Generalization of subpixel analysis for hyperspectral data with flexibility in spectral similarity measures

IEEE Transactions on Geoscience and Remote Sensing

Volumn 47, Issue 7, 2009, Pages 2165-2171

  Chen, Jin ^a   Jia, Xiuping ^b   Yang, Wei ^c   Matsushita, Bunkei ^c  

^a BEIJING NORMAL UNIVERSITY   (China)

^b UNIVERSITY OF NEW SOUTH WALES   (Australia)

^c UNIVERSITY OF TSUKUBA   (Japan)

Author keywords

Constrained nonlinear optimization; Sequential quadratic optimization; Spectral mixture analysis; Spectrum matching

Indexed keywords

BEST MATCH; CONSTRAINED LEAST SQUARES METHOD; CONSTRAINED NONLINEAR OPTIMIZATION; DISTANCE MEASURE; ENDMEMBERS; EUCLIDEAN; EUCLIDEAN DISTANCE MEASURE; HYPERION; HYPERSPECTRAL DATA; LINEAR SPECTRAL MIXTURE MODEL; NON-LINEAR OPTIMIZATION PROBLEMS; PERFORMANCE COMPARISON; SEQUENTIAL QUADRATIC OPTIMIZATION; SEQUENTIAL QUADRATIC PROGRAMMING; SIMILARITY MEASURE; SPECTRAL ANGLE MAPPING; SPECTRAL CORRELATION; SPECTRAL INFORMATION DIVERGENCES; SPECTRAL MATCHING; SPECTRAL MIXTURE ANALYSIS; SPECTRAL SIMILARITY; SPECTRAL UNMIXING; SPECTRUM MATCHING; SUB-PIXEL ANALYSIS; SUB-PIXEL MAPPING; UNMIXING; WEIGHTED SUM;

FORESTRY; MIXTURES; NONLINEAR ANALYSIS; PHOTOMAPPING; QUADRATIC PROGRAMMING; SPECTRUM ANALYSIS;

CONSTRAINED OPTIMIZATION;

COMPARATIVE STUDY; IMAGE ANALYSIS; MAPPING METHOD; MEASUREMENT METHOD; MODELING; OPTIMIZATION; PERFORMANCE ASSESSMENT; PIXEL;

HYPERION;

EID: 67651166641     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2008.2011432     Document Type: Article

References (21)

1. J. B. Adams, M. O. Smith, and P. E. Johnson, "Spectral mixture modeling: A new analysis of rock and soil types at the Viking Lander I site," J. Geophys. Res., vol. 91, pp. 8098-8112, Jul. 1985.
2. P. M. Atkinson, M. E. J. Cutler, and H. Lewis, "Mapping sub-pixel proportional land cover with AVHRR imagery," Int. J. Remote Sens., vol. 18, no. 4, pp. 917-935, Mar. 1997.
3. J. Ju, E. D. Kolaczyk, and S. Gopal, "Gaussian mixture discriminant analysis and sub-pixel land cover characterization in remote sensing," Remote Sens. Environ., vol. 84, no. 4, pp. 550-560, Apr. 2003.
4. C.-I. Chang, X. Zhao, M. L. G. Althouse, and J.-J. Pan, "Least squares subspace projection approach to mixed pixel classification in hyperspectral images," IEEE Trans. Geosci. Remote Sens., vol. 36, no. 3, pp. 898-912, May 1998.
5. Q. H. Weng, D. S. Lu, and J. Schubring, "Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies," Remote Sens. Environ., vol. 89, no. 4, pp. 467-483, Feb. 2004.
6. D. S. Lu and Q. H. Weng, "Spectral mixture analysis of ASTER images for examining the relationship between urban thermal features and biophysical descriptors in Indianapolis, Indiana, USA," Remote Sens. Environ., vol. 104, no. 2, pp. 157-167, Sep. 2006.
7. S. Kameyama, Y. Yamagata, F. Nakamura, and M. Kaneko, "Development of WTI and turbidity estimation model using SMA-Application to Kushiro Mire, eastern Hokkaido, Japan," Remote Sens. Environ., vol. 77, no. 1,pp. 1-9, Jul. 2001.
8. J. Rogan, J. Franklin, and D. A. Roberts, "A comparison of methods for monitoring multitemporal vegetation change using Thematic Mapper imagery," Remote Sens. Environ., vol. 80, no. 1, pp. 143-156, Apr. 2000.
9. D. Riano, E. Chuvieco, S. Ustin, R. Zomer, P. Dennison, D. Roberts, and J. Salas, "Assessment of vegetation regeneration after fire through multitemporal analysis of AVIRIS images in the Santa Monica Mountains," Remote Sens. Environ., vol. 79, no. 1, pp. 60-71, Jan. 2002.
10. D. C. Heinz and C.-I. Chang, "Fully constrained least squares linear spectral mixture analysis method for material quantification in hyperspectral imagery," IEEE Trans. Geosci. Remote Sens., vol. 39, no. 3, pp. 529-545, Mar. 2001.
11. F. A. Kruse, A. B. Lefkoff, J. W. Boardman, K. B. Heidebrecht, A. T. Shapiro, P. J. Barloon, and A. F. H. Goetz, "The spectral image processing system (SIPS)-Interactive visualization and analysis of imaging spectrometer data," Remote Sens. Environ., vol. 44, no. 2/3, pp. 145-163, May/Jun. 1993.
12. F. van der Meer and W. Bakker, "Cross correlogram spectral matching (CCSM): Application to surface mineralogical mapping using AVIRIS data from Cuprite, Nevada," Remote Sens. Environ., vol. 61, no. 3, pp. 371-382, Sep. 1997.
13. C.-I. Chang, "An information theoretic-based approach to spectral variability, similarity and discriminability for hyperspectral image analysis," IEEE Trans. Inf. Theory, vol. 46, no. 5, pp. 1927-1932, Aug. 2000.
14. K. Schittkowski, "The nonlinear programming method of Wilson, Han, and Powell with an augmented Lagrangian type line search function- Part 2: An efficient implementation with linear least squares subproblems," Numer. Math., vol. 38, no. 1, pp. 115-127, Feb. 1981.
15. G. C. Zhang, W. J. Wang, H. L. Han, and L. Zhang, Computational Methods for Nonlinear Optimization. Beijing, China: Higher Educ., 2005. (in Chinese).
16. N. S. Bazaraa and C. M. Shetty, Nonlinear Programming: Theory and Algorithms. New York: Wiley, 1997.
17. J. Belnap, "The world at your feet: Desert biological soil crusts," Front. Ecol. Environ., vol. 1, no. 5, pp. 181-189, 2003.
18. J. Chen, M. Y. Zhang, L. Wang, H. Shimazaki, and M. Tamura, "A new index for mapping lichen-dominated biological soil crusts in desert areas," Remote Sens. Environ., vol. 96, no. 2, pp. 165-175, May 2005.
19. B. Datt, T. R. McVicar, T. G. van Niel, D. L. B. Jupp, and J. S. Pearlman, "Preprocessing EO-1 Hyperion hyperspectral data to support the application of agricultural indexes," IEEE Trans. Geosci. Remote Sens., vol. 41, no. 6, pp. 1246-1259, Jun. 2003.
20. R. G. Congalton, "A review of assessing the accuracy of classifications of remotely sensed data," Remote Sens. Environ., vol. 37, no. 1, pp. 35-46, Jul. 1991.
21. F. van der Meer, "The effectiveness of spectral similarity measures for the analysis of hyperspectral imagery," Int. J. Appl. Earth Observ. Geoinf., vol. 8, no. 1, pp. 3-17, Jan. 2006.