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NTIS 바로가기대한원격탐사학회지 = Korean journal of remote sensing, v.21 no.4, 2005년, pp.341 - 369
김선화 (인하대학교 지리정보공학과) , 마정림 (인하대학교 지리정보공학과) , 국민정 (인하대학교 지리정보공학과) , 이규성 (인하대학교 지리정보공학과)
Hyperspectral images have emerged as a new and promising remote sensing data that can overcome the limitations of existing optical image data. This study was designed to provide a comprehensive review on definition, data processing methods, and applications of hyperspectral data. Various types of ai...
Abousleman, G. P., M. W. Marcellin, and B. R Hoot, 1995. Compression of hyperspectral imagery using the 3-D DCT and Hybrid DPCMj DCT, IEEE Transactions on Geoscience and Remote Sensing, 33(1): 26-34
Aiazzi, B., P. Alba, L. Alparone, and S. Baronti, 1999. Lossless Compression of Multi/HyperSpectral Imagery Based on a 3-D Fuzzy Prediction, IEEE Transactions on Geoscience and Remote Sensing, 37(5): 2287-2294
Aiazzi, B., L. Alparone, and S. Baronti, 2001. Near Lossless compression of 3-D optical data IEEE Transactions on Geoscience and Remote Sensing, 39(11): 2547-2557
Apan, A., A. Held, S. Phinn, and J. Markley, 2004. Detecting sugarcane 'orange rust' disease using EO-1 Hyperion hyperspectral imagery, International Journal of Remote Sensing, 25(2): 489-498
Asner, G. P. and K. B. Heidebrecht, 2002. Spectral unmixing of vegetation, soil and dry carbon cover in arid regions:comparing multispectral and hyperspectral observations, International Journal of Remote Sensing, 23(19): 3939-3958
Asner, G. P. and K. B. Heidebrecht, 2003. Imaging spectroscopy for desertification studies: comparing A VIRIS and EO-1 Hyperion in Argentina Drylands, IEEE Transactions on Geoscience and Remote Sensing, 41(6): 1283-1296
Asner, G. P., M. M. C. Bustamante, and A. R. Townsend, 2003. Scale dependence of biophysical structrue in deforested areas bordering the Tapaos National Forest, Central Amazon, Remote Sensing of Environment, 87: 507-520
Atkinson, P. M., 1997. On estimating measurement error in remotely sensed images with the variogram, International Journal of Remote Sensing, 18(14): 3075-3084
Bachmann, C. M., 2003. Improving the performance of classifiers in High dimensional remote sensing applications: An adaptive resampling strategy for error prone example, IEEE Transactions on Geoscience and Remote Sensing, 41(9): 2101-2112
Bachmann, C. M., M. H. Bettenhausen, and R. A. Fusina, 2003. A Credit Assignment Approach to fusing Classifiers of Multiseason Hyperspectral Imagery, IEEE Transactions on Geoscience and Remote Sensing, 41(11): 2488-2499
Bateson, C. A., G. P. Asner, and C. A. Wessman, 2000. Endmember Bundles: A New Approach to incorporating endmember variability into spectral mixture analysis, IEEE Transactions on Geoscience and Remote Sensing, 38(2): 1083-1094
Ben-Dor, E., N. Levin, and H. Saaroni, 2001. A spectral based recognition of the urban environment using the visible and near infrared spectral region. A case study over Tel Aviv, Israel International Journal of Remote Sensing, 22(11): 2193-2218
Ben-Dor, E., B. Kindel, and A. F. H. Goetz, 2004. Quality assessment of several methods to recover surface reflectance using synthetic imaging spectroscopy data, Remote Sensing of Environment, 90: 389-404
Benediktsson, J. I., J. R. Sveinsson, and K. Amason, 1995. Classification and Feature Extraction of A VIRIS Data, IEEE Transactions on Geoscience and Remote Sensing, 33(5): 1194-1205
Biggar, S. F., K. J. Thome, and W. Wisniewski, 2003. Vicarious radiometric calibration of EO-1 sensors by reference to High-reflectance ground targets, IEEE Transactions on Geoscience and Remote Sensing, 41(6): 11741179
