Progress in hyperspectral remote sensing science and technology in China over the past three decades

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Volumn 7, Issue 1, 2014, Pages 70-91

  Tong, Qingxi ^a   Xue, Yongqi ^b   Zhang, Lifu ^a  

^a INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

^b SHANGHAI INSTITUTE OF TECHNICAL PHYSICS   (China)

Author keywords

Hyperspectral remote sensing; Imaging spectrometry; Remote sensing applications; Remote sensing technology

Indexed keywords

AIRBORNE IMAGING SPECTROMETERS; HYPERSPECTRAL IMAGE PROCESSING; HYPERSPECTRAL IMAGING SYSTEMS; HYPERSPECTRAL REMOTE SENSING; IMAGE PROCESSING TECHNIQUE; IMAGING SPECTROMETRY; REMOTE SENSING APPLICATIONS; REMOTE SENSING TECHNOLOGY;

DESIGN; IMAGE PROCESSING; MINERAL EXPLORATION; SPECTROMETERS; SPECTROSCOPY;

REMOTE SENSING;

IMAGE PROCESSING; REMOTE SENSING; SCIENCE AND TECHNOLOGY; SPECTROMETRY; TECHNOLOGICAL DEVELOPMENT;

CHINA;

EID: 84891742004     PISSN: 19391404     EISSN: 21511535     Source Type: Journal    
DOI: 10.1109/JSTARS.2013.2267204     Document Type: Article

References (158)

