The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008 
land-cover change in the Brazilian Amazon. Remote Sensing of 
Environment, 52(2), 137-154. 
Abrams, M. (2000). The Advanced Spacebome Thermal 
Emission and Reflection Radiometer (ASTER): Data products 
for the high spatial resolution imager on NASA's Terra platform. 
International Journal ofRemote Sensing, 21, 847-859. 
Brown, M., Lewis, H. G., & Gunn, S. R. (2000). Linear spectral 
mixture models and support vector machines for remote sensing. 
IEEE Transactions on Geoscience and Remote Sensing, 38(5), 
2346-2360. 
Boardman, J.W., 1989. Inversion of imaging spectrometry data 
using singular value decomposition. In: IGARSS’ 89, 12th 
Canadian Symposium on Remote Sensing, pp. 2069 - 2072. 
Boardman, J.W., 1993. Automating spectral unmixing of 
AVIRIS data using convex geometry concepts. In: Summaries 
of the 4th Annual JPL Air-borne Geoscience Workshop, 
Pasadena, pp. 11 - 14. 
Borel, C. C., & Gerstl, S. A. W. (1994). Nonlinear spectral 
mixing models for vegetative and soil surfaces. Remote Sensing 
of Environment, 47(3),403-416. , 
Boardman, J.W., Kruse, F.A., Green, R.O., 1995. Mapping 
target signatures via partial unmixing of AVIRIS data. In: 
Summaries, Fifth JPL Airborne Earth Science Workshop, pp. 23 
-26. 
Boardman, J.W., Kruse, F.A., 1994. Automatic spectral analysis: 
a geological example using AVIRIS data, North Grapevine 
Mountain, Nevada. In: 10th Thematic Conference on Geologic 
Remote Sensing,Ann Arbor, pp. 407 - 418.Boardman, J.W., 
Kruse, F. 
Brown, M., Gunn, S. R., & Lewis, H. G. (1999). Support vector 
machines for optimal classification and spectral unmixing. 
Ecological Modelling, 120(2 - 3), 167-179. 
Charles Lchoku, Amon Kamieli. A Review of Mixture 
Modeling Techniques for Sub-Pixel Land Cover Estimation. 
Remote Sensing Rewiews,1996,13(l):161~186 
Chabrillat, S., Pinet, P.C., Ceuleneer, G., Johnson, P.E., 
Mustard, J.F.,2000. Ronda peridotite massif: methodology for 
its geological mapping and litho logical discrimination from 
airborne hyperspectral data .International Journal of Remote 
Sensing ,21,2363-2388. 
Carlson T N, Ripley D A. On the relation between NDVI, 
fractional vegetation cover, and leaf area index. Remote Sensing 
of Environment ,1997,62 ( 3):241-252. 
Dengsheng Lu, Qihao Weng.(2006) Spectral mixture analysis of 
ASTER images for examining the relationship between urban 
thermal features and biophysical descriptors in Indianapolis, 
Indiana, USA. Remote Sensing of Environment, 104,157 - 167. 
Fang Qiu, Mohamed Abdelsalam, Pathik Thakkar.(2006) 
Spectral analysis of ASTER data covering part of the 
Neoproterozoic Allaqi-Heiani suture, Southern Egypt. Journal 
of African Earth Sciences, 44,169-180. 
Fujisada, H. (1998). ASTER level-1 data processing algorithm. 
IEEE Transactions on Geoscience and Remote Sensing, 36, 
1101-1112. 
Gong, P., Miller, J. R., & Spanner, M. (1994). Forest canopy 
closure from classification and spectral unmixing of scene 
components—Multisensor evaluation of an open canopy. IEEE 
Transactions on Geoscience and Remote Sensing, 32(5), 
1067-1080. 
Green, A.A., Berman, M., Switzer, P., Craig, M.D., 1988. A 
transformation for ordering multispectral data in terms of image 
quality with implications for noise removal. IEEE Transactions 
on Geoscience and Remote Sensing 26, 65 - 74. 
GarciaHaro, F. J., Gilabert, M. A., & Melia, J. (1996). Linear 
spectral mixture modelling to estimate vegetation amount from 
optical spectral data. International Journal of Remote Sensing, 
17(17), 3373-3400. 
lchoku, C., & Kamieli, A. (1996). A review of mixture 
modeling techniques for sub-pixel land cover estimation. 
Remote Sensing Reviews, 13, 161-186. 
lchoku, C., & Karnieli, A. (1996). A review of mixture 
modeling techniques for sub-pixel land cover estimation. 
Remote Sensing Reviews, 13, 161-186. 
Ju, J. C., Kolaczyk, E. D., & Gopal, S. (2003). Gaussian 
mixture discriminant analysis and sub-pixel land cover 
characterization in remote sensing. Remote Sensing of 
Environment, 84(4), 550-560. 
Keshava, N., & Mustard, J. F. (2002). Spectral unmixing. IEEE 
Signal Processing Magazine, 19(1), 44-57. 
Kahle, A. B., Palluconi, F. D., Hook, S. J., Realmuto, V. J., and 
Bothwell, G. (1991).The Advanced Spacebome Thermal 
Emission and Reflectance Radiometer (ASTER). Int. J. Imaging 
Systems Tech. 3,144-156. 
Klaus I. Itten, Peter Meyer.(1993). Geometric and 
Radiometric Correction of TM Data of Mountainous Forested 
Areas, IEEE Transactions on Geoscience and Remote Sensing, 
31(4):764-770. 
Li, J. (2004). Wavelet-based feature extraction for improved 
endmember abundance estimation in linear unmixing of 
hyperspectral signals. IEEE Transactions on Geoscience and 
Remote Sensing, 42(3), 644-649. 
McDaniel K C, Haas R H. Assessing mesquite-grass 
vegetation condition from Landsat. Photogrammetric 
Engineering and Remote Sensing, 1982 (48):441—450. 
Meyer, P., Itten, K.I., Kellenberger, T., Sandmeier, S. and 
Sandmeier, R., 1993,Radiometric Corrections of 
Topographically Induced Effects on Landsat TM Data in an 
Alpine Environment, ISPRS Journal of Photogrammetry and 
Remote Sensing, 48, 17-28. 
Neville, R. A., Levesque, J., Staenz, K., Nadeau, C., Hauff, P., 
& Borstad, G. A. (2003). Spectral unmixing of hyperspectral 
imagery for mineral exploration: Comparison of results from 
SFSI and AVIRIS. Canadian Journal ofRemote Sensing, 29(1), 
99-110. 
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