Blackburn, G. A. and E. J. Milton., 1997. An ecological survey of deciduous woodlands using airborne remote sensing and geographical information system(GIS), International Journal of Remote Sensing, 18(9): 1919-1935
Brando, V. E. and A. G. Dekker, 2003. Satellite Hyperspectral Remote Sensing of Estimating Esturaine and Coastal Water Quality, IEEE Transactions on Geoscience and Remote Sensing, 41(6): 1378-1387
Bruce, L. M., C. Morgan, and S. Larsen, 2001. Automated Detection of subpixel hyperspectral targets with continuous and discrete wavelet transforms, IEEE Transactions on Geoscience and Remote Sensing, 39(10): 2217-2226
Cairns, B., B. E. Carlson, R. Ing., A. A. Lacis, and V. Oinas, 2003. Atmospheric Correction and Its Application to an Analysis of hyperion Data, IEEE Transactions on Geoscience and Remote Sensing, 41(6): 1232-1244
Chabrillat, S., P. C. Pinet, G. Ceulneer, P. E. Johnson, and J. F. Mustard, 2000. Ronda peridotite massif: methodology for its geological mapping and lithological discrimination from airborne hyperspecral data, International Journal of Remote Sensing, 21(12): 2363-2388
Chabrillat, S., A. F. H. Goetz, L. Krosley, and H. W. Olsen, 2002. Use of hyperspectral images in the identification and mapping of expansive clay soils and the role of spatial resolution, Remote Sensing of Environment, 82: 431-445
Chang, C. I. and O. Du, 1999. Interference and Noise Adjusted principal components analysis, IEEE Transactions on Geoscience and Remote Sensing, 37(5): 2387-2396
Chang, C. I. and H. Ren, 2000. An Experiment-Based Quantitative and Comparative Analysis of Target Detection and Image Classification Algorithm for Hyperspectral Imagery, IEEE Transaction on Geoscience and Remote Sensing, 38(2): 1044-1063
Chang, C. I., S. S. Chiang, J. A Smith, and K. W. Ginsberg, 2002. Linear Spectral Random Mixture Analysis for Hyperspectral Imagery, IEEE Transactions on Geoscience and Remote Sensing, 40(2): 375-392
Chang, C. I., 2002. Target Signature constrained mixed pixel classification for hyperspectral imagery, IEEE Transactions on Geoscience and Remote Sensing, 40(5): 1065-1081
Chang C. I., Ren H., and Chiang S. S., 2001. Realtime processing algorithms for target detection and classification in hyperspectral imagery, IEEE Transactions on Geoscience and Remote Sensing, 39(4): 760-768
Crosta, A. P., C. Sabine, and J. V. Taranik, 1998. Hydrothermal Alteration Mapping at bodie, California, Using A VIRIS hyperspectral data, Remote Sensing of Environment, 65: 309-319
Curran, P. J. and J. L. Dungan, 1989. Estimation of Signal to Noise: Anew procedure applied to A VlRIS data, IEEE Transactions on Geoscience and Remote Sensing, 27(5): 620-628
Datt, B., T. R. McVicar, T. G. Van Niel, D. L. B. Jupp, and J. S. Pearlman, 2003. Preprocessing EO-l Hyperion Hyperspectral data to Support the Application of Agricultural Indexs, IEEE Transactions on Geoscience and Remote Sensing, 41(6): 1246-1259
Dennison, P. E. and D. A. Roberts, 2003. The effects of vegetation phenology on endmember selection and species mapping in southern California chaparral, Remote Sensing of Environment, 87: 295-309
Drake, N. A., S. Mackin, and J. J. Settle, 1999. Mapping vegetation, soils, and geology in semiarid shrublands using spectral matching and mixture modeling of SWIR A VIRIS iamgery, Remote Sensing of Environment, 68: 12-25
Du, Q. and C. I. Chang, 2004. Linear Mixture Analysis based compression for hyperspectral image Analysis, IEEE Transactions on Geoscience and Remote Sensing, 42(4): 875-89l