1. A. F. H. Goetz, G. Vane, J.E. Solomon, andB. N. Rock, "Imaging spectrometry for earth remote-sensing, " Science, vol. 228, pp. 1147-1153, 1985.
2. A. F. H. Goetz, "Hyperspectral imaging and quantitative remote sensing, " Land Satellite Information in the Next Decade, pp. E1-E10, 180, 1995.
3. A. F. H. Goetz, "Three decades of hyperspectral remote sensing of the earth: A personal view, " Remote Sens. Environ., vol. 113, pp. S5-S16, 2009.
4. C. Chang, Hyperspectral Imaging: Techniques for Spectral Detection and Classification. New York, NY, USA: Springer, 2003.
5. K. L. Castro-Esau, G. A. Sanchez-Azofeifa, B. Rivard, S. J. Wright, and M. Quesada, "Variability in leaf optical properties of Mesoamerican trees and the potential for species classification, " Am. J. Botany, vol. 93, pp. 517-530, Apr. 2006.
6. Y. B. Cheng, S. L. Ustin, D. Riano, and V. C. Vanderbilt, "Water content estimation from hyperspectral images and MODIS indexes in Southeastern Arizona, " Remote Sens. Environ., vol. 112, pp. 363-374, Feb. 15, 2008.
7. A. Plaza, J. A. Benediktsson, J.W. Boardman, J. Brazile, L. Bruzzone, G. Camps-Valls, J. Chanussot, M. Fauvel, P. Gamba, A. Gualtieri, M. Marconcini, J. C. Tilton, and G. Trianni, "Recent advances in techniques for hyperspectral image processing, " Remote Sens. Environ., vol. 113, pp. S110-S122, Sep. 2009.
8. Q. Tong, Y. Xue, J. Wang, L. Zhang, J. Fang, Y. Yang, X. Liu, H. Qi, L. Zheng, and C. Huang, "Development and application of the field imaging spectrometer system, " J. Remote Sens., vol. 14, pp. 409-422, 2010.
9. L. Zhang, C. Huang, T. Wu, F. Zhang, and Q. Tong, "Laboratory calibration of a field imaging spectrometer system, " Sensors, vol. 11, pp. 2408-2425, 2011.
10. J. Wang and Y. Xue, "Airborne imaging spectrometers developed in China, " in SPIE, Beijing, China, 1998.
11. B. Liu, J. Y. Fang, X. Liu, L. F. Zhang, B. Zhang, and Q. X. Tong, "Research on crop-weed discrimination using a field imaging spectrometer, " Spectroscopy and Spectral Analysis, vol. 30, pp. 1830-1833, Jul. 2010.
12. C. Huang, L. Zhang, X. Zhang, L. Zheng, and Q. Tong, "Study on discrimination of varieties of milk based on FISS imaging spectral data, " Spectroscopy and Spectral Analysis, vol. 31, pp. 214-218, Jan. 2011.
13. C. Huang, L. Zhang, J. Fang, and Q. Tong, "A radiometric calibration model for the field imaging spectrometer system, " IEEE Trans. Geosci. Remote Sens., vol. 51, pp. 2465-2475, 2013.
14. J. S. Pearlman, P. S. Barry, C. C. Segal, J. Shepanski, D. Beiso, and S. L. Carman, "Hyperion, a space-based imaging spectrometer, " IEEE Trans. Geosci. Remote Sens., vol. 41, pp. 1160-1173, 2003.
15. Z. Mao, J. Chen, and X. He, "Evaluation of CMODIS-measured radiance by a hyperspectral model, " Int. J. Remote Sens., vol. 31, pp. 5179-5198, 2010.
16. Y. Wu, B. Xue, B. Zhao, P. Lucey, J. Chen, X. Xu, C. Li, and Z. Ouyang, "Global estimates of lunar iron and titanium contents from the Chang'E-1 IIM data, " J. Geophys. Res., vol. 117, 2012.
17. A. Cheriyadat, "Limitations of principal component analysis for dimensionality- reduction for classification of hyperspectral data, " Mississippi State University, MS, USA, pp. 31-56, 2003.
18. F. A. Mianji and Y. Zhang, "Robust hyperspectral classification using relevance vector machine, " IEEE Trans. Geosci. Remote Sens., vol. 49, pp. 2100-2112, Jun. 2011.
19. N. Acito, M. Diani, and G. Corsini, "Hyperspectral signal subspace identification in the presence of rare signal components, " IEEE Trans. Geosci. Remote Sens., vol. 48, pp. 1940-1954, Apr. 2010.
20. Q. Tong, B. Zhang, and L. Zheng, Hyperspectral Remote Sensing-Principles, Techniques and Applications. Beijing, China: Higher Education Press, 2006.
21. C.-I. Chang, Ed., Hyperspectral Data Exploitation: Theory and Applications. New York, NY, USA: Wiley-Interscience, 2007.
22. N. Keshava and J. F. Mustard, "Spectral unmixing, " IEEE Signal Process. Mag., vol. 19, pp. 44-57, 2002. (Pubitemid 34237207)
23. C. Quintano, A. Fernández-Manso, Y. E. Shimabukuro, and G. Pereira, "Spectral unmixing, " Int. J. Remote Sens., vol. 33, 2012.
24. T.A. Wilson, S. K. Rogers, andM. Kabrisky, "Perceptual-based image fusion for hyperspectral data, " IEEE Trans. Geosci. Remote Sens., vol. 35, pp. 1007-1017, Jul. 1997. (Pubitemid 127771140)
25. M. T. Eismann and R. C. Hardie, "Application of the stochastic mixing model to hyperspectral resolution, enhancement, " IEEE Trans. Geosci. Remote Sens., vol. 42, pp. 1924-1933, Sep. 2004.
