A. Bibliographie, G. Alimohammadi, and T. Tehran, Application of remote sensing in urban area studies. Ms courses in RS, 1998.

. Arkun, Study of CASI (Compact Airbourne Spectral Graphics Imager) to differenciate urban surfaces for inclusion into GIS data, Thèse de doctorat, 2002.

S. Arkun, J. Iain, and S. M. Ranson, Hyperspectral remote sensing for vineyard management. web site, 2001.

L. Beaudoin, Sélection de données satellitales optiques pour la photo-interprétation, Thèse de doctorat, 2001.

E. Ben-dor, Imaging Spectrometry For Urban Applications, pp.243-281, 2003.
DOI : 10.1007/978-0-306-47578-8_9

E. Ben-dor, N. Levin, and H. Saaroni, A spectral based recognition of the urban environment using the visible and near-infrared spectral region (0.4-1.1 m). a case study over tel-aviv, International Journal of Remote Sensing, issue.11, pp.222193-2218, 2001.

E. Ben-dor, Y. Unbar, and Y. Chen, The reflectance spectra of organic matter in the visible near-infrared and short wave infrared region (400???2500 nm) during a controlled decomposition process, Remote Sensing of Environment, vol.61, issue.1, pp.1-15, 1997.
DOI : 10.1016/S0034-4257(96)00120-4

A. Berk, L. S. Bernstein, and D. C. , Roberston : Modtran a moderate resolution model for lowtran, 1989.

A. Bijaoui, D. Nuzillard, and T. D. Barma, Séparation aveugle de sources, démélange de pixel et la classification, application en télédétection. Action spécifique de GDR-ISIS, 2003.

V. Bouland, CaractérisationCaractérisationélectromagneéique des milieux urbains en imagerie de télédétection par radaràradarà synthèse d'ouverture, Thèse de doctorat, 2002.

L. Brad, L. Johnson, C. Hlavka, R. Armstrong, and C. Bell, Grapevine remote sensing analysis of phylloxera early stress (grapes) Rapport technique, 1997.

A. P. Bradley, The use of the area under the ROC curve in the evaluation of machine learning algorithms, Pattern Recognition, vol.30, issue.7, pp.1145-1159, 1997.
DOI : 10.1016/S0031-3203(96)00142-2

D. Broghys, Interprétation et recalage d'images SAR polarimétriquespolarimétriquesà haute résolution, Thèse de doctorat, 2001.

A. Capelle, O. Colot, and C. Fernandez-maloigne, Evidential clustering algorithm for color quantization, Beijing International Conference on Imaging : Technology and Applications for the 21st Century, 2005.
URL : https://hal.archives-ouvertes.fr/hal-00343867

J. Cardoso, High-Order Contrasts for Independent Component Analysis, Neural Computation, vol.140, issue.1, pp.157-192, 1999.
DOI : 10.1109/78.599941

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

J. Cardoso and B. H. Laheld, Equivariant adaptive source separation, IEEE Transactions on Signal Processing, vol.44, issue.12, pp.3017-3030, 1996.
DOI : 10.1109/78.553476

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

J. Cardoso and A. Souloumiac, Blind beamforming for non-gaussian signals, IEE proceedings-f, 1993.
DOI : 10.1049/ip-f-2.1993.0054

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

F. Casciati, P. Gamba, F. Giorgi, and A. Mecocci, Planning a radsatt extention, Proceeding of GIS and Applications of Remote Sensing to Damage Management, pp.1-10, 1996.

F. Chaabane, Suivi multitemporel en interferometrie radar et prise en compte des effets atmospheriques, Thèse de doctorat, 2004.

C. Chang, Hyperspectral Imaging, 2003.
DOI : 10.1007/978-1-4419-9170-6

C. Chang, J. Liu, B. Chieu, C. Wang, C. S. Lo et al., A generalized constrained energy minimization approach to subpixel target detection for multispectral imagery, pp.1275-1281, 2000.

K. Chehdi and C. , Kermad : Multi-bands image segmentation : A scalar approach, IEEE International Conference on Image Processing, pp.1012-1025, 2000.