Farrand, W. H. and J. C. Harsanyi, 1997. Mapping the distribution of mine tailings in the Coeur d'Alene River Valley, Idaho through the use of a Constrained Energy Minimization technique, Remote Sensing of the Environment, 59: 64-76
Feind, R. E. and R. M. WELCH, 1995. Cloud fraction and cloud shadow property retrievals from coregistered TIMS and AVIRIS imagery: the use of cloud morphology for registration, IEEE Transactions on Geoscience and Remote Sensing, 33(1): 172-184
Gao, B. C. and A. F. H. Goetz, 1995. Retrieval of Equivalent Water Thickness and Information Related to Biochemical Components of Vegetation Canopies from AVIRIS Data, Remote Sensing of Environment, 52: 155-162
Gao, B. C, P. Yang, W. Han, R. R. Li, and W. J. Wiscombe, 2002. An algorithm using visible and 1.38m channels to retrieve cirrus cloud reflectances from aircraft and satellite data, IEEE Transactions on Geoscience and Remote Sensing, 40(8): 1659-1668
Gao, B. C, M. J. Montes, and C. O. Davis, 2004. Refinement of wavelength calibrations of hyperspectral imaging data using a spectrum matching technique, Remote Sensing of Environment, 90: 424-433
Goodenough, D. G., A. Dyk, K. O. Niemann, J. S. Pearlman, H Chen, T. Han, M. Murdoch, and C. West, 2003. Processing hyperion and ALI for Forest Classification, IEEE Transactions on Geoscience and Remote Sensing, 41(6): 1321-1331
Galvao, L. S., W. P. Filho, M. M. Abdon, E. M. M. L. Novo, J. S. V. Silva, and F. J. Ponzoni, 2003. Spectral reflectance characterization of shallow lakes from the Brazilian Pantanal wetlands with field and airborne hyperspectral data, International Journal of Remote Sensing, 24(21): 4093-4112
Garcia, M. and S. L. Us tin, 2001. Detection of Interannual Vegetaion Responses to Climatic Variability using AVIRIS data in a coastal savanna in California, IEEE Transactions on Geoscience and Remote Sensing, 39(7): 14801490
Gelpi, C. C., 2000. Removing Path Scattered Radiance from Over ocean spectrometer Images for Water vapor estimation, Remote Sensing of Environment, 74: 414-421
Goetz A. F. H., 1991. Imaging spectrometry for studying Earth, Air, Fire and Water, EARSeL Advances in Remote Sensing, 1: 3-15
Goetz, A. F. H, B. C. Kinde , M. Ferri, and Z. Qu, 2003. HATCH: Results from simulated radiances, AVIRIS and Hyperion, IEEE Transactions on Geoscience and Remote Sensing, 41(6): 1215-1222
Gong, P., J. R. Miller, and M. Spanner, 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
Gong, P., R. Pu, and R. C. Heald, 2002. Analysis of in situ hyperspectral data for nutrient estimation of giant sequoia, International Journal of Remote Sensing, 23(9): 1827-1850
Green, A. A., M. Berman, P. Switzer, and M. D. Graig, 1998. A transformation for ordering multispectral data in terms of image quality with implications for noise removal, IEEE Transactions on Geoscience and Remote Sensing, 26(1): 65-74
Gu, D., A. R. Gillespie, A. B. Kahle, and F. D. Palluconi, 2000. Autonomous Atmospheric Compensation(AAC) of High Resolution Hyperspectral thermal infrared remote sensing imagery, IEEE Transactions on Geoscience and Remote Sensing, 38(6): 2557-2570
Gu, Y, J. M. Anderson, and J. G. C. Monk, 1999. An approach to the spectral and radiometric calibration of the VIFIS system, International Joural of Remote Sensing, 20(3): 535-548
Hapke, B., 1981. Bidirectional reflectance spectroscopy 1. Theory, J. Geophys. Res., 86: 3039-3054
Hapke, B., 1993. Theory of Reflectance and Emittance Spectroscopy, Cambridge, U.K.: Cambridge Univ. Press
Herold, M., D. A. Roberts, M. E. Gardner, and P. E. Dennison, 2004. Spectrometry for urban area remote sensing-development and analysis of a spectral library from 350 to 2400nm, Remote Sensing of Environment, 91: 304-319