26. R. C. Hardie, M. T. Eismann, and G. L. Wilson, "MAP estimation for hyperspectral image resolution enhancement using an auxiliary sensor, " IEEE Trans. Image Process., vol. 13, pp. 1174-1184, Sep. 2004.
27. M. T. Eismann and R. C. Hardie, "Hyperspectral resolution enhancement using high-resolution multispectral imagery with arbitrary response functions, " IEEE Trans. Geosci. Remote Sens., vol. 43, pp. 455-465, Mar. 2005. (Pubitemid 40320268)
28. N. Yokoya, T. Yairi, and A. Iwasaki, "Coupled nonnegative matrix factorization unmixing for hyperspectral and multispectral data fusion, " IEEE Trans. Geosci. Remote Sens., vol. 50, pp. 528-537, Feb. 2012.
29. S. C. Park, M. K. Park, and M. G. Kang, "Super-resolution image reconstruction: A technical overview, " IEEE Signal Process. Mag., vol. 20, pp. 21-36, May 2003.
30. Z. He and B. He, "Weight spectral angle mapper (WSAM) method for hyperspectral mineral mapping, " Spectroscopy and Spectral Analysis, vol. 31, pp. 2200-2204, 2011.
31. S. Fang and H. Gong, "Spectral similarity scale based on dynamic wighting adjustment method, " Geomatrics and Information Science of Wuhan University, vol. 31, pp. 1044-1046, 2006.
32. H. Jiao, Y. Zhong, and L. Zhang, "Artificial DNA computing-based spectral encoding and matching algorithm for hyperspectral remote sensing data, " IEEE Trans. Geosci. Remote Sens., vol. 50, pp. 4085-4104, 2012.
33. P. Du, J. Xia, W. Zhang, K. Tan, Y. Liu, and S. Liu, "Multiple classifier system for remote sensing image classification: A review, " Sensors (Basel), vol. 12, pp. 4764-92, 2012.
34. J. M. Bioucas-Dias, A. Plaza, N. Dobigeon, M. Parente, Q. Du, P. Gader, and J. Chanussot, "Hyperspectral unmixing overview: Geometrical, statistical, and sparse regression-based approaches, " IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens., vol. 5, pp. 354-379, 2012.
35. C. Small, "High spatial resolution spectral mixture analysis of urban reflectance, " Remote Sens. Environ., vol. 88, pp. 170-186, 2003. (Pubitemid 38184694)
36. X. Chen and L. Vierling, "Spectral mixture analyses of hyperspectral data acquired using a tethered balloon, " Remote Sens. Environ., vol. 103, pp. 338-350, 2006. (Pubitemid 44093660)
37. P. M. Atkinson, "Mapping sub-pixel boundaries from remotely sensed images, " Innovations in GIS, vol. 4, pp. 166-180, 1997.
38. K. J. Guilfoyle, M. L. Althouse, and C. I. Chang, "A quantitative and comparative analysis of linear and nonlinear spectral mixture models using radial basis function neural networks, " IEEE Trans. Geosci. Remote Sens., vol. 39, pp. 2314-2318, 2001. (Pubitemid 33048403)
39. K. Wu, L. Zhang, and P. Li, "A neural network method of selective endmember for pixel unmixing, " J. Remote Sens.-Beijing, vol. 11, p. 20, 2007.
40. B. Wu, L. Zhang, P. Li, and J. Zhang, "Nonlinear estimation of hyperspectral mixture pixel proportion based on kernel orthogonal subspace projection, " Advances in Neural Networks-ISNN 2006, pp. 1070-1075, 2006. (Pubitemid 44046235)
41. C. I. Chang, C. C. Wu, W. Liu, and Y. C. Ouyang, "A new growing method for simplex-based endmember extraction algorithm, " IEEE Trans. Geosci. Remote Sens., vol. 44, pp. 2804-2819, 2006.
42. M. D. Craig, "Minimum-volume transforms for remotely sensed data, " IEEE Trans. Geosci. Remote Sens., vol. 32, pp. 542-552, 1994.
43. J. M. P. Nascimento and J. M. B. Dias, "Vertex component analysis: A fast algorithm to unmix hyperspectral data, " IEEE Trans. Geosci. Remote Sens., vol. 43, pp. 898-910, 2005. (Pubitemid 40476033)
44. R. Neville, K. Staenz, T. Szeredi, J. Lefebvre, and P. Hauff, "Automatic endmember extraction from hyperspectral data for mineral exploration, " in Proc. 21st Canadian Symp. Remote Sens., 1999, pp. 21-24.
45. H. Li and L. Zhang, "A hybrid automatic endmember extraction algorithm based on a local window, " IEEE Trans. Geosci. Remote Sens., vol. 49, pp. 4223-4238, 2011.
46. J. M. Liu and J. S. Zhang, "A new maximum simplex volume method based on householder transformation for endmember extraction, " IEEE Trans. Geosci. Remote Sens., vol. 50, pp. 104-118, Jan. 2012.
47. T. H. Chan, C. Y. Chi, Y. M. Huang, and W. K. Ma, "A convex analysis-based minimum-volume enclosing simplex algorithm for hyperspectral unmixing, " IEEE Trans. Signal Process., vol. 57, pp. 4418-4432, Nov. 2009.
48. B. Zhang, X. Sun, L. Gao, and L. Yang, "Endmember extraction of hyperspectral remote sensing images based on the discrete particle swarm optimization algorithm, " IEEE Trans. Geosci. Remote Sens., vol. 49, pp. 4173-4176, 2011.
49. B. Zhang, X. Sun, L. Gao, and L. Yang, "Endmember extraction of hyperspectral remote sensing images based on the ant colony optimization (ACO) algorithm, " IEEE Trans. Geosci. Remote Sens., vol. 49, pp. 2635-2646, 2011.