P. Comon, Independent component analysis, a new concept ? Signal Processing, pp.287-314, 1994.

I. Couloingner, T. Ranchin, V. P. Valtonen, and L. Wald, Benefit of the future SPOT-5 and of data fusion to urban roads mapping, International Journal of Remote Sensing, vol.19, issue.8, pp.1519-1532, 1998.
DOI : 10.1080/014311698215324

L. W. Cudlip, C. Lysons, R. Ley, G. Deane, F. Stroink et al., A new information system in support of landscape assessment: PLAINS, Computers, Environment and Urban Systems, vol.23, issue.6, pp.459-467, 1999.
DOI : 10.1016/S0198-9715(99)00035-6

O. and D. Joinville, Evaluation de la qualité d'une cartographie urbainè a l'aide d'images aériennesaériennesà haute résolution, Thèse de doctorat, 2001.

M. Ehlers, Remote sensing for GIS applications: new sensors and analysis methods, Proceedings of SPIE, 2003.
DOI : 10.1117/12.514078

C. D. Elvige, Visible and near infrared reflectance characteristics of dry plant materials, International Journal of Remote Sensing, vol.26, issue.10, pp.1775-1795, 1990.
DOI : 10.1139/x88-002

E. Nasa, EO1 documantations (new technology demonstrator satellite) NASA Earth Observer -1

W. H. Farrand and J. C. Harsanyi, 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 Environment, vol.59, issue.1, pp.64-76, 1997.
DOI : 10.1016/S0034-4257(96)00080-6

D. Frolov and R. B. , Smith : Locally adaptive constrained energy minimization for aviris image, Eighth JPL Airborne Earth Science (AVIRS), 1999.

T. Fung and W. Siu, Environmental quality and its changes, an analysis using NDVI, International Journal of Remote Sensing, vol.21, issue.5, pp.1011-1024, 2000.
DOI : 10.1080/014311600210407

P. Gamba and P. Savazzi, Classification of urban environments in SAR images: a fuzzy clustering perspective, IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings. (Cat. No.98CH36174), pp.351-353, 1998.
DOI : 10.1109/IGARSS.1998.702902

B. Gao, C. O. Daviss-shen, and ´. , Development of a line by line based atmosphere removal algorithm for airborne and spaceborn imaging spectrometer, Imaging Spectrometry III SPIE, pp.132-141, 1997.

B. Gao, M. J. Montes, A. Ziauddin, and O. D. Curtiss, Atmospheric correction algorithm for hyperspectral remote sensing of ocean color from space, Applied Optics, vol.39, issue.6, pp.887-896, 2000.
DOI : 10.1364/AO.39.000887

N. Gat, Direction in environmental spectroscopy, Spcetrocopy SHWCASE, 1999.

A. F. Goetz, G. Vane, J. E. Solomon, and B. Rock, Imaging Spectrometry for Earth Remote Sensing, Science, vol.228, issue.4704, pp.1147-1153, 1985.
DOI : 10.1126/science.228.4704.1147

R. B. Gomez, Key issues of hyperspectral sensing technology applications, Space Technology Conference and Exposition, 1999.
DOI : 10.2514/6.1999-4563

J. C. Granahan and J. N. , Sweet : An evaluation of atmospheric correction techniques using the spectral similarity scale, pp.2022-2024, 2001.

C. I. Grove, S. J. Hook, and I. E. Paylor, Labratory reflectance spectra of 160 minerals, 0.4 to 2.25 micrometers, pp.92-94, 1992.

J. C. Harsanyi, Detection and Classification of Sub pixel spectral Signatures in Hyperspectral Image Sequences, 1993.

G. Healey and D. Slater, Invariant recognition in hyperspectral images, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149), pp.438-443, 1999.
DOI : 10.1109/CVPR.1999.786975

G. Healey and D. Slater, Models and methods for automated material identification in hyperspectral imagery acquired under unknown illumination and atmospheric conditions, IEEE Transactions on Geoscience and Remote Sensing, vol.37, issue.6, pp.2706-2716, 1999.
DOI : 10.1109/36.803418

S. Homayouni, Assessment of multi source data fusion methods for improvement of accuracy in urban area classification from remotely sensed data, 1998.