Hoffman, R. N. and D. W. Johnson, 1994. Application of EOF's to Multispectral Imagery: Data Compression and Noise Detection for AVIRIS, IEEE Transactions on Geoscience and Remote Sensing, 32(1): 25-34
Hochberg, E. J. and M. J. Atkinson, 2003. Capabilities of remote sensors to classify coral, algae, and sand as pure and mixed spectra, Remote Sensing of Environment, 85: 174-189
Hoogenboom, H. J., A. G. Dekker, and I. A. Althuis, 1998. Simulation of A VIRIS Sensitivity for Detecting Chlorophyll over Coastal and Inland Waters, Remote Sensing of Environment, 65: 333-340
Hubbard, B. E., J. K.Crowley, and D. R. Zimbelman, 2003. Comparative Alteration Mineral Mapping Using Visible to Shortwave Infrared(0.4-2.5, $\mu$ m) Hyperion, ALI, and ASTER Imagery, IEEE Transactions on Geoscience and Remote Sensing, 41(6): 14011410
Ifarraguerri, A. and C. I. Chang, 1999. Multispectral and Hyperspectral Image Analysis with Convex Cones, IEEE Transactions on Geoscience and Remote Sensing, 37(2): 756-770
Ingram, P. M. and A. H. Muse, 2001. Sensitivity of Iterative Spectrally Smooth Temperature/ Emissivity Separation to algorithmic assumptions and measurement noise, IEEE Transactions on Geoscience and Remote Sensing, 39(10): 2158-2167
Jacquemoud, S., F. Baret, B. Andrieu, F. M. Danson, and K. Jaggard, 1995. Extraction of Vegetation Biophysical Parameters by Inversion of the PROSPECT + SAIL models on Sugar beet canopy reflectance data. Application to TM and A VIRIS sensors, Remote Sensing of Environment, 52: 163-172
Jia, X. and J. A. Richards, 1998. Progressive two class decision classifier for optimization class discriminations, Remote Sensing of Environment, 63: 289-297
Jia, X. and J. A. Richards, 2002. Cluster Space Representation for Hyperspectral Data Classification, IEEE Transactions on Geoscience and Remote Sensing, 40(3): 593-598
Jiang, X., L. Tang, and C. Wang, 2004. Spectral characteristics and feature selection of hyperspectral remote sensing data, International Journal of Renwte Sensing, 25(1): 51-59
Jimenez, L. O. and D. A. Landgrebe, 1999. Hyperspectral Data Analysis and supervised feature reduction via projection pursuit, IEEE Transactions on Geoscience and Remote Sensing, 37(6): 2653-2667
Jong, S. M., E. J. Pebesma, and B. Lacaze, 2003. Above ground biomass assessment of Mediterranean forests using airborne imaging spectrometry: the DAIS Peyne experiment, International Journal of Remote Sensing, 24(7): 1505-1520
JPL, 2005. NASA JPL Homepage (http://aviris.jpl. nasa.gov)
Kaewpijit, S., J. Le Moigne, and T. El Ghazawi, 2003. Automatic Reduction of Hyperspectral Imagery Using Wavelet Spectral Analysis, IEEE Transactions on Geoscience and Remote Sensing, 41(4): 863-871
Kallio, K., S. Koponen, and J. Pulliainen, 2003. Feasibility of airborne imaging spectrometry for lake monitoring a case study of spatial chlorophyll a distribution in two, International Journal of Renwte Sensing, 24(19): 3771-3790
Keshava, N. and J. F. Mustard, 2002, Spectral Unmixing, IEEE Signal Processing Magazine, 19(1): 44-57
Kim, B. Y. and D. A. Landgrebe, 1991. Hierarchical classifier design in high dimensional, numerous class cases, IEEE Transactions on Geoscience and Remote Sensing, 29(4): 518-528
Kirkland, L., K. Herr, E. Keirn, P. Adams, J. Salisbury, J. Hackwell, and A Treiman, 2002. First use of an airborne thermal infrared hyperspectral scanner for compositional mapping, Remote Sensing of Environment, 80: 447-459
