Endmember search and proportion estimates from airborne hyperspectral surveys

References

• Acito, N., M. Diani, and G. Corsini. 2009. “A New Algorithm for Robust Estimation of the Signal Subspace in Hyperspectral Images in the Presence of Rare Signal Components.” IEEE Transactions on Geoscience and Remote Sensing 47 (11): 3844–3856. doi:10.1109/TGRS.2009.2021764.
   Web of Science ®Google Scholar
• Akaike, H. 1973. “Information Theory and an Extension of the Maximum Likelihood Principle.” In 2nd International Symposium on Information Theory, Tsahkadsor, eds B. N. Petrov and F. Csáki, 267–281. Armenia, USSR, Budapest: Akadémiai Kiadó. 2–8 September 1971.
   Google Scholar
• Berman, M., L. Bischof, and J. Huntington. 1999. “Algorithms and Software for the Automated Identification of Minerals Using Field Spectra or Hyperspectral Imagery.” In Proceedings of the 13th International Conference on Applied Geologic Remote Sensing 1: 222–232, Vancouver, 1–3 March.
   Google Scholar
• Berman, M., H. Kiiveri, R. Lagerstrom, A. Ernst, R. Dunne, and J. Huntington. 2004. “ICE: A Statistical Approach to Identifying Endmembers.” IEEE Transactions on Geoscience and Remote Sensing 42: 2085–2095. doi:10.1109/TGRS.2004.835299.
   Web of Science ®Google Scholar
• Berman, M., T. Traylen, and P. Caccetta. 2009. “Towards Seamless Hyperspectral Mapping and Monitoring on a Continental Scale.” Paper presented at the International Statistical Institute (ISI) Invited Paper Meetings 31, Durban, 16–22 August.
   Google Scholar
• Bioucas-Dias, J., and J. Nascimento. 2008. “Hyperspectral Subspace Identification.” IEEE Transactions on Geoscience and Remote Sensing 46 (8): 2435–2445. doi:10.1109/TGRS.2008.918089.
   Web of Science ®Google Scholar
• Cawse-Nicholson, K., S. Damelin, A. Robin, and M. Sears. 2013. “Determining the Intrinsic Dimension of a Hyperspectral Image Using Random Matrix Theory.” IEEE Transactions on Image Processing 22 (4): 1301–1310. doi:10.1109/TIP.2012.2227765.
   PubMed Web of Science ®Google Scholar
• Chang, C., and Q. Du. 2004. “Estimation of Number of Spectrally Distinct Signal Sources in Hyperspectral Imagery.” IEEE Transaction on Geoscience and Remote Sensing 42 (3): 608–619. doi:10.1109/TGRS.2003.819189.
   Web of Science ®Google Scholar
• Cocks, T., R. Jenssen, A. Stewart, I. Wilson, and T. Shields. 1998. The HyMap Airborne Hyperspectral Sensor: The System, Calibration and Performance. Proceedings of the 1st European Association of Remote Sensing Laboratories (Earsel) Workshop on Imaging Spectroscopy, Zurich. 6–8 October, edited by. M. Schaepman, D. Schläpfer, and K. I. Itten 37–42.
   Google Scholar
• Collings, S., and P. Caccetta. 2011. “On the Generation of Broad-Scale Hyperspectral Ground Reflectance Mosaics from Aerial and Ground-Based Observations.” International Journal of Image and Data Fusion 2 (3): 237–253. doi:10.1080/19479832.2010.551523.
   Google Scholar
• Collings, S., P. Caccetta, N. Campbell, and X. Wu. 2010. “Techniques for BRDF Correction of Hyperspectral Mosaics.” IEEE Transactions on Geoscience and Remote Sensing 48 (10): 3733–3746. doi:10.1109/TGRS.2010.2048574.
   Web of Science ®Google Scholar
• Green, A. A., M. Berman, P. Switzer, and M. D. Craig. 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. doi:10.1109/36.3001.
   Web of Science ®Google Scholar
• Guerschman, J. P., M. J. Hill, L. J. Renzullo, D. J. Barrett, A. S. Marks, and E. J. Botha. 2009. “Estimating Fractional Cover of Photosynthetic Vegetation, Non-Photosynthetic Vegetation and Bare Soil in the Australian Tropical Savanna Region Upscaling the EO-1 Hyperion and MODIS Sensors.” Remote Sensing of Environment 13 (5): 928–945. doi:10.1016/j.rse.2009.01.006.