T. J. Hornstra, M. J. Lemmens, and G. L. Wright, Incorporating intra-pixel reflectance variability in the multispectral classification process of high-resolution satellite imagery of urbanised areas, Cartography, vol.54, issue.5, pp.1-9, 1999.
DOI : 10.1080/00690805.1999.9714313

L. Hubert-moy, Evaluation du capteur hyperspectral casi sur le bassin versant du yar (baie de lannion). rapport final de l'axe 1 du gstb " paysages et environnement, 2002.

DOI : 10.1190/1.1440721

G. R. Hunt and J. W. Salisbury, Visible and near-infrared spectra of minerals and rocks, ii. carbonates. Modern Geology, pp.23-30, 1971.

A. Hyvarinen, Survey on independent component analysis, Neural Computing Surveys, vol.2, pp.94-128, 1999.

A. Hyvarinen, E. Karhunen, and J. Oja, Independent Component Analysis, 2001.

A. Hyvarinen and E. Oja, Independent component analysis: algorithms and applications, Neural Networks, vol.13, issue.4-5, pp.411-430, 2000.
DOI : 10.1016/S0893-6080(00)00026-5

A. K. Jain and B. Chandrasekaran, Dimentionality and sample size considerations in pattern recognition practice, Handbook of Statistics, 1982.

L. M. Jensen, Classification of urban land cover based on expert systems, object models and texture, Computers, Environment and Urban Systems, vol.21, issue.3-4, pp.291-302, 1997.
DOI : 10.1016/S0198-9715(97)01004-1

X. Jia, Classification techniques for Hyperspectral Remote sensing Image Data, 1996.

X. Jia, J. F. Arnold, M. C. Carvenor, and J. A. , Richards : Data reduction techniques for remote sensing data, Proc. IREECON int, pp.136-139, 1989.

X. Jia and J. A. Richards, Segmented principal components transformation for efficient hyperspectral remote-sensing image display and classification, IEEE TRAN- SACTIONS ON GEOSCIENCE AND REMOTE SENSING, vol.37, pp.538-543, 1999.

J. Nasa, AVIRIS documaentations and application

I. Keller and J. Fischer, Details and improvements of the calibration of casi, First EARSel Workshop on Imaging Spectrometry, pp.81-88, 1998.

P. Keranen, A. Kaarna, and P. Toivanen, <title>Spectral similarity measures for classification in lossy compression of hyperspectral images</title>, Image and Signal Processing for Remote Sensing VIII, pp.285-296, 2002.
DOI : 10.1117/12.463160

N. Keshava and J. F. , Mustard : Spectral unmixing, Signal processing, vol.19, issue.1, 2002.

T. I. Konovala, Remote sensing analysis of environmental conditions in siberian cities. Mapping Sciences and Remote Sensing, pp.92-104, 1999.

F. Kruse, A. B. Lefkoff, J. W. Boardman, K. B. Heidebrecht, A. Shapiro et al., The spectral image processing system (sips) interactive visualisation and analysis of imaging spectrometer data. Remote sensing of Environment, pp.145-163, 1993.

D. Landgrebe, Information Extraction Principles and Methods for Multispectral and Hyperspectral Image Data, chapitre 1 : Information, Processing for Remote Sensing, 1999.

D. Landgrebe, Some fundamentals and methods for hyperspectral image data analysis, Systems and Technologies for Clinical Diagnostics and Drug Discovery II, pp.104-113, 1999.
DOI : 10.1117/12.346731

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

D. Landgrebe, Hyperspectral image data analysis, IEEE Signal Processing Magazine, vol.19, issue.1, pp.17-18, 2002.
DOI : 10.1109/79.974718

C. Lee and J. S. Bethel, Extraction, modelling, and use of linear features for restitution of airborne hyperspectral imagery, ISPRS Journal of Photogrammetry and Remote Sensing, vol.58, issue.5-6, pp.5-6289
DOI : 10.1016/j.isprsjprs.2003.10.003

C. Lee, H. Theiss, J. S. Bethel, and E. Mikhail, Rigorous mathematical modeling of airborne pushbroom imaging systems, PE and RS, 2000.

M. Leloglu, Dense urban dem with three or more high-resolution aerial images, ISPRS Symposium on GIS -Between Visions and Applications, 1998.

M. Lennon, Méthodes d'analyse d'images hyperspectrales Exploitation du capteur aéroporté CASI pour des applications de cartographie agro-environnementale en Bretagne, Thèse de doctorat, 2002.