50. G. Martín and A. Plaza, "Region-based spatial preprocessing for endmember extraction and spectral unmixing, " IEEEGeosci. Remote Sens. Lett., vol. 8, pp. 745-749, 2011.
51. A. Plaza, P. Martínez, R. Pérez, and J. Plaza, "Spatial/spectral endmember extraction by multidimensional morphological operations, " IEEE Trans. Geosci. Remote Sens., vol. 40, pp. 2025-2041, 2002. (Pubitemid 35458399)
52. D. Rogge, B. Rivard, J. Zhang, A. Sanchez, J. Harris, and J. Feng, "Integration of spatial-spectral information for the improved extraction of endmembers, " Remote Sens. Environ., vol. 110, pp. 287-303, 2007. (Pubitemid 47285207)
53. S. Mei, M. He, Y. Zhang, Z. Wang, and D. Feng, "Improving spatialspectral endmember extraction in the presence of anomalous ground objects, " IEEE Trans. Geosci. Remote Sens., vol. 49, pp. 4210-4222, 2011.
54. J. M. P. Nascimento and J. M. B. Dias, "Does independent component analysis play a role in unmixing hyperspectral data?, " IEEE Trans. Geosci. Remote Sens., vol. 43, pp. 175-187, 2005. (Pubitemid 40162736)
55. D. Seung and L. Lee, "Algorithms for non-negative matrix factorization, " Advances in Neural Information Processing Systems, vol. 13, pp. 556-562, 2001.
56. M. D. Iordache, J. M. Bioucas-Dias, and A. Plaza, "Sparse unmixing of hyperspectral data, " IEEE Trans. Geosci. Remote Sens., vol. 49, pp. 2014-2039, 2011.
57. D. S. Huang and J. X. Mi, "A new constrained independent component analysis method, " IEEE Trans. Neural Netw., vol. 18, pp. 1532-1535, 2007.
58. Z. L. Sun and L. Shang, "An improved constrained ICA with reference based unmixing matrix initialization, " Neurocomputing, vol. 73, pp. 1013-1017, 2010.
59. L. Miao and H. Qi, "Endmember extraction from highly mixed data usingminimumvolume constrained nonnegativematrix factorization, " IEEE Trans. Geosci. Remote Sens., vol. 45, pp. 765-777, 2007. (Pubitemid 46375748)
60. S. Jia and Y. Qian, "Constrained nonnegative matrix factorization for hyperspectral unmixing, " IEEE Trans. Geosci. Remote Sens., vol. 47, pp. 161-173, 2009.
61. K. C. M. Corresponding, L. Verbeke, E. Ducheyne, and R. De Wulf, "Using genetic algorithms in sub-pixel mapping, " Int. J. Remote Sens., vol. 24, pp. 4241-4247, 2003. (Pubitemid 37447114)
62. G. Foody, "Sharpening fuzzy classification output to refine the representation of sub-pixel land cover distribution, " Int. J. Remote Sens., vol. 19, pp. 2593-2599, 1998. (Pubitemid 28560708)
63. A. Tatem, H. Lewis, P. Atkinson, and M. S. Nixon, "Super-resolution land cover pattern prediction using a hopfield neural network, " Remote Sens. Environ., vol. 79, pp. 1-14, 2002. (Pubitemid 34050050)
64. L. Zhang, K. Wu, Y. Zhong, and P. Li, "A new sub-pixel mapping algorithm based on a BP neural network with an observation model, " Neurocomputing, vol. 71, pp. 2046-2054, 2008.
65. Y. Zhong and L. Zhang, "Remote sensing image subpixel mapping based on adaptive differential evolution, " IEEE Trans. Syst., Man, Cybern., B: Cybernetics, 2012.
66. Y. Zhong, L. Zhang, L. Pingxiang, and H. Shen, "A sub-pixel mapping algorithm based on artificial immune systems for remote sensing imagery, " in Proc. 2009 IEEE Int.Geoscience and Remote Sensing Symp., IGARSS 2009, pp. III-1007-III-1010.
67. Y. F. Zhang, S. De Backer, and P. Scheunders, "Noise-resistant wavelet-based Bayesian fusion of multispectral and hyperspectral images, " IEEE Trans. Geosci. Remote Sens., vol. 47, pp. 3834-3843, Nov. 2009.
68. Y. F. Gu, Y. Zhang, and J. P. Zhang, "Integration of spatial-spectral information for resolution enhancement in hyperspectral images, " IEEE Trans. Geosci. Remote Sens., vol. 46, pp. 1347-1358, May 2008.
69. Z. Shi, Z. An, and Z. Jiang, "Hyperspectral image fusion by the similarity measure-based variational method, " Optical Eng., vol. 50, p. 077006, 2011.
70. H. F. Shen, L. P. Zhang, B. Huang, and P. X. Li, "A MAP approach for joint motion estimation, segmentation, and super resolution, " IEEE Trans. Image Process., vol. 16, pp. 479-490, Feb. 2007. (Pubitemid 46421688)
71. X. Jiang, L. Tang, C. Wang, and C. Wang, "Spectral characteristics and feature selection of hyperspectral remote sensing data, " Int. J. Remote Sens., vol. 25, pp. 51-59, 2004. (Pubitemid 38211469)
72. S. Jia, Z. Ji, Y. Qian, and L. Shen, "Unsupervised band selection for hyperspectral imagery classification without manual band removal, " IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens, vol. 5, pp. 531-543, 2012.
