, 5, 993-1013.
24. Halligan, K. Q. (2002). Multiple endmember spectral mixture analysis of vegetation in the northeast corner of Yellowstone national park. Master's Thesis, University of California Santa Barbara.
25. Huete, A. R. (1986). Separation of soil-plant spectral mixtures by factor analysis. Remote Sensing of Environment, 19, 237-251.
26. Kameyama, S., Yamagata, Y., Nakamura, F., & Kaneko, M. (2001). Development of WTI and turbidity estimation model using SMA - application to Kushiro Mire, eastern Hokkaido, Japan. Remote Sensing of Environment, 77, 1-9.
27. Kauth, R. J., & Thomas, G. S. (1976). The tasseled cap - a graphic description of the spectral-temporal development of agricultural crops as seen by Landsat. Proceedings of the symposium on machine processing of remotely sensed data (pp. 4B41-4B51). West Lafayette, IN: Purdue University.
28. Li, L., & Mustard, J. F. (2003). Highland contamination in lunar mare soils: Improved mapping with multiple endmember spectral mixture analysis (MESMA). Journal of Geophysical Research - Planets, 108 (E6), 7-1 to 7-14.
29. Maselli, F. (1998). Multiclass spectral decomposition of remotely sensed scenes by selective pixel unmixing. IEEE Transactions on Geoscience and Remote Sensing, 36, 1809-1820.
30. Metternicht, G. I., & Fermont, A. (1998). Estimating erosion surface features by linear mixture modeling. Remote Sensing of Environment, 64, 254-265.
31. Mustard, J. F., & Head, J. W. (1996). Buried stratigraphic relationships along the southwestern shores of Oceanus Procellarum - implications for early lunar volcanism. Journal of Geophysical Research - Planets, 101, 18913-18925.
32. Okin, G. S., Roberts, D. A., Murray, B., & Okin, W. J. (2001). Practical limits on hyperspectral vegetation discrimination in arid and semiarid environments. Remote Sensing of Environment, 77, 212-225.
33. Painter, T. H., Dozier, J., Roberts, D. A., Davis, R. E., & Green, R. O. (2003). Retrieval of subpixel snow-covered area and grain size from imaging spectrometer data. Remote Sensing of Environment, 85, 64-77.
34. Painter, T. H., Roberts, D. A., Green, R. O., & Dozier, J. (1998). The effect of grain size on spectral mixture analysis of snow-covered area from AVIRIS data. Remote Sensing of Environment, 65, 320-332.
35. Peddle, D. R., Brunke, S. P., & Hall, F. G. (2001). A comparison of spectral mixture analysis and ten vegetation indices for estimating boreal forest biophysical information from airborne data. Canadian Journal of Remote Sensing, 27, 627-635.
36. Peddle, D. R., Hall, F. G., & LeDrew, E. F. (1999). Spectral mixture analysis and geometric-optical reflectance modeling of boreal forest biophysical structure. Remote Sensing of Environment, 67, 288-297.
37. Phinn, S., Stanford, M., Scarth, P., Murray, A. T., & Shyy, P. T. (2002). Monitoring the composition of urban environments based on the vegetation-impervious surface_soil (VIS) model by subpixel analysis techniques. International Journal of Remote Sensing, 23, 4131-4153.
38. Pinet, P. C., Shevchenko, V. V., Chevrel, S. D., Daydou, Y., & Rosemberg, C. (2000). Local and regional lunar regolith characteristics at Reiner Gamma Formation: Optical and spectroscopic properties from Clementine and Earth-based data. Journal of Geophysical Research - Planets, 105, 9457-9475.
39. Ray, T. W., & Murray, B. C. (1996). Nonlinear spectral mixing in desert vegetation. Remote Sensing of Environment, 55, 59-64.
40. Riano, D., Chuvieco, E., Ustin, S., Zomer, R., Dennison, P., Roberts, D., & Salas, J. (2002). Assessment of vegetation regeneration after fire through multitemporal analysis of AVIRIS images in the Santa Monica Mountains. Remote Sensing of Environment, 79, 60-71.
41. Roberts, D. A., Dennison, P. E., Gardner, M., Hetzel, Y. L., Ustin, S. L., & Lee, C. (2003). Evaluation of the potential of Hyperion for fire danger assessment by comparison to the airborne visible infrared imaging spectrometer. IEEE Transactions on Geoscience and Remote Sensing (in press).
42. Roberts, D. A., Dennison, P. E., Ustin, S. L., Reith, E., & Morais, M. E. (1999). Development of a regionally specific library for the Santa Monica Mountains using high resolution AVIRIS data. Proceedings of the Eight AVIRIS Earth Science Workshop (pp. 349-354). Pasadena, CA: Jet Propulsion Laboratory.
43. Roberts, D. A., Gardner, M., Church, R., Ustin, S., Scheer, G., & Green, R. O. (1998). Mapping chaparral in the Santa Monica Mountains using multiple endmember spectral mixture models. Remote Sensing of Environment, 65, 267-279.
44. Roberts, D. A., Gardner, M., Church, R., Ustin, S. L., & Green, R. O. (1997). Optimum strategies for mapping vegetation using multiple endmember spectral mixture models. Imaging spectrometry III (pp. 108-119). Bellingham, WA: SPIE Optical Engineering Press.
45. Roberts, D. A., Green, R. O., & Adams, J. B. (1997). Temporal and spatial patterns in vegetation and atmospheric properties from AVIRIS. Remote Sensing of Environment, 62, 223-240.
46. Roberts, D. A., Numata, I., Holmes, K., Batista, G., Krug, T., Monteiro, A., Powell, B., & Chadwick, O. A. (2002). Large area mapping of landcover change in Rondonia using multitemporal spectral mixture analysis and decision tree classifiers. Journal of Geophysical Research - Atmospheres, 107, 8073.
47. Roberts, D. A., Smith, M. O., & Adams, J. B. (1993). Green vegetation nonphotosynthetic vegetation and soils in AVIRIS data. Remote Sensing of Environment, 44, 255-269.
48. Rogan, J., Franklin, J., & Roberts, D. A. (2002). A comparison of methods for monitoring multitemporal vegetation change using Thematic Mapper imagery. Remote Sensing of Environment, 80, 143-156.
49. Small, C. (2001). Multiresolution analysis of urban reflectance. Remote sensing data fusion over urban areas, IEEE/ISPRS Joint Workshop 2001 IEEE, Rome, Italy (pp. 15-19).
50. Small, C. (2002). Multitemporal analysis of urban reflectance. Remote Sensing of Environment, 81, 427-442.
51. Smith, M. O., Johnson, P. E., & Adams, J. B. (1985). Quantitative determination of mineral types and abundances from reflectance spectra using principal components analysis. Journal of Geophysical Research, 90, C797-C804.
52. Theseira, M. A., Thomas, G., & Sannier, C. A. D. (2002). An evaluation of spectral mixture modelling applied to a semi-arid environment. International Journal of Remote Sensing, 23, 687-700.
53. Tompkins, S., Mustard, J. F., Pieters, C. M., & Forsyth, D. W. (1997). Optimization of endmembers for spectral mixture analysis. Remote Sensing of Environment, 59, 472-489.