T. M. Lillesand and R. W. Kiefer, Remote Sensing and Image Interpretation, 1994.

A. M. Djafari and A. , Mohammadpour : Modeling wavelenght and spatial dependency in the hyperspectral image proccessing Statistics for Dependent Data, 2005.

F. D. Meer and S. M. Jong, Imaging Spectrometry. Remote Sensing and Digital Image Processing, 2001.

F. Melgani and L. Bruzzone, Support vector machines for classification of hyperspectral remote sensing images, IGARSS, 2002.

G. Mercier, S. Derrode, and M. Lennon, Hyperspectral image segmentation with Markov chain model, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477), 2003.
DOI : 10.1109/IGARSS.2003.1295263

URL : https://hal.archives-ouvertes.fr/hal-00082591

G. Mercier and M. Lennon, Support vector machines for hyperspectral image classification with spectral-based kernels, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477), 2003.
DOI : 10.1109/IGARSS.2003.1293752

E. J. Milton, E. M. Rollin, and K. M. , Brown : Practical methodologies for the reflectance calibration of casi data, Web, vol.site

A. Mohammadpour, A. M-djafari, and O. Féron, Bayesian segmentation of hyperspectral images, AIP Conference Proceedings, pp.541-548, 2004.
DOI : 10.1063/1.1835254

URL : https://hal.archives-ouvertes.fr/hal-00447132

A. Muller, F. Lehmann, and H. Rothfub, The potential of imaging spectrometry (dais 7915) for the monitoring of recutivation activities in mining areas, Proceeding of the Eleventh Tematic Conference and workshop on applied Geologic Remote Sensing, pp.350-357, 1996.

J. M. Nascimento and J. M. Dias, Does independent component analysis play a role in unmixing hyperspectral data ? In, Pattern Recognition and Image AnalysisLecture Notes in Computer Science), pp.616-625, 2003.

E. Oja, J. Karhunen, L. Wang, and R. Vigario, Principal and independent components in neural networks -recent developments, Proc. VII Italian Workshop Neural Networks WIRN '95, pp.16-35, 1995.

N. Otsu, A Threshold Selection Method from Gray-Level Histograms, IEEE Transactions on Systems, Man, and Cybernetics, vol.9, issue.1, pp.62-66, 1979.
DOI : 10.1109/TSMC.1979.4310076

M. Pesaresi, Texture Analysis for Urban Pattern Recognition Using Fine-resolution Panchromatic Satellite Imagery, Geographical and Environmental Modelling, vol.8, issue.1, pp.43-63, 2000.
DOI : 10.1016/0034-4257(87)90015-0

J. C. Price, M. Steven, B. Andrieu, and K. Jaggard, Examples of high resolution visible to near-infrared reflectance spectra and a standardized collection for remote sensing studies, International Journal of Remote Sensing, vol.834, issue.6, pp.993-1000, 1995.
DOI : 10.1016/0034-4257(91)90002-N

M. S. Ramsey, W. L. Stefanov, and P. R. Christtensen, Monitoring world-wide land cover changes with aster : Preliminary results from the phoenix az lter site, Proceeding of international COnference on Applied Geologic Remote Sensing, pp.237-244, 1999.

M. Rast, Imaging spectroscopy and its applications in spaceborne systems, European Space Agency Publications ESA SP-114, p.114, 1991.

J. Richards and X. , Jia : Remote Sensing Digital Image Analysis, 1986.

M. K. Rid, Exploring a V-I-S (vegetation-impervious surface-soil) model for urban ecosystem analysis through remote sensing: comparative anatomy for cities???, International Journal of Remote Sensing, vol.21, issue.12, pp.2165-2185
DOI : 10.1080/01431169508954549

M. Riedmann, Labratory calibration of the casi-2. Rapport technique, School of geography

M. Riedmann and E. M. Rollin, Labroatory calibration procedure of casi-2 owned by nerc, Web, vol.site

. Ch, K. Rosenberger, and . Chehdi, Unsupervised clustering method with optimal estimation of the number of clusters : Application to image segmentation, Proc. International Conference on Pattern Recognition, 2000.

G. H. Rosenfield, Fitzpatric-Lins : A coefficient of agreement as a measure of thematic classification accuracy, Photogrammetric Engineering and Remote Sensing, vol.52, issue.2, pp.23-227, 1986.