73. Y. Q. Zhao, L. Zhang, and S. G. Kong, "Band-subset-based clustering and fusion for hyperspectral imagery classification, " IEEE Trans. Geosci. Remote Sens., vol. 49, pp. 747-756, 2011.
74. R. Huang and M. He, "Band selection based on feature weighting for classification of hyperspectral data, " IEEE Geosci. Remote Sens. Lett., vol. 2, pp. 156-159, 2005. (Pubitemid 40680165)
75. Y. Zhong and L. Zhang, "An adaptive artificial immune network for supervised classification of multi-/hyperspectral remote sensing imagery, " IEEE Trans. Geosci. Remote Sens., vol. 50, pp. 894-909, 2012.
76. Y. Zhong and L. Zhang, "Sub-pixel mapping algorithm based on adaptive differential evolution for remote sensing imagery, " in Proc. 2011 IEEE Int. Geoscience and Remote Sensing Symp., IGARSS 2011, pp. 1724-1727.
77. A. Plaza, J. A. Benediktsson, J.W. Boardman, J. Brazile, L. Bruzzone, G. Camps-Valls, J. Chanussot, M. Fauvel, P. Gamba, and A. Gualtieri, "Recent advances in techniques for hyperspectral image processing, " Remote Sens. Environ., vol. 113, pp. S110-S122, 2009.
78. R. Zhang and J. Ma, "Feature selection for hyperspectral data based on recursive support vector machines, " Int. J. Remote Sens., vol. 30, pp. 3669-3677, 2009.
79. X. Huang and L. Zhang, "Comparison of vector stacking, multi-SVMs fuzzy output, and multi-SVMs voting methods for multiscale VHR urban mapping, " IEEE Geosci. Remote Sens. Lett., vol. 7, pp. 261-265, 2010.
80. Y. Chen and X. Li, "Kernel-based hierarchical cluster analysis, " J. Jilin University (Earth Science Edition), vol. 40, pp. 1211-1216, 2010.
81. X. Huang and L. Zhang, "A comparative study of spatial approaches for urban mapping using hyperspectral ROSIS images over Pavia city, northern Italy, " Int. J. Remote Sens., vol. 30, pp. 3205-3221, 2009.
82. X. Huang and L. Zhang, "An adaptivemean-shift analysis approach for object extraction and classification from urban hyperspectral imagery, " IEEE Trans. Geosci. Remote Sens., vol. 46, pp. 4173-4185, 2008.
83. L. Zhang and X. Huang, "Object-oriented subspace analysis for airborne hyperspectral remote sensing imagery, " Neurocomputing, vol. 73, pp. 927-936, 2010.
84. Q. Yu, P. Gong, N. Clinton, G. Biging, M. Kelly, and D. Schirokauer, "Object-based detailed vegetation classificationwith airborne high spatial resolution remote sensing imagery, " Photogramm. Eng. Remote Sens., vol. 72, p. 799, 2006.
85. C. Zhang and Z. Xie, "Combining object-based texture measures with a neural network for vegetation mapping in the everglades from hyperspectral imagery, " Remote Sens. Environ., vol. 124, pp. 310-320, 2012.
86. Q. Tong, L. Zheng, and Y. Xue, "Development and application of hyperspectral remote sensing in China, " in Asia-Pacific Symp. Remote Sensing of the Atmosphere, Environment, and Space, 1998, pp. 2-9.
87. T. Qingxi, Z. Lanfen, J. Hao, W. Jinnian, T. Qingjiu, H. Hongfei, and Y. Jinshan, "The study for gold mineralization by thermal infrared multispectral scanner (TIMS), " J. Infrared Millim. Waves, vol. 11, pp. 249-256, 1992.
88. S. Yan, B. Zhang, Y. Zhao, L. Zheng, Q. Tong, and K. Yang, "Summarizing the technical flow and main approaches for discrimination and mapping of rocks and minerals using hyperspectral remote sensing, " Remote Sens. Technol. Applicat., vol. 19, pp. 52-63, 2004.
89. Q. Zhou, F. Gan, R. Wang, and J. Chen, "Mineral auto-identification based on hyperspectral imaging data and its application, " Remote Sensing for Land and Resources, vol. 4, pp. 28-31, 2005.
90. F. Gan and R. Wang, "The application of the hyperspectral imaging technique to geological investigation, " Remote Sensing for Land and Resources, vol. 4, pp. 14-14, 2007.
91. P. Hu, Q. Tian, and B. Yan, "The application of hyperspectral remote sensing to the identification of hydrocarbon alteration minerals in QAIDAM basin, " Remote Sensing for Land and Resources, vol. 2, pp. 54-61, 2009.
92. W. Sun, J. Chen, R. Wang, B. Yan, and H. Yu, "The application and research of hyperion for hyperspectral mineral mapping on east of Tianshan mountain, " Xinjiang Geology, vol. 28, pp. 214-217, 2010.
93. R. Wang, F. Gan, B. Yan, S. Yang, and Q. Wang, "Hyperspectral mineral mapping and its application, " Remote Sensing for Land and Resources, vol. 1, pp. 1-13, 2010.
94. S. Yan, X. Wu, C. Zhou, Z. Liu, Y. Zhuang, C. Cao, X. Wei, C. Yu, and C. Xiao, "Remote sensing and spectral geology and their applications to mineral exploration, " Advances in Earth Science, vol. 26, pp. 13-29, 2011.