Kokaly, R. F., D. G. Despain, R. N, Clark, and K. E. Livo, 2003. Mapping vegetation in yellowstone national park using spectral feature analysis of A VIRIS data, Remote Sensing of Environment, 84: 437-456
Koponen, S., J. Pulliainen, K. Kallio, and M. Hallikainen, 2002. Lake water Quality classification with airborne hyperspectral spectrometer and simulated MERIS data, Remote Sensing of Environment, 79: 51-59
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
Kumar,S., J. Ghosh, and M. M. Crawford, 2001. Best bases feature extraction algorithms for classification of hyperspectral data, IEEE Transactions on Geoscience and Remote Sensing, 39(7): 1368-1379
Kuo, B. C. and D. A Landgrebe, 2002. A Covariance estimator for small sample size classification problems and its application to feature extraction, IEEE Transactions on Geoscience and Remote Sensing, 40(4): 814-81
Landgrebe D., 2001. Analysis of Multispectral and Hyperspectral Image Data, John Wiley & Sans, 2001
Launeau, P., J. Girardeau, C. Satin, and J. M. Tubia, 2004. Comparison between field measurements and airborne visible and infrared mapping spectrometry(AVIRIS and HyMap) of the Ronda peridotite massif (south west Spain), International Joural of Remote Sensing, 25(14): 2773-2792
Lee, Z. P. and K. L. Carder, 2004. Absorption spectrum of phytoplankton pigments derived from hyperspectal remote sensing reflectance, Remote Sensing of Environment, 89: 361-368
Longhi, I., M. Sgavetti, R Chiari, and C. Mazzoli, 2001. Spectral analysis and classification of metamorphic rocks from laboratory reflectance spectra in the 0.4-2.5 interval: a tool for hyperspectral data interpretation, International Journal of Remote Sensing, 22(18): 3763-3782
Lu, D., P. Mausel, E. Brondizio, and E. Moran, 2004. Change Detection techniques, International Journal of Remote Sensing, 25(12): 2365-2407
Manolakis, D., C. Siracusa, and G. Shaw, 2001. Hyperspectral Subpixel Target Detection Using the Linear Mixing Model, IEEE Transactions on Geoscience and Remote Sensing, 39(7): 1392-1409
Marion, R, R Michel, and C. Faye, 2004. Measuring Trace Gases in Plumes From Hyperspectral Remotely Sensed data, IEEE Transactions on Geoscience and Remote Sensing, 42(4): 854-864
Metternicht, G. I. and J. A. Zinck, 2003. Remote Sensing of soil salinity: potentials and constraints, Remote Sensing of Environment, 85: 1-20
Mutanga, O. and A. K. Skidmore, 2004. Integrating imaging spectroscopy and neural networks to map grass uality in the Kruger National Park, South Afria, Remote Sensing of Environment, 90: 104-115
Niemann, K. O., D. G. Goodenough, and A. S. Bhogal, 2002. Remote Sensing of relative moisture status in old growth Douglas fir, International Journal of Remote Sensing, 23(2): 395-400
Okin, G. S. and T. H. Painter, 2004. Effect of grain size on remotely sensed spectral reflectance of sandy desert surfaces, Remote Sensing of Environment, 89: 272-280
Palacios Orueta, A. and S. L. Ustin, 1996. Multicariate statistical classification of soil spectra, Remote Sensing of Environment, 57: 108-118
Pekkarinen, A., 2002. A method for the segmentation of very high spatial resolution images of forested landscapes, International Journal of Remote Sensing, 23(14): 2817-2836
Pu, R, Gong P., and G. S. Biging, 2003. Simple calibration of AVIRIS data and LAI mapping of forest plantation in southern argentina, International Journal of Remote Sensing, 24(23): 4699-4714
Pu, R., Q. Yu. P. Gong, and G. S. Biging, 2005. EO-1 Hyperion, ALI and Landsat 7 ETM+ data comparison for estimating forest crown closure and leaf area index, International Journal of Remote Sensing, 26(3): 457-474