M. Roux, M. Fradkin, and H. Ma??trema??tre, Urban areas description using multiple aerial images. SFPT Special Issue on 3D Geospatial Data Production : Meeting Application Requirements, pp.36-45, 1999.

M. Roux and H. Ma??trema??tre, Map analysis for guided interpretation of aerial images, Lecture Notes in Computer Science Graphics Recognition, Algorithms and Systems, vol.1389, pp.243-256, 1998.
DOI : 10.1007/3-540-64381-8_53

M. Roux, H. Ma??trema??tre, and S. Girard, A step towards stereo reconstruction of urban aerial images, IAPRS (Int. Ass. Photogrammetry and Remote Sensing, pp.3-4, 1997.

P. Ruiliang, M. Kelly, and G. Anderson, Gong : Considerations for using casi hyperspectral imagery to detect mortality and vegetation stress associated with a new hardwood forest disease, Computers And Electronics In Agriculture, 2004.

R. A. Ryerson, . The, . Of, 3. Sensing, and . Edition, American Society of Photogrammetry and Remote Sensing, 1999.

J. Salisoubury, L. Walter, N. Vergo, and D. , Aria : Infrared (2.1-25 micrometer) spectra of minerals, 1991.

J. Schwarz and K. Staenz, Adaptive Threshold for Spectral Matching of Hyperspectral Data, Canadian Journal of Remote Sensing, vol.24, issue.2, pp.216-224, 2001.
DOI : 10.1080/014311697218674

J. Scott, Remote Sensing :The Image chain Approach, 1997.

. Sekine, Relationship between living envirenmental and land use for a residential area in morioka city : Rs/gis analysis of spot xs data, Geographical Review of Japan, Series A, issue.2, pp.75-92, 1999.

G. M. Senseman, C. F. Bagely-et-tweddale, and S. A. , Accuracy assessment of the discrete classification of remotely sensed digital data for lancover mapping, 1995.

G. Shaw, Manolakis : Signal processing for hyperspectral image exploitation, IEEE Signal processing magazine, vol.19, issue.1, 2002.
DOI : 10.1109/79.974715

P. Shippert, Spotlight on hyperspectral, Geospatial Solutions, 2002.

D. Slater and G. Healey, Material mapping for 3d objects in arial hyperspectral images, Int. Symp. on Aerospace/Defense Sensing Simulation and Controls, 1999.

D. Slater and G. Healey, Physics-based model acquisition and identification in airborne spectral images, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001, pp.257-262, 2001.
DOI : 10.1109/ICCV.2001.937633

G. M. Smith and E. J. Milton, The use of the empirical line method to calibrate remotely sensed data to reflectance, International Journal of Remote Sensing, vol.20, issue.13, pp.2653-2662, 1999.
DOI : 10.1080/014311699211994

H. Stokman and T. Gevers, Detection and classification of hyperspectral edges, The Tenth British Machine Vision Conference, 1999.

P. H. Suen, G. Healey, and D. Slater, The impact of viewing geometry on material discriminability in hyperspectral images, IEEE Transactions on Geoscience and Remote Sensing, vol.39, issue.7, pp.438-443, 2001.
DOI : 10.1109/36.934068

P. H. Swain and S. M. Davis, Remote Sensing: The Quantitative Approach, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.3, issue.6, 1978.
DOI : 10.1109/TPAMI.1981.4767177

J. C. Tilton and W. T. Lawrence, Intractive analysis of hierarchical image segmentation, IGRASS 2000, pp.733-735, 2000.

C. Tison, Interférométrie RSOàRSOà haute résolution en milieu urbain : application au calcul de MNS urbain, Thèse de doctorat, 2004.

R. C. Tryon and D. E. Bailey, Cluster Analysis, 1970.

R. H. Yuhas, A. F. Goetz, and J. W. Boardman, Discrimination among semi-arid landscape endmembers using the spectral angle mapper (sam) algorithm, Summaries of the Third Annual JPL Airborne Geoscience Workshop, pp.147-149

S. Zinger, Interpolation et ré-´ echantillonnage de données spatiales et applicationàapplicationà la cartographie urbaine, Thèse de doctorat, 2004.