   Web of Science ®Google Scholar
• Hewson, R. D., T. J. Cudahy, J. Drake-Brockman, J. Meyers, and A. Hashemi. 2006. “Mapping Geology Associated with Manganese Mineralisation Using Spectral Sensing Techniques at Woodie Woodie, East Pilbara.” Exploration Geophysics 37: 389–400. doi:10.1071/EG06389.
   Web of Science ®Google Scholar
• Hubbard, B. E., and J. K. Crowley. 2005. “Mineral Mapping on the Chilean-Bolivian Altiplano Using Co-Orbital ALI, ASTER and Hyperion Imagery: Data Dimensionality Issues and Solutions.” Remote Sensing of Environment 99 (1–2): 173–186. doi:10.1016/j.rse.2005.04.027.
   Web of Science ®Google Scholar
• Hurvich, C. M., and C.-L. Tsai. 1989. “Regression and Time Series Model Selection in Small Samples.” Biometrika 76: 297–307. doi:10.1093/biomet/76.2.297.
   Web of Science ®Google Scholar
• Kobayashi, C., O. Kashimura, T. Maruyama, M. Oyanagi, I. C. Lau, T. Cudahy, B. Wheaton, and D. Carter. 2010. “Method to Reduce Green and Dry Vegetation Effects for Soil Mapping Using Hyperspectral Data.” In International Archives of the Photogrammetry, Remote Sensing and Spatial Information Science, edited by K. Kajiwara, K. Muramatsu, N. Soyama, T. Endo, A. Ono, and S. Akatsuka, Volume XXXVIII, Part 8, 448–453. Kyoto Japan.
   Google Scholar
• Kokaly, R. F., R. N. Clark, G. A. Swayze, K. E. Livo, T. M. Hoefen, N. C. Pearson, R. A. Wise, et al. 2017. USGS Spectral Library Version 7: U.S. Geological Survey Data Series 1035. Accessed 01 July 2017. https://doi.org/10.3133/ds1035.
   Google Scholar
• Kruse, F. A., J. W. Boardman, and J. F. Huntington. 2003. “Comparison of Airborne Hyperspectral Data and EO-1 Hyperion for Mineral Mapping.” IEEE Transactions on Geoscience and Remote Sensing 41 (6): 1388–1400. doi:10.1109/TGRS.2003.812908.
   Web of Science ®Google Scholar
• Miao, L., and H. Qi. 2007. “Endmember Extraction from Highly Mixed Data Using Minimum Volume Constrained Nonnegative Matrix Factorisation.” IEEE Transactions on Geoscience and Remote Sensing 45 (3): 765–777. doi:10.1109/TGRS.2006.888466.
   Web of Science ®Google Scholar
• Roberts, D., M. Gardner, R. Church, S. Ustin, G. Scheer, and R. Green. 1998. “Mapping Chaparral in the Santa Monica Mountains Using Multiple Endmember Spectral Mixture Models.” Remote Sensing of Environment 65: 267–279. doi:10.1016/S0034-4257(98)00037-6.
   Web of Science ®Google Scholar
• Robichaud, P. R., S. A. Lewis, D. Y. M. Laes, A. T. Hudak, R. F. Kokaly, and J. A. Zamudio. 2007. “Postfire Soil Burn Severity Mapping with Hyperspectral Image Unmixing.” Remote Sensing of Environment 108: 467–480. doi:10.1016/j.rse.2006.11.027.
   Web of Science ®Google Scholar
• Rodger, A. 2011. “SODA: A New Method of In-Scene Atmospheric Water Vapor Estimation and Post-Flight Spectral Recalibration for Hyperspectral Sensors - Application to the HyMap Sensor at Two Locations.” Remote Sensing of Environment 115 (2): 536–547. doi:10.1016/j.rse.2010.09.022.
   Web of Science ®Google Scholar
• Roger, R. E., and J. F. Arnold. 1996. “Reliably Estimating the Noise in AVIRIS Hyperspectral Images.” International Journal of Remote Sensing 17 (10): 1951–1962. doi:10.1080/01431169608948750.
   Web of Science ®Google Scholar
• Schwarz, G. E. 1978. Estimating the Dimension of a Model. Annals of Statistics 6 2: 461–464. MR 468014. doi:10.1214/aos/1176344136.
   Web of Science ®Google Scholar
• Zhang, J., B. Rivard, and A. Sanchez-Azofeifa. 2005. “Spectral Unmixing of Normalised Reflectance Data for the Deconvolution of Lichen and Rock Mixtures.” Remote Sensing of Environment 95: 57–66. doi:10.1016/j.rse.2004.11.019.
   Web of Science ®Google Scholar