T. Abraham and J. Roddick, Survey of spatio-temporal databases, GeoInformatica, vol.3, issue.1, pp.61-99, 1999.
DOI : 10.1023/A:1009800916313

J. Adams, D. Sabol, V. Kapos, R. Almeida-filho, D. Roberts et al., Classification of multispectral images based on fractions of endmembers: Application to land-cover change in the Brazilian Amazon, Remote Sensing of Environment, vol.52, issue.2, pp.137-154, 1995.
DOI : 10.1016/0034-4257(94)00098-8

R. Agarwal, C. Aggarwal, and V. Prasad, Depth first generation of long patterns, Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '00, pp.108-118, 2000.
DOI : 10.1145/347090.347114

R. Agrawal and R. Srikant, Fast algorithms for mining association rules, Proc. 20th Int. Conf. Very Large Data Bases, VLDB, pp.487-499, 1994.

R. Agrawal and R. Srikant, Mining sequential patterns, Proceedings of the Eleventh International Conference on Data Engineering, pp.3-14, 1995.
DOI : 10.1109/ICDE.1995.380415

H. Albert-lorincz and . Jf, Mining frequent sequential patterns under regular expressions: a highly adaptative strategy for pushing constraints, 3rd SIAM Int. Conf. on Data Mining (SIAM DM'03, 2003.
DOI : 10.1137/1.9781611972733.37

J. Allen, Maintaining knowledge about temporal intervals, Communications of the ACM, vol.26, issue.11, pp.832-843, 1983.
DOI : 10.1145/182.358434

M. Armstrong, Temporality in spatial databases, Proceedings of GIS/LIS, vol.88, issue.2, pp.880-889, 1988.

L. Aurdal, R. Huseby, L. Eikvil, R. Solberg, D. Vikhamar et al., Use of hidden Markov models and phenology for multitemporal satellite image classification: applications to mountain vegetation classification, International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, 2005., pp.220-224, 2005.
DOI : 10.1109/AMTRSI.2005.1469877

N. Ayache and O. D. Faugeras, HYPER: A New Approach for the Recognition and Positioning of Two-Dimensional Objects, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.8, issue.1, pp.44-544767751, 1986.
DOI : 10.1109/TPAMI.1986.4767751

J. Ayres, J. Flannick, J. Gehrke, and T. Yiu, Sequential PAttern mining using a bitmap representation, Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '02, pp.429-435, 2002.
DOI : 10.1145/775047.775109

S. Bartalev, F. Achard, D. Erchov, and V. Gond, The potential contribution of SPOT 4/VEGETATION data for mapping Siberian forest cover at continental scale, Proceedings of Vegetation, pp.3-6, 2000.

Y. Bastide, R. Taouil, N. Pasquier, G. Stumme, and L. Lakhal, Mining frequent patterns with counting inference, ACM SIGKDD Explorations Newsletter, vol.2, issue.2, pp.66-75, 2000.
DOI : 10.1145/380995.381017

URL : https://hal.archives-ouvertes.fr/hal-00467750

B. Jr and R. Agrawal, Mining the most interesting rules, Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining, pp.145-154, 1999.

P. S. Beck, C. Atzberger, K. A. Høgda, B. Johansen, and A. K. Skidmore, Improved monitoring of vegetation dynamics at very high latitudes : A new method using modis ndvi. Remote Sensing of Environment, Belward and C. Valenzuela. Remote Sensing and Geographical Information Systems for Resource Management in Developing Countries. Kluwer Academic Print on Demand, pp.321-334, 1991.

S. Beucher and C. Lantuejoul, Use of watersheds in contour detection, International Workshop on Image Processing : Real-time Edge and Motion Detection/Estimation, 1979.

F. Bodon, A fast apriori implementation, FIMI, 2003.

E. Bolson, S. Kliman, F. Sheehan, and H. Dodge, Left ventricular segmental wall motion : a new method using local direction information, Computers in Cardiology, pp.245-248, 1980.

J. Boreczky and L. Wilcox, A hidden Markov model framework for video segmentation using audioand image features, Acoustics, Speech and Signal Processing Proceedings of the 1998 IEEE International Conference on, 1998.

C. Borgelt, Efficient implementations of apriori and eclat, Workshop of Frequent Item Set Mining Implementations, 2003.

M. Bosc, F. Heitz, J. Armspach, I. Namer, D. Gounot et al., Automatic change detection in multimodal serial mri : application to multiple sclerosis lesion evolution Motion segmentation and qualitative dynamic scene analysis from an image sequence, NeuroImage International Journal of Computer Vision, vol.20, issue.102, pp.643-656157, 1993.

S. Bouzidi, J. Berroir, and I. Herlin, A remote sensing data fusion approach to monitor agricultural areas, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170), p.1387, 1998.
DOI : 10.1109/ICPR.1998.711961

URL : https://hal.archives-ouvertes.fr/inria-00532720

S. Bouzidi, S. Belhaj, I. Herlin, and J. Berroir, An approach for land cover change detection using low spatial resolution data, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477), pp.1585-1587, 2003.
DOI : 10.1109/IGARSS.2003.1294183

URL : https://hal.archives-ouvertes.fr/inria-00527193

F. Bovolo and L. Bruzzone, A multilevel parcel-based approach to change detection in very high resolution multitemporal images, Geoscience and Remote Sensing Symposium, 2005. IGARSS '05. Proceedings. 2005 IEEE International, pp.2145-2148, 2005.