95. X. Bi, F. Miao, B. Wu, J. Li, and D. Wang, "Hyperion hyperspectral remote sensing application in altered mineral mapping in East Kunlun of the Qinghai-Tibet Plateau, " in 2010 Int. Conf. Challenges in Environmental Science and Computer Engineering (CESCE), 2010, pp. 519-523.
96. F. Ye, D. Liu, and Y. Zhao, "Airborne hyperspectral survey system CASI/SASI and its preliminary application in uranium exploration, " World Nuclear Geoscience, vol. 28, pp. 231-236, 2012.
97. D.-Q. Xu, G.-Q. Ni, L.-L. Jiang, Y.-T. Shen, T. Li, S.-L. Ge, and X.-B. Shu, "Exploring for natural gas using reflectance spectra of surface soils, " Advances in Space Research, vol. 41, pp. 1800-1817, 2008. (Pubitemid 351622087)
98. Y. Z. Wu, X. Zhang, B. K. Yan, F. P. Gan, Z. S. Tang, A. A. Xu, Y. C. Zheng, and Y. L. Zou, "Global absorption center map of the mafic minerals on the moon as viewed by CE-1 IIM data, " Science China Physics, Mechanics & Astronomy, vol. 53, pp. 2160-2171, 2010.
99. Y. Wu, B. Xue, B. Zhao, P. Lucey, J. Chen, X. Xu, C. Li, and Z. Ouyang, "Global estimates of lunar iron and titanium contents from the Chang'E-1 IIM data, " J. Geophys. Res., vol. 117, p. E02001, 2012.
100. J. Wang, L. Zhang, Q. Tong, and X. Sun, The Spectral Crust Project-Research on New Mineral Exploration Technology. Shanghai, China: WHISPER, 2012.
101. G. Carr, A. Andrew, G. Denton, A. Giblin, M. Korsch, and D. Whitford, "The "Glass Earth"-Geochemical frontiers in exploration through cover, " AIG Bulletin, vol. 28, pp. 33-40, 1999.
102. S. U. Junying, "A spectrum fractal feature classification algorithm for agriculture crops with hyper spectrum image, " MIPPR 2011: Multispectral Image Acquisition, Processing, and Analysis, vol. 8002, 2011.
103. J. Wang, Y. H. Li, Y. Q. Chen, T. He, and C. Y. Lv, "Hyperspectral degraded soil line index and soil degradation mapping in agriculturepasturemixed area in Northern China, " in Proc. Int.Workshop on Earth Observation and Remote Sensing Applications, 2008, pp. 217-226.
104. J. Wu and D. L. Peng, "Advances in researches on hyperspectral remote sensing forestry information-extracting technology, " Spectroscopy and Spectral Analysis, vol. 31, pp. 2305-2312, Sep. 2011.
105. Y. Keming, C. Yunhao, and G. Dazhi, "Spectral information detection and extraction of wheat stripe rust based on hyperspectral image, " Acta Photonica Sinica, vol. 31, pp. 145-150, 2008.
106. G. L. Tian and X. H. Yang, "Remote sensing model for wheat drought monitoring, " Remote Sens. Environ. (China), vol. 7, pp. 83-89, 1992.
107. L. Y. Liu, "Hyperspectral remote sensing application in precision agriculture, " Ph.D. dissertation, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing, China, 2002.
108. L. Y. Liu, B. Zhang, L. F. Zheng, Q. X. Tong, Y. N. Liu, Y. Q. Xue, M. H. Yang, and C. J. Zhao, "Target classification and soil water content regression using surface temperature (LST) and vegetation index (VI), " J. Infrared Millim. Waves, vol. 21, pp. 269-273, 2002. (Pubitemid 35157664)
109. Y.Y. Wang, Y.H. Chen, J. Chen, andW. J. Huang, "Two newred edge indices as indicatiors for stripe rust disease severity of winter wheat, " J. Remote Sens., vol. 11, pp. 875-881, 2007.
110. L. Y. Liu, J. H. Wang, W. J. Huang, C. J. Zhao, B. Zhang, and Q. X. Tong, "Improving winter wheat yield prediction by novel spectral index, " Trans. CSAE, vol. 20, pp. 172-175, 2004.
111. P. Gong and R. L. Pu, "Conifer species recognition: Effects of data transformation, " Int. J. Remote Sens., vol. 22, pp. 3471-3481, Nov. 20, 2001. (Pubitemid 33028414)
112. Y. Q. Zhang, J. M. Chen, J. R. Miller, and T. L. Noland, "Leaf chlorophyll content retrieval from airborne hyperspectral remote sensing imagery, " Remote Sens. Environ., vol. 112, pp. 3234-3247, Jul. 15, 2008.
113. W. H. Zhao, B. H. Shan, and R. X. Zhong, "The normalized difference thermal index (NDTI) for the MODIS fire detection, " Remote Sens. Technol. Applicat., vol. 22, pp. 403-409, 2007.
114. F. Gan, S. Liu, and Q. Zhou, "Identification of mining pollution using Hyperion data at Dexing copper mine in Jiangxi Province, China, " Earth Science-J. China University of Geosciences, vol. 29, pp. 119-126, 2004.
115. B. Zhang, D. Wu, L. Zhang, Q. J. Jiao, and Q. T. Li, "Application of hyperspectral remote sensing for environment monitoring in mining areas, " Environmental Earth Sciences, vol. 65, pp. 649-658, Feb. 2012.
116. F. L. Yan, S. X. Wang, Y. Zhou, and Q. Xiao, "Monitoring the water quality of Taihu lake by using Hyperion hyperspectral data, " J. Infrared Millim. Waves, vol. 25, pp. 460-464, 2006.