Rand, R S. and D. M. Keenan, 2001. A spectral mixture process conditioned by cibbs based partitioning, IEEE Transactions on Geoscience and Remote Sensing, 39(7): 1421-1434
Rees, W. G., O. V. Tutubalina, and E.I. Golubeva, 2004. Reflectance spectra of subarctic lichens between 400 and 2400 nm, Remote Sensing of Environment, 90: 281-292
Resmini, R F., M. E. Kappus, W. S. Sldrich, J. C. Haranyi, and M. Anderson, 1997. Mineral mapping withhyperspectral Digital Imagery Collection Experiment (HYDICE) sensor data at Cuprite, Nevada, U.S.A. International Journal of Remote Sensing, 18(7): 1553-1570
Riano, D., E. Chuvieco, S. Ustin, R Zomer, P. Dennison, D. Roberts, and J. Salas, 2002. Asessment of vegetation regeneration after fire through multi temporal analysis of AVIRIS images in the Santa Monica Mountains, Remote Sensing of Environment, 79: 60-71
Richter, R. and D. Schlapfer, 2002. Geo atmospheric processing of airborne imaging spectrometry data. Part 2: atmospheric .topographic correction, International Journal of Remote Sensing, 23(13): 2631-2649
Roberts, D. A., M. O. Smith, and J. B. Adams, 1993. Green vegetation, nonphotosynthetic vegetation, and soils in AVIRIS data, Remote Sensing of Environment, 44: 255-269
Roberts, D. A., P. E. Dennison, M. E. Gardner, Y. Hetzel, S. L. Ustin, and C. T. Lee, 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, 41(6): 1297-1310
Ryan, M. J. and J. F. Arnold, 1997. The lossles compression of AVIRIS images by vector quantization, IEEE Transactions on Geoscience and Remote Sensing, 35(3): 546-550
Sanders, L. C. J. R. Schott, and R. Raqueno, 2001. AVNIR/SWIR atmospheric correction algorithm for hyperspectal imagery with adjacency effect, Remote Sensing of Environment, 78: 252-263
Schmid, T., M. Koch, J. Gumuzzio, and P. M. Mather, 2004. A spectral library for a semi arid wetland and its application to studies of wetland degradation using hyperspectral and multispectral data, International Journal of Remote Sensing, 25(13): 2485-2496
Seeker, J., K. Staenz, R. P. Gauthier, and P. Budkewitsch, 2001. Vicarious calibration of airborne hyperspectral sensors in operational environments, Remote Sensing of Environment, 76: 81-92
Serpico, S. B. and L. Bruzzone, 2001. Anew search algorithm for feature selection in hyperspectral remote sensing images, IEEE Transactions on Geoscience and Remote Sensing, 39(7): 1360-1367
Shaw, G. and D. Manolakis, 2002, Singal Processing for Hyperspectral Image Exploitation, IEEE Signal Processing Magazine, 19(1): 12-16
Shippert, P., 2004. Why Use Hyperspectral Imagery?, Photogrammetric Engineering & Remote Sensing, 70(4): 377-380
Silvestri, S., M. Marani, J. Settle, F. Benvenuto, and A. Marani, 2002. Salt marsh vegetation radiomerty data analysis and scaling, Remote Sensing of Environment, 80: 473-482
Smith, M. L., M. E. Martin, L. Plourde, and S. V. Ollinger, 2003. Analysis of Hyperspectral data for estimation of temperate forest canopy nitrogen concentration: comparison Between an Airborne(AVIRIS) and a space borne(Hyperion) Senor, IEEE Transactions on Geoscience and Remote Sensing, 41(6): 13321337
Teillet, P. M., G. Fedosejevs, R. P. Gauthier, N. T. O'Neill, K. J. Thome, S. F. Biggar, H. Ripley, and A. Meygret, 2001. A generalized approach to the vicarious calibration of multiple Earth observation sensors using hyperspectral data, Remote Sensing of Environment, 77: 304-327
Thiemann, S. and H. Kaufmann, 2002. Lake water quality monitoring using hyperspectral airborne data a semiempirical multisensor and multitemporal approach for the Mecklenburg Lake Distric, Germany Remote Sensing of Environment, 81: 228-237