F. Bovolo and L. Bruzzone, A Theoretical Framework for Unsupervised Change Detection Based on Change Vector Analysis in the Polar Domain, IEEE Transactions on Geoscience and Remote Sensing, vol.45, issue.1, pp.218-236, 2007.
DOI : 10.1109/TGRS.2006.885408

F. Bovolo, L. Bruzzone, and S. Marchesi, A Context-Sensitive Technique Robust to Registration Noise for Change Detection in Very High Resolution Multispectral Images, IGARSS 2008, 2008 IEEE International Geoscience and Remote Sensing Symposium, pp.150-1534779305, 2008.
DOI : 10.1109/IGARSS.2008.4779305

Y. Boykov and G. Funka-lea, Graph Cuts and Efficient N-D Image Segmentation, International Journal of Computer Vision, vol.18, issue.9, pp.109-131, 2006.
DOI : 10.1007/s11263-006-7934-5

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

R. Bremond and F. Marquès, Segmentation-Based Morphological Interpolation of Partition Sequences, Mathematical Morphology and its Applications to Image and Signal Processing, pp.369-376, 1996.
DOI : 10.1007/978-1-4613-0469-2_43

S. Brin, R. Motwani, J. D. Ullman, and S. Tsur, Dynamic itemset counting and implication rules for market basket data, pp.255-264, 1997.

L. Bruzzone and D. Prieto, An adaptive parcel-based technique for unsupervised change detection, International Journal of Remote Sensing, vol.21, issue.4, pp.817-822, 2000.
DOI : 10.1080/014311600210614

L. Bruzzone and S. Serpico, An iterative technique for the detection of land-cover transitions in multitemporal remote-sensing images, IEEE Transactions on Geoscience and Remote Sensing, vol.35, issue.4, pp.858-867, 1997.
DOI : 10.1109/36.602528

D. Burdick, M. Calimlim, and J. Gehrke, MAFIA: a maximal frequent itemset algorithm for transactional databases, Proceedings 17th International Conference on Data Engineering, pp.443-452, 1998.
DOI : 10.1109/ICDE.2001.914857

A. Bykowski and C. Rigotti, A condensed representation to find frequent patterns, Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems , PODS '01, 2001.
DOI : 10.1145/375551.375604

P. Cachier and X. Pennec, 3d non-rigid registration by gradient descent on a gaussianwindowed similarity measure using convolutions, Proceedings. IEEE Workshop on, pp.182-189, 2000.
URL : https://hal.archives-ouvertes.fr/inria-00615855

T. Calders and B. Goethals, Minimal k-Free Representations of Frequent Sets, LECTURE NOTES IN COMPUTER SCIENCE, pp.71-82, 2003.
DOI : 10.1007/978-3-540-39804-2_9

J. Canny, A computational approach to edge detection, IEEE Trans. Pattern Anal. Mach. Intell, vol.8, issue.6, pp.679-698, 1986.

A. Carleer and E. Wolff, Change detection for updates of vector database through regionbased classification of VHR satellite data, Proceedings of SPIE, p.674911, 2007.

P. Ceccato, Operational early warning system using SPOT-VGT and TERRA-MODIS to predict Desert Locust outbreaks, Proceedings of the Second International SPOTVE- GETATION Users Conference (Editors. F. Veroustraete and E. Bartholomé), 2004.

L. Chang, Adaptive image region-growing, IEEE Transactions on Image Processing, vol.3, issue.6, pp.868-872, 1994.
DOI : 10.1109/83.336259

J. Chen, P. Jönsson, M. Tamura, Z. Gu, B. Matsushita et al., A simple method for reconstructing a high-quality ndvi time-series data set based on the savitzky-golay filter, pp.3-4

M. Chen, J. Park, and P. Yu, Efficient Data Mining for Path Traversal Patterns, IEEE Transactions on Knowledge and Data Engineering, vol.10, issue.122, pp.332-344209, 1998.

C. Claramunt and M. Thériault, Managing Time in GIS An Event-Oriented Approach, Proceedings of the International Workshop on Temporal Databases, pp.23-42, 1995.
DOI : 10.1007/978-1-4471-3033-8_2

P. Clarysse, D. Friboulet, and I. Magnin, Tracking geometrical descriptors on 3-D deformable surfaces: application to the left-ventricular surface of the heart, IEEE Transactions on Medical Imaging, vol.16, issue.4, pp.392-404, 1997.
DOI : 10.1109/42.611349

J. Collins and C. Woodcock, An assessment of several linear change detection techniques for mapping forest mortality using multitemporal landsat TM data, Remote Sensing of Environment, vol.56, issue.1, pp.66-77, 1996.
DOI : 10.1016/0034-4257(95)00233-2

J. B. Collins and C. E. Woodcock, Change detection using the gramm-schmidt transformation applied to mapping forest mortality. Remote Sensing of Environment, pp.267-279, 1994.

D. Comaniciu and P. Meer, Robust analysis of feature spaces : color image segmentation In Computer Vision and Pattern Recognition, IEEE Computer Society Conference on, pp.750-755, 1997.

M. D. Mura, J. Benediktsson, F. Bovolo, and L. Bruzzone, An unsupervised technique based on morphological filters for change detection in very high resolution images. Geoscience and Remote Sensing Letters, IEEE, vol.5, issue.3, pp.433-437, 2008.