117. G.H. Zhou, Q. H. Liu, R.H. Ma, andG. L. Tian, "Inversion of chlorophyll- A concentration in turbid water of Lake Taihu based on optimized multi-spectral combination, " J. Lake Sci., vol. 20, pp. 153-159, 2008.
118. D. Y. Sun, Y. M. Li, and Q. Wang, "A unified model for remotely estimating chlorophyll-a in Lake Taihu, China, based on SVM and in situ hyperspectral data, " IEEE Trans. Geosci. Remote Sens., vol. 47, pp. 2957-2965, Aug. 2009.
119. Q. Shen, B. Zhang, and J. S. Li, "Study on level-1 requirements of hyperapectral remote sensing sensor for inland waters, " presented at the WHISPERS 2012, Shanghai, China, 2012.
120. X. Hu, B. Zhang, X. Zhang, Q. Tong, L. Zheng, Q. Wang, and J. Yu, "A new architecture for remote-sensing environmental monitoring system REMS: Design and implementation, " in Proc. IEEE Int. Geoscience and Remote Sensing Symp. (IGARSS), 2004, pp. 2115-2118. (Pubitemid 40438181)
121. J. S. Li, "Study on retrieval of inland water quality parameters from hyperspectral remote sensing data by analytical approach-Taking Taihu Lake as an example, " Ph.D. dissertation, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing, China, 2007.
122. S. Li, L. Chen, F. Zheng, D. Han, and Z. Wang, "Design and application of Haze Optic Thickness retrieval model for Beijing Olympic Games, " in Proc. 2009 IEEE Int. Geoscience and Remote Sensing Symp., IGARSS 2009, pp. II-507-II-510.
123. D. Ji, Y. Wang, L. Wang, L. Chen, B. Hu, G. Tang, J. Xin, T. Song, T. Wen, Y. Sun, Y. Pan, and Z. Liu, "Analysis of heavy pollution episodes in selected cities of Northern China, " Atmospheric Environment, vol. 50, pp. 338-348, 2012.
124. J. Jiang, Y. Zha, J. Gao, and J. Jiang, "Monitoring of SO column concentration change over China from Aura OMI data, " Int. J. Remote Sens., vol. 33, pp. 1934-1942, 2012.
125. K. Wang, H. Jiang, X. Zhang, and G. Zhou, "Analysis of spatial and temporal variations of carbon dioxide over China using SCIAMACHY satellite observations during 2003-2005, " Int. J. Remote Sens., vol. 32, pp. 815-832, 2011.
126. Z. Wang, L. Chen, J. Tao, Y. Zhang, and L. Su, "Satellite-based estimation of regional particulate matter (PM) in Beijing using vertical- and-RH correcting method, " Remote Sens. Environ., vol. 114, pp. 50-63, 2010.
127. W. Xu, M. Wooster, and C. Grimmond, "Modelling of urban sensible heat flux at multiple spatial scales: A demonstration using airborne hyperspectral imagery of Shanghai and a temperature-emissivity separation approach, " Remote Sens. Environ., vol. 112, pp. 3493-3510, 2008.
128. H. Yang, L. Zhang, X. Zhang, C. Fang, and Q. Tong, "Algorithm of emissivity spectrum and temperature separation based on TASI data, " Yaogan Xuebao-J. Remote Sens., vol. 15, pp. 1242-1254, 2011.
129. H. Yang, "Study on temperature and emissivity separation from airborne hyperspectral thermal infraed data and their scale effect, " Ph.D. dissertation, Graduate University of Chinese Academy of Sciences, Beijing, China, 2011.
130. B. Zhang, "Hyperspectral data mining supported by temporal and spatial information, " Ph.D. dissertation, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing, China, 2002.
131. Y. D. Fan, Q. Wen, and S. R. Chen, "Engineering survey of the environment and disaster monitoring and forecasting small satellite constellation, " Int. J. Digital Earth, vol. 5, pp. 217-227, 2012.
132. Y. J. Cui, J.G. Du, Z. Chen, J. Li, C. Xie, X. Zhou, and L. Liu, "Remote sensing signals of atmospheric physics and chemistry related to 2010 Yushu Ms 7.1 earthquake, " Advances in Earth Science, vol. 26, pp. 787-794, 2011.
133. W. H. Pang, J. J. Chen, H. Chen, C. G. Zhang, and L. C. Li, "Dynamic monitoring of drought in Fujian Province fromMODIS remote sensing data, " Chinese J. Eco-Agriculture, vol. 16, pp. 1015-1019, 2008.
134. Y. L. Weng and P. Gong, "Remote sensing research progress of soil salinization, " Geograph. Sci., vol. 26, pp. 369-375, 2006.
135. Y.D. Fan, L. Wang, J. Nie, W. Wang, andB. J. Zhang, "Remote sensing monitoring and assessment technology for cryogenic freezing rain and snow disasters in China: Research and application, " J. Natural Disasters, vol. 17, pp. 21-25, 2009.
136. H. X. He, S. Y. Yang, W. T. Chen, H. Huang, Y. Cui, and X. P. Xie, "Application of HJ-1A hyperspectral data to the disaster reduction, " Spacecraft Eng., vol. 20, pp. 118-125, 2012.
137. R. Waring, J. Landsberg, and M. Williams, "Net primary production of forests: A constant fraction of gross primary production?, " Tree Physiol., vol. 18, pp. 129-134, 1998. (Pubitemid 28153662)