Tu, T. M., C. H. Chen, and C. I. Chang, 1997. A Posteriori Least Squares Orthogonal Subspace projection approach to Desired signature extraction and detection, IEEE Transactions on Geoscience and Remote Sensing, 35(1): 127-139
Tu, T. M., C. H. Chen, J. L. Wu, and C. I. Chang, 1998. A Fast Two stage classification method for high dimensional remote sensing data, IEEE Transactions on Geoscience and Remote Sensing, 36(1): 182-191
Ustin, S. L. and Q. F. Xiao, 2001. Mapping successional boreal forests in interior central Alaska, International Journal of Remote Sensing, 22(6): 1779-1797
Van der Meer, F., F. Lihui, and J. Bodechtel, 1997 MAIS imaging spectrometer data analysis for Ni Cu prospecting in ultramafic rocks of the Jinchuan group, China International Journal of Remote Sensing, 18(13): 2743-2761
Van der Meer, F., 2000. Spectral curve shape matching with a continnurn removed CCSM algorithm, International Journal of Remote Sensing, 21(16): 3179-3185
Van der Meer, F. and V. Kato, 2002. Developing a schematic petrogenetic transect for a contact aureole using field spectrometry; a case study in Los Santos, Salamanca Province, central western Spain, International Journal of Remote Sensing, 23(23): 5087-5094
Van der Meer, F., 2003. Bayesian inversion of imaging spectrometer data using a fuzzy geological outcrop model, International Journal of Remote Sensing, 24(22): 4301-4310
Verhoef, W. and H. Bach, 2003. Simulation of hyperspectral and directional radiance images using coupled biophysical and atmosphere radiative transfer models, Remote Sensing of Environment, 87: 23-41
Viggh, H. E. M. and D. H. Staelin, 2003. Spatial surface prior infomation reflectance estimation (SPIRE) algorithm, IEEE Transactions on Geoscience and Remote Sensing, 41(11): 2424-2435
Wagtendonk, J. W, R. R. Root, and C. H. Key, 2004. Comparison of AVIRIS and Landsat ETM + detection capabilities for burn severity, Remote Sensing of Environment, 92: 397-408
Warner, T. A. and M. C. Shank, 1997. Spatial Autocorrelation Analysis of Hyperspectral Imagery for Feature Selection, Remote Sensing of Environment, 60: 58-70
Warner, T. A., K. Steinmaus, and H. Foote, 1999. An evaluation of spatial autocorrelation feature selection, International Journal of Remote Sensing, 20(8): 1601-1616
Whiting, M. L., L. Li, and S. L. Ustin, 2004. Predicting water content using Gaussian model on soil spectra, Remote Sensing of Environment, 89: 535-552
Williams, A. P. and Jr R. E. Hunt, 2002. Estimation of leafy spurge cover from hyperspectral imagery using mixture tuned matched filtering, Remote Sensing of Environment, 82: 446-456
Yang, H, F. Van der Meer, W Bakke, and Z. J. Tan, A back propagation neural network for mineralogical mapping from AVIRlS data, 1999. International Journal of Remote Sensing, 20(1): 97-110
Yao, H. and L. Tian, 2003. A genetic algorithm based selective principal component analysis (GA SPCA) method for high dimensional data feature extraction, IEEE Transactions on Geoscience and Remote Sensing, 41(6): 1469-1478
Zarco Tejada, P. J., J. R. Miller, T. L. Noland, G. H. Mohammed, and P. H. Sampson, 2001. Scaling up and model inversion methods with narrowband optical indices for chlorophyll content estimation in closed forest canopies with hyperspectral data, IEEE Transactions on Geoscience and Remote Sensing, 39(7): 1491-1507
Zarco Tejada, P. J., J. C. Pushnik, S. Dobrowskui, and S. L. Ustin, 2003. Steady state chlorophyll a fluorescence detection from canopy derivatice reflectance and double peak red edge effects, Remote Sensing of Environment, 84: 283-294
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