M. Datcu, K. Seidel, and M. Walessa, Spatial information retrieval from remote-sensing images. i. information theoretical perspective. Geoscience and Remote Sensing, IEEE Transactions on, vol.36, issue.5, pp.1431-1445, 1998.

M. Datcu, H. Daschiel, A. Pelizzari, M. Quartulli, A. Galoppo et al., Information mining in remote sensing image archives -part a : System concepts, IEEE Transactions on Geoscience and Remote Sensing, issue.12, p.41, 2003.

G. Daughters, E. Alderman, and N. Ingels, A rational approach to the clinical detection of wall motion abnormalities, Ventricular Wall Motion, International Symposium Lausanne, pp.74-82, 1982.

K. De-beurs and G. Henebry, War, drought, and phenology: changes in the land surface phenology of Afghanistan since 1982, Journal of Land Use Science, vol.55, issue.2-3, pp.95-111, 2008.
DOI : 10.1111/j.1529-8817.2003.00784.x

K. M. De-beurs and G. M. Henebry, Land surface phenology, climatic variation, and institutional change : Analyzing agricultural land cover change in kazakhstan. Remote Sensing of Environment, pp.497-509, 2004.

L. De and . Briandais, File searching using variable length keys, AIEE-IRE, pp.295-298, 1959.

M. De-martinao, F. Causa, and S. Serpico, Classification of optical high resolution images in urban environment using spectral and textural information, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477), pp.467-469, 2003.
DOI : 10.1109/IGARSS.2003.1293811

C. De-roover, A. Herbulot, A. Gouze, E. Debreuve, M. Barlaud et al., Multimodal segmentation combining active contours and watersheds, Proceedings of the 13th European Signal Processing Conference (EUSIPCO05), 2005.

G. Delyon, F. Galland, and P. Refregier, Minimal Stochastic Complexity Image Partitioning With Unknown Noise Model, IEEE Transactions on Image Processing, vol.15, issue.10, pp.3207-3212, 2006.
DOI : 10.1109/TIP.2006.877484

URL : https://hal.archives-ouvertes.fr/hal-00079459

A. Demiriz, Asipath : A simple path mining algorithm, Proceedings of the 16th International Conference on Parallel and Distributed Computing and Systems, p.9, 2004.

N. Diehl, Object-oriented motion estimation and segmentation in image sequences, Signal Processing : Image Communication, pp.23-56, 1991.
DOI : 10.1016/0923-5965(91)90028-Z

F. Dufaux and F. Moscheni, Segmentation-based motion estimation for second generation video coding techniques. Video coding : the second generation approach, pp.219-263, 1996.

J. Duncan, P. Shi, A. Amimi, R. Constable, L. Staib et al., Toward reliable, non invasive measurement of myocardial function from 4D images, Proceedings of SPIE, p.149, 1994.

B. Dunkel and N. Soparkar, Data organization and access for efficient data mining, Proceedings 15th International Conference on Data Engineering (Cat. No.99CB36337), pp.522-529, 1999.
DOI : 10.1109/ICDE.1999.754968

P. Eisert and B. Girod, Analyzing facial expressions for virtual conferencing, IEEE Computer Graphics and Applications, vol.18, issue.5, pp.70-78, 1998.
DOI : 10.1109/38.708562

D. Filipova-racheva and M. Hall-beyer, Smoothing of ndvi time series curves for monitoring of vegetation changes in time, In Ecological Monitoring and Assessment Network National Science Meeting URL Availableonlineat, 2000.

A. Fischer, A simple model for the temporal variations of NDVI at regional scale over agricultural countries. Validation with ground radiometric measurements, International Journal of Remote Sensing, vol.46, issue.7, pp.1421-1446, 1994.
DOI : 10.1016/0034-4257(87)90051-4

A. U. Frank, Qualitative temporal reasoning in gis -ordered time scales, advances in GIS research In Proc. of th 6th Int Symp on spatial data handling, pp.20-35, 1994.

E. Fredkin, Trie memory, Communications of the ACM, vol.3, issue.9, pp.490-499, 1960.
DOI : 10.1145/367390.367400

F. Fuchs and H. Le-men, Efficient subgraph isomorphism with 'a priori' knowledge (application to 3d reconstruction of buildings for cartography), Proceedings of the Joint IAPR International Workshops on Advances in Pattern Recognition, pp.427-436, 2000.

T. Fung, An Assessment Of TM Imagery For Land-cover Change Detection, IEEE Transactions on Geoscience and Remote Sensing, vol.28, issue.4, pp.681-684, 1990.
DOI : 10.1109/TGRS.1990.572980

F. Galland, N. Bertaux, and P. Refregier, Minimum description length synthetic aperture radar image segmentation, IEEE Transactions on Image Processing, vol.12, issue.9, pp.995-1006, 2003.
DOI : 10.1109/TIP.2003.816005

URL : https://hal.archives-ouvertes.fr/hal-00079440

F. Galland, N. Bertaux, and P. Réfrégier, Multi-component image segmentation in homogeneous regions based on description length minimization: Application to speckle, Poisson and Bernoulli noise, Galton. Space, time, and the representation of geographical reality. Topoi, pp.1926-1936, 2001.
DOI : 10.1016/j.patcog.2004.10.002

M. Garofalakis, R. Rastogi, and K. Shim, SPIRIT : Sequential pattern mining with regular expression constraints, Proceedings of the international conference on very large data bases, pp.223-234, 1999.

M. Gelgon and P. Bouthemy, A region-level motion-based graph representation and labeling for tracking a spatial image partition, Pattern Recognition, vol.33, issue.4, pp.725-740, 2000.
DOI : 10.1016/S0031-3203(99)00083-7

URL : https://hal.archives-ouvertes.fr/hal-00442736

S. Geman and D. Geman, Stochastic relaxation, gibbs distributions and the bayesian restoration of images, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.6, issue.6, pp.721-741, 1984.

G. Gerig, D. Welti, C. R. Guttmann, A. C. Colchester, and G. Székely, Exploring the discrimination power of the time domain for segmentation and characterization of active lesions in serial mr data Giros. Comparison of partitions of two images for satellite image time series segmentation, Geoscience and Remote Sensing Symposium IGARSS 2006. IEEE International Conference on, pp.31-42, 1109.

J. Gonzalez, L. Holder, and D. Cook, Application of Graph-Based Concept Learning to the Predictive Toxicology Domain, Proceedings of the Predictive Toxicology Challenge Workshop, 2001.

K. Gouda and M. Zaki, Efficiently mining maximal frequent itemsets, Proceedings 2001 IEEE International Conference on Data Mining, pp.163-170, 2001.
DOI : 10.1109/ICDM.2001.989514

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

K. Gouda, M. Hassaan, and M. Zaki, Prism: A Primal-Encoding Approach for Frequent Sequence Mining, Seventh IEEE International Conference on Data Mining (ICDM 2007), pp.487-492, 2007.
DOI : 10.1109/ICDM.2007.33

S. Goward, C. Tucker, and D. Dye, North American vegetation patterns observed with the NOAA-7 advanced very high resolution radiometer, Vegetatio, vol.199, issue.1, pp.3-14, 1985.
DOI : 10.1007/BF00033449

C. Gu and M. Lee, Semantic video object segmentation and tracking using mathematical morphology and perspective motion model, IEEE International Conference on Image Processing, 1997.

E. Gudes, S. Shimony, and N. Vanetik, Discovering Frequent Graph Patterns Using Disjoint Paths, IEEE Transactions on Knowledge and Data Engineering, vol.18, issue.11, pp.1441-1456, 2006.
DOI : 10.1109/TKDE.2006.173

L. Gueguen and M. Datcu, Image time-series data mining based on the informationbottleneck principle. Geoscience and Remote Sensing, IEEE Transactions on, vol.45890557, issue.4, pp.827-838, 2006.

L. Gueguen and M. Datcu, A similarity metric for retrieval of compressed objects : Application for mining satellite image time series. Knowledge and Data Engineering, IEEE Transactions on, vol.20, issue.4, pp.562-575, 2007.

L. Gueguen and D. Men, Analysis of Satellite Image Time Series Based on Information Bottleneck, AIP Conference Proceedings, pp.367-374, 2006.
DOI : 10.1063/1.2423296

L. Guigues, Modèles multi-echelles pour la segmentation d'images, Thèse de doctorat, 2003.

J. Guo, J. Kim, and C. J. Kuo, <title>Fast and accurate moving object extraction technique for MPEG-4 object-based video coding</title>, Visual Communications and Image Processing '99, pp.1210-1221, 1999.
DOI : 10.1117/12.334628

S. Gupta and J. Prince, Stochastic models for DIV-CURL optical flow methods, IEEE Signal Processing Letters, vol.3, issue.2, pp.32-34, 1996.
DOI : 10.1109/97.484208

R. Güting, M. Böhlen, M. Erwig, C. Jensen, N. Lorentzos et al., A foundation for representing and querying moving objects, ACM Transactions on Database Systems, vol.25, issue.1, pp.1-42, 2000.
DOI : 10.1145/352958.352963

O. Hagolle, G. Dedieu, B. Mougenot, V. Debaecker, B. Duchemin et al., Correction of aerosol effects on multi-temporal images acquired with constant viewing angles: Application to Formosat-2 images, Remote Sensing of Environment, vol.112, issue.4, pp.1689-1701, 2008.
DOI : 10.1016/j.rse.2007.08.016

URL : https://hal.archives-ouvertes.fr/hal-00265400

A. Hampapur, R. Jain, and T. Weymouth, Production model based digital video segmentation, Multimedia Tools and Applications, vol.1, issue.1, pp.9-46, 1995.
DOI : 10.1007/BF01261224

J. Han, J. Pei, Y. Yin, and R. Mao, Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach, Data Mining and Knowledge Discovery, vol.8, issue.1, pp.53-87, 2004.
DOI : 10.1023/B:DAMI.0000005258.31418.83

A. Hanjalic, R. Lagendijk, and J. Biemond, Automated high-level movie segmentation for advanced video-retrieval systems, IEEE Transactions on Circuits and Systems for Video Technology, vol.9, issue.4, pp.580-588, 1999.
DOI : 10.1109/76.767124

Y. Haxhimusa and W. Kropatsch, Segmentation graph hierarchies. Structural , Syntactic, and Statistical Pattern Recognition, pp.343-351, 2004.

P. Heas and M. Datcu, Modeling trajectory of dynamic clusters in image time-series for spatio-temporal reasoning, IEEE Transactions on Geoscience and Remote Sensing, vol.43, issue.7, pp.1635-1647, 2005.
DOI : 10.1109/TGRS.2005.847791

URL : https://hal.archives-ouvertes.fr/hal-00670342

P. Heas, E. Memin, N. Papadakis, and A. Szantai, Layered Estimation of Atmospheric Mesoscale Dynamics From Satellite Imagery, IEEE Transactions on Geoscience and Remote Sensing, vol.45, issue.12, pp.4087-4104, 2007.
DOI : 10.1109/TGRS.2007.906156

URL : https://hal.archives-ouvertes.fr/hal-00596167

C. Hidber, Online association rule mining, ACM SIGMOD Record, vol.28, issue.2, pp.145-156, 1999.
DOI : 10.1145/304181.304195

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

J. Hipp, U. Guntzer, and G. Nakhaeizadeh, Mining Association Rules: Deriving a Superior Algorithm by Analyzing Today???s Approaches, LECTURE NOTES IN COMPUTER SCIENCE, pp.159-168, 2000.
DOI : 10.1007/3-540-45372-5_16

J. N. Hird and G. J. Mcdermid, Noise reduction of NDVI time series: An empirical comparison of selected techniques, Remote Sensing of Environment, vol.113, issue.1, pp.248-258686, 2001.
DOI : 10.1016/j.rse.2008.09.003

B. Holben, Characteristics of maximum-value composite images from temporal AVHRR data, International Journal of Remote Sensing, vol.7, issue.11, pp.1417-1434, 1986.
DOI : 10.1016/0034-4257(83)90053-6

L. Holder, D. Cook, and S. Djoko, Substructure discovery in the subdue system, Proc. of the AAAI Workshop on Knowledge Discovery in Databases, pp.169-180, 1994.

L. Hong and G. Chen, Segment-based stereo matching using graph cuts, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004., 1999.
DOI : 10.1109/CVPR.2004.1315016

R. Horaud and O. Monga, Vision par ordinateur : outils fondamentaux, Hermes, 1995.
URL : https://hal.archives-ouvertes.fr/inria-00590049

R. Horaud and T. Skordas, Stereo correspondence through feature grouping and maximal cliques, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.11, issue.11, pp.1168-1180, 1989.
DOI : 10.1109/34.42855

URL : https://hal.archives-ouvertes.fr/inria-00589991

B. Horn and B. Schunck, Determining optical flow, Artificial Intelligence, vol.17, issue.1-3, pp.185-203, 1981.
DOI : 10.1016/0004-3702(81)90024-2

S. L. Horowitz and T. Pavlidis, Picture Segmentation by a Tree Traversal Algorithm, Journal of the ACM, vol.23, issue.2, pp.368-388, 1976.
DOI : 10.1145/321941.321956

H. Horwitz, R. Nalepka, P. Hyde, and J. Morganstern, Estimating the proportion of objects within a single resolution element of a Multispectral Scanner, 1971.

A. Huete, A soil-adjusted vegetation index (SAVI) Remote sensing of environment (USA), 1988.

A. Huete, C. Justice, and W. Van-leeuwen, MODIS vegetation index (MOD13) algorithm theoretical basis document. Greenbelt : NASA Goddard Space Flight Centre, 1999.

P. Héas, Apprentissage bayésien de structures spatio-temporelles :application à la fouille visuelle des séries temporelles d'images satellites, Thèse de doctorat, Ecole Nationale Supérieure de l'Aéronautique et de l'Espace (SupAéro), 2005.

N. B. Ingels, C. W. Mead, G. T. Daughters, E. B. Stinson, and E. L. Alderman, A new method for assessment of left ventricular segmental wall motion, Comput. Cardiol, pp.57-78, 1978.

J. Inglada, G. Mercier, and T. Cnes, A New Statistical Similarity Measure for Change Detection in Multitemporal SAR Images and Its Extension to Multiscale Change Analysis, IEEE Transactions on Geoscience and Remote Sensing, vol.45, issue.5, pp.1432-1445, 2007.
DOI : 10.1109/TGRS.2007.893568

URL : https://hal.archives-ouvertes.fr/hal-00582539

A. Inokuchi, T. Washio, and H. Motoda, An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data, Data Mining and Knowledge Discovery, pp.13-23, 2000.
DOI : 10.1007/3-540-45372-5_2

I. Iec, Information technology -coding of audio-visual objects :visual, Doc.ISO/IEC 14496-2 Final Committee Draft, 1998.

E. Ito, M. Araki, A. Tani, M. Kanzaki, K. Saret et al., Leaf-shedding phenology in tropical seasonal forests of Cambodia estimated from NOAA satellite images, IEEE International Geoscience and Remote Sensing Symposium, pp.4331-4335, 2007.

S. Jha and N. Unni, Digital change detection of forest conversion of a dry tropical Indian forest region, International Journal of Remote Sensing, vol.43, issue.13, pp.2543-2552, 1994.
DOI : 10.1126/science.214.4522.755

X. Jing, L. Liu, C. Zhang, X. Li, Y. Li et al., The extraction of beijing main crops planting area based on time series modis ndvi reconstruction, Geoscience and Remote Sensing Symposium, 2005. IGARSS '05. Proceedings. 2005 IEEE International, pp.3020-3023, 2005.

R. John, J. Chen, N. Lu, K. Guo, C. Liang et al., Predicting plant diversity based on remote sensing products in the semi-arid region of Inner Mongolia, Remote Sensing of Environment, vol.112, issue.5
DOI : 10.1016/j.rse.2007.09.013

P. Jonsson and L. Eklundh, Seasonality extraction by function fitting to time-series of satellite sensor data, IEEE Transactions on Geoscience and Remote Sensing, vol.40, issue.8, pp.1824-1832, 2002.
DOI : 10.1109/TGRS.2002.802519

I. Jonyer, D. Cook, and L. Holder, GRAPH-BASED HIERARCHICAL CONCEPTUAL CLUSTERING, International Journal on Artificial Intelligence Tools, vol.10, issue.01n02, pp.19-43, 2002.
DOI : 10.1142/S0218213001000441

C. Jordan, Derivation of Leaf-Area Index from Quality of Light on the Forest Floor, Ecology, vol.50, issue.4, pp.663-666, 1969.
DOI : 10.2307/1936256

A. Julea, N. Méger, and P. Bolon, On mining METEOSAT and ERS multitemporal images, Proc of the 4th conference on Information Mining For Security and Intelligence, 2006.
URL : https://hal.archives-ouvertes.fr/hal-00133152

A. Julea, N. Méger, and P. Bolon, On mining pixel based evolution classes in satellite image time series, Proc of the 5th conference on Information Mining : pursuing automation of geospatial intelligence for environment and security, 2008.
URL : https://hal.archives-ouvertes.fr/hal-00520967

C. Kambhamettu and D. Goldgof, Curvature-based approach to point correspondence recovery in conformal nonrigid motion, CVGIP. Image understanding, vol.60, issue.1, pp.26-43, 1994.

T. Kanungo, B. Dom, W. Niblack, and D. Steele, A fast algorithm for mdl-based multiband image segmentation, IEEE Conf. CVPR, pp.609-616, 1994.

M. Kass, A. Witkin, and D. Terzopoulos, Snakes: Active contour models, International Journal of Computer Vision, vol.5, issue.6035, pp.321-331, 1988.
DOI : 10.1007/BF00133570

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

Y. Kaufman and D. Tanre, Atmospherically resistant vegetation index (ARVI) for EOS-MODIS, IEEE Transactions on Geoscience and Remote Sensing, vol.30, issue.2, pp.261-270, 1992.
DOI : 10.1109/36.134076

M. Kawamura, Y. Tsujiko, K. Tsujino, and T. Sakai, Time-series fire-induced forest hazard mapping using Landsat and IKONOS imageries, IEEE International IEEE International IEEE International Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004, 2004.
DOI : 10.1109/IGARSS.2004.1369733

Q. Ke and T. Kanade, A subspace approach to layer extraction, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, 1999.
DOI : 10.1109/CVPR.2001.990484

Z. M. Kedem, Pincer-search : A new algorithm for discovering the maximum frequent set, 6th Intl. Conf. Extending Database Technology, pp.105-119, 1998.

A. Klaus, M. Sormann, and K. Karner, Segment-Based Stereo Matching Using Belief Propagation and a Self-Adapting Dissimilarity Measure, 18th International Conference on Pattern Recognition (ICPR'06), pp.15-18, 2006.
DOI : 10.1109/ICPR.2006.1033

T. Knudsen and B. Olsen, Automated change detection for updates of digital map databases Photogrammetric engineering and remote sensing, pp.1289-1296, 2003.

G. Koepfler, C. Lopez, and J. M. , A Multiscale Algorithm for Image Segmentation by Variational Method, SIAM Journal on Numerical Analysis, vol.31, issue.1, pp.282-299, 1994.
DOI : 10.1137/0731015

I. Koprinska and S. Carrato, Temporal video segmentation : A survey Signal processing : Image communication, pp.477-500, 2001.

M. Kryszkiewicz, Concise representation of frequent patterns based on disjunction-free generators. Data Mining, p.305, 2001.

M. Kryszkiewicz, Concise Representations of Association Rules, LECTURE NOTES IN COMPUTER SCIENCE, pp.92-109, 2002.
DOI : 10.1007/3-540-45728-3_8

M. Kryszkiewicz and M. Gajek, Why to Apply Generalized Disjunction-Free Generators Representation of Frequent Patterns?, LECTURE NOTES IN COMPUTER SCIENCE, pp.383-392, 2002.
DOI : 10.1007/3-540-48050-1_42

M. Kuramochi and G. Karypis, Frequent subgraph discovery, Proceedings 2001 IEEE International Conference on Data Mining, pp.313-320, 2001.
DOI : 10.1109/ICDM.2001.989534

M. Kuramochi and G. Karypis, An efficient algorithm for discovering frequent subgraphs, IEEE Transactions on Knowledge and Data Engineering, vol.16, issue.9, pp.1038-1051, 2004.
DOI : 10.1109/TKDE.2004.33

E. Lambin and D. Ehrlich, The surface temperature-vegetation index space for land cover and land-cover change analysis, International Journal of Remote Sensing, vol.60, issue.3, pp.463-487, 1996.
DOI : 10.1109/TGRS.1986.289691

G. Langran, Time in geographic information systems, Geocarto International, vol.7, issue.2, 1992.
DOI : 10.1080/10106049209354371

G. Langran and N. Chrisman, A framework for temporal geographic information. Cartographica : The International Journal for Geographic Information and Geovisualization, pp.1-14, 1988.

A. Lanterman, . Schwarz, and R. Wallace, Schwarz, Wallace, and Rissanen: Intertwining Themes in Theories of Model Selection, International Statistical Review, vol.22, issue.2, pp.185-212, 2001.
DOI : 10.1109/TIT.1982.1056490

R. Laurini and D. Thompson, Fundamentals of spatial information systems, 1992.

C. , L. Men, A. Julea, M. Méger, N. Datcu et al., Radiometric evolution classification in high resolution satellite images time series, Proc of the 5th conference on Information Mining : pursuing automation of geospatial intelligence for environment and security, 2008.