138. C. Wu, Z. Niu, Q. Tang, W. Huang, B. Rivard, and J. Feng, "Remote estimation of gross primary production in wheat using chlorophyll- related vegetation indices, " Agricult. Forest Meteorol., vol. 149, pp. 1015-1021, 2009.
139. C. Wu, "Use of a vegetation indexmodel to estimate gross primary production in open grassland, " J. Appl. Remote Sens., vol. 6, p. 063532-1, 2012.
140. C. Y. Wu, J. M. Chen, and N. Huang, "Predicting gross primary production from the enhanced vegetation index and photosynthetically active radiation: Evaluation and calibration, " Remote Sens. Environ., vol. 115, pp. 3424-3435, Dec. 15, 2011.
141. C. Y. Wu, J. W. Munger, Z. Niu, and D. Kuang, "Comparison of multiplemodels for estimating gross primary production usingMODIS and eddy covariance data in Harvard forest, " Remote Sens. Environ., vol. 114, pp. 2925-2939, Dec. 15, 2010.
142. C. Y. Wu, Z. Niu, and S. A. Gao, "Gross primary production estimation from MODIS data with vegetation index and photosynthetically active radiation in maize, " J. Geophys. Res.-Atmospheres, vol. 115, Jun. 30, 2010.
143. C. Y. Wu, X. Z. Han, J. S. Ni, Z. Niu, andW. J. Huang, "Estimation of gross primary production in wheat from in situ measurements, " Int. J. Appl. Earth Observ. Geoinf., vol. 12, pp. 183-189, Jun. 2010.
144. M. Shen, Y. Tang, J. Klein, P. Zhang, S. Gu, A. Shimono, and J. Chen, "Estimation of aboveground biomass using in situ hyperspectral measurements in five major grassland ecosystems on the Tibetan plateau, " J. Plant Ecol., vol. 1, pp. 247-257, 2008.
145. L. F. Zhang, "The universal pattern decompositionmethod and the vegetation index based on the UPDM, " Ph.D. dissertation, Wuhan University, Wuhan, China, 2005.
146. L. Zhang, S. Furumi, K. Muramatsu, N. Fujiwara, M. Daigo, and L. Zhang, "A new vegetation index based on the universal pattern decomposition method, " Int. J. Remote Sens., vol. 28, pp. 107-124, 2007. (Pubitemid 46978743)
147. L. Zhang, N. Fujiwara, S. Furumi, K. Muramatsu, M. Daigo, and L. Zhang, "Assessment of the universal pattern decomposition method using MODIS and ETM+ data, " Int. J. Remote Sens., vol. 28, pp. 125-142, 2007. (Pubitemid 46978744)
148. L. Zhang, B. Liu, B. Zhang, and Q. Tong, "An evaluation of the effect of the spectral response function of satellite sensors on the precision of the universal pattern decomposition method, " Int. J. Remote Sens., vol. 31, pp. 2083-2090, 2010.
149. J. W. Zhao, K. L. Wang, Q. Ouyang, and Q. S. Chen, "Measurement of chlorophyll content and distribution in tea plant's leaf using hyperspectral imaging technique, " Spectroscopy and Spectral Analysis, vol. 31, pp. 512-515, Feb. 2011.
150. C. Zhao, Z. Wang, J. Wang, W. Huang, and T. Guo, "Early detection of canopy nitrogen deficiency in winter wheat (Triticum aestivum L.) based on hyperspectral measurement of canopy chlorophyll status, " New Zealand J. Crop Horticult. Sci., vol. 39, pp. 251-262, 2011.
151. X. G. Xu, X. H. Gu, X. Y. Song, C. J. Li, and W. J. Huang, "Assessing rice chlorophyll content with vegetation indices from hyperspectral data, " Computer and Computing Technologies in Agriculture IV, Pt. 1, vol. 344, pp. 296-303, 2011.
152. S. Chen, S. Zhang, X. Sun, and Z. Li, "Quantitative estimation of rice chlorophyll concentration based on hyperspectral remote sensing technology, " in Proc. 2011 Int. Conf. Agricultural and Biosystems Engineering-Advances in Biomedical Engineering, 2011, vol. 1-2, pp. 354-356.
153. J. Y. Shi, X. B. Zou, J. W. Zhao, and X. P. Yin, "Measurement of chlorophyll distribution in cucumber leaves based on hyperspectral imaging technique, " Chinese J. Analyt. Chem., vol. 39, pp. 243-247, Feb. 2011.
154. Z. Niu, H. Zhang, and P. Gong, "More protection for China's wetlands, " Nature, vol. 471, pp. 305-305, 2011.
155. B. Zhang, X. Wang, J. Liu, L. Zheng, and Q. Tong, "Hyperspectral image processing and analysis system (HIPAS) and its applications, " Photogramm. Eng. Remote Sens., vol. 66, pp. 605-609, 2000. (Pubitemid 30263903)
156. H. Xingtang, "The research on the key technology of hyperspectral remote sensing enviroment monitoring system and its applications to water resources, " Ph.D. dissertation, Graduate University of Chinese Academy of Sciences, Beijing, China, 2005.
157. S. Yanmin, Z. Qijiang, W. Peijuan, W. Jindi, L. Suhong, and B. Xianghua, "Research on design of data warehouse system for object spectrum, " Comput. Eng. Applicat., vol. 39, pp. 199-201, 2003.
158. H. Qin and L. Zhang, "Design of hyperspectral multidimensional database for rock and mineral, " in Proc. 2011 Int. Conf. Remote Sensing, Environment and Transportation Engineering (RSETE), 2011, pp. 1092-1095.