Y. G. Leclerc, Constructing simple stable descriptions for image partitioning, International Journal of Computer Vision, vol.1, issue.2, pp.73-102, 1989.
DOI : 10.1007/BF00054839

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

S. Lee and H. Park, Mining Weighted Frequent Patterns from Path Traversals on Weighted Graph, IJCSNS, vol.7, issue.4, p.140, 2007.

R. Leighton, S. Wilt, and R. Lewis, Detection of Hypokinesis by a Quantitative Analysis of Left Ventricular Cineangiograms, Circulation, vol.50, issue.1, pp.121-127, 1974.
DOI : 10.1161/01.CIR.50.1.121

M. Leleu, Extraction de motifs séquentiels sous contraintes dans des données avec répétitions consécutives, 2004.

M. Leleu, C. Rigotti, J. Boulicaut, and G. Euvrard, Constraint-based mining of sequential patterns over datasets with consecutive repetitions. Lecture notes in computer science, pp.303-314, 2003.

S. Li, Inexact matching of 3D surfaces, 1990.

S. Liang, Quantitative Remote Sensing of Land Surfaces, 2005.
DOI : 10.1002/047172372X

Z. Liu, F. Huang, L. Li, and E. Wan, Dynamic monitoring and damage evaluation of flood in north-west Jilin with remote sensing, International Journal of Remote Sensing, vol.10, issue.18, pp.3669-3679, 2002.
DOI : 10.1080/01431160010006953

D. S. Lu, P. Mausel, E. S. Brondizio, and M. , Change detection of successional and mature forests based on forest stand characteristics using multitemporal TM data in the Altamira, Brazil, XXII FIG International Congress, ACSM-ASPRS Annual Conference Proceedings, 2002.

M. Ma and F. Veroustraete, Reconstructing pathfinder AVHRR land NDVI time-series data for the Northwest of China, bbaf53def60ca08343a476c8b5fcbe7 Natural Hazards and Oceanographic Processes from Satellite Data, pp.835-840, 2006.
DOI : 10.1016/j.asr.2005.08.037

R. Macleod and R. Congalton, A quantitative comparison of change-detection algorithms for monitoring eelgrass from remotely sensed data, Photogrammetric Engineering and Remote Sensing, vol.64, issue.3, pp.207-216, 1998.

S. Macomber and C. Woodcock, Mapping and monitoring conifer mortality using remote sensing in the Lake Tahoe Basin. Remote sensing of environment, pp.255-266, 1994.

H. Maitre, Le Traitement des images, 0197.

. Malingreau, Global vegetation dynamics: satellite observations over Asia, International Journal of Remote Sensing, vol.199, issue.9, pp.1121-1146, 1986.
DOI : 10.1016/0034-4257(85)90097-5

J. Mangin, Mise en correspondance d'images médicales 3D multi-modalités multiindividus pour la corrélation anatomo-fonctionnelle cérébrale, 1995.

H. Mannila, H. Toivonen, and A. Verkamo, Discovering frequent episodes in sequences, 1st Conference on Knowledge Discovery and Data Mining, pp.210-215, 1995.

H. Mannila, H. Toivonen, and A. I. Verkamo, Discovery of frequent episodes in event sequences, Data Mining and Knowledge Discovery, vol.1, issue.3, pp.259-289, 1997.
DOI : 10.1023/A:1009748302351

I. B. Marcotegui, Segmentation de séquences d'images en vue du codage, Thèse de doctorat, 1996.

F. Marques and C. Molina, Object tracking for content-based functionalities, Proceedings of SPIE, the International Society for Optical Engineering, pp.190-199, 1997.

F. Marques, B. Llorens, and A. Gasull, Prediction of image partitions using Fourier descriptors: application to segmentation-based coding schemes, IEEE Transactions on Image Processing, vol.7, issue.4, pp.529-542, 1998.
DOI : 10.1109/83.663497

F. Masseglia, F. Cathala, and P. Poncelet, The PSP approach for mining sequential patterns, PKDD '98 : Proceedings of the Second European Symposium on Principles of Data Mining and Knowledge Discovery, pp.176-184, 1998.
DOI : 10.1007/BFb0094818

A. Matheny and D. Goldgof, The use of three-and four-dimensional surface harmonics for rigid and nonrigid shape recovery and representation. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.17, issue.10, pp.967-981, 1995.

R. Mech and M. Wollborn, A noise robust method for 2D shape estimation of moving objects in video sequences considering a moving camera, Signal Processing, vol.66, issue.2, pp.203-217, 1998.
DOI : 10.1016/S0165-1684(98)00006-1

T. Meier and K. Ngan, Automatic segmentation of moving objects for video object plane generation, IEEE Transactions on Circuits and Systems for Video Technology, pp.525-538, 1998.
DOI : 10.1109/76.718500

G. Mercier, L. Hubert-moy, T. Houet, and P. Gouery, Estimation and monitoring of bare soil/vegetation ratio with SPOT VEGETATION and HRVIR, IEEE Transactions on Geoscience and Remote Sensing, vol.43, issue.2, pp.348-354, 2005.
DOI : 10.1109/TGRS.2004.841628

URL : https://hal.archives-ouvertes.fr/hal-00321791

G. Mercier, G. Moser, and S. Serpico, Conditional copula for change detection on heterogeneous SAR data, 2007 IEEE International Geoscience and Remote Sensing Symposium, 2007.
DOI : 10.1109/IGARSS.2007.4423324

F. Meyer, AN OVERVIEW OF MORPHOLOGICAL SEGMENTATION, International Journal of Pattern Recognition and Artificial Intelligence, vol.15, issue.07, pp.1089-1118, 2001.
DOI : 10.1142/S0218001401001337

F. Meyer and P. Bouthemy, Exploiting the temporal coherence of motion for linking partial spatiotemporal trajectories, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp.746-747, 1993.
DOI : 10.1109/CVPR.1993.341154

F. Meyer and P. Bouthemy, Region-based tracking using affine motion models in long image sequences, CVGIP Image Understanding, vol.60, issue.2, pp.1994-2003, 1994.

A. Moody, D. M. Johnson, F. Moscheni, S. Bhattacharjee, and M. Kunt, Land-surface phenologies from avhrr using the discrete fourier transform Spatio-temporal segmentation based on region merging, Remote Sensing of Environment IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.75, issue.209, pp.305-323897, 1998.

D. Muchoney and B. Haack, Change detection for monitoring forest defoliation. PE&RS- Photogrammetric Engineering & Remote Sensing, pp.1243-1251, 1994.

D. Mumford and J. Shah, Optimal approximations by piecewise smooth functions and associated variational problems, Communications on Pure and Applied Mathematics, vol.3, issue.5, pp.577-685, 1989.
DOI : 10.1002/cpa.3160420503

C. Munyati, Wetland change detection on the Kafue Flats, Zambia, by classification of a multitemporal remote sensing image dataset, International Journal of Remote Sensing, vol.21, issue.9, pp.1787-1806, 2000.
DOI : 10.1080/014311600209742

A. Nanopoulos and Y. Manolopoulos, Finding Generalized Path Patterns for Web Log Data Mining, LECTURE NOTES IN COMPUTER SCIENCE, pp.215-228, 2000.
DOI : 10.1007/3-540-44472-6_17

A. Neri, S. Colonnese, G. Russo, and P. Talone, Automatic moving object and background separation. Signal Process, pp.219-232, 1998.

H. T. Nguyen, M. Worring, R. Van-den, and . Boomgaard, Watersnakes: Energy-driven watershed srgmentation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.25, issue.3, pp.330-342, 2003.
DOI : 10.1109/TPAMI.2003.1182096

H. Nicolas, S. Pateux, and D. Le-guen, Minimum description length criterion and segmentation map coding for region-based video compression. Circuits and Systems for Video Technology, IEEE Transactions on, vol.11, issue.2, pp.184-198, 2001.

E. Nishimura, G. Xu, and S. Tsuji, Motion segmentation and correspondence using epipolar constraint, Proc. 1st Asian Conf. Computer Vision, pp.199-204, 1993.

J. Ohm, Core experiments on multifunctional and advanced layered coding aspects of MPEG-4 video, Doc. ISO/IEC JTC1/SC29/WG11, p.2176, 0199.

I. Olsen, Epipolar line estimation, ECCV '92 : Proceedings of the Second European Conference on Computer Vision, pp.307-311, 1992.
DOI : 10.1007/3-540-55426-2_35

L. Olsson and L. Eklundh, Fourier Series for analysis of temporal sequences of satellite sensor imagery, International Journal of Remote Sensing, vol.15, issue.18, pp.3735-3741, 1994.
DOI : 10.1016/0034-4257(81)90018-3

S. Osher and J. A. Sethian, Fronts propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulations, Journal of Computational Physics, vol.79, issue.1, pp.12-49, 1988.
DOI : 10.1016/0021-9991(88)90002-2

N. Paragios and R. Deriche, Geodesic active regions and level set methods for supervised texture segmentation, International Journal of Computer Vision, vol.46, issue.3, pp.223-247, 2002.
DOI : 10.1023/A:1014080923068

J. Park, M. Chen, and P. Yu, An effective hash-based algorithm for mining association rules, Proc. ACM-SIGMOD Int. Conf. Management of Data (SIGMOD'95), pp.175-186, 1995.

J. Park, D. Metaxas, and L. Axel, Analysis of left ventricular wall motion based on volumetric deformable models and MRI-SPAMM, Medical Image Analysis, vol.1, issue.1, pp.53-71, 1996.
DOI : 10.1016/S1361-8415(01)80005-0

J. Park, D. Metaxas, A. Young, and L. Axel, Deformable models with parameter functions for cardiac motion analysis from tagged MRI data, IEEE Transactions on Medical Imaging, vol.15, issue.3, pp.278-289, 1996.
DOI : 10.1109/42.500137

N. Pasquier, Y. Bastide, R. Taouil, and L. Lakhal, Discovering Frequent Closed Itemsets for Association Rules, Database Theory?ICDT'99, pp.398-416, 1999.
DOI : 10.1007/3-540-49257-7_25

URL : https://hal.archives-ouvertes.fr/hal-00467747

J. Pei, J. Han, and R. Mao, Closet : An efficient algorithm for mining frequent closed itemsets, proc. SIGMOD Int'l Workshop Data Mining and knowledge Discovery, pp.21-30, 2000.

J. Pei, J. Han, B. Mortazavi-asl, H. Pinto, Q. Chen et al., PrefixSpan : Mining Sequential Patterns Efficiently by Prefix-Projected Pattern, IEEE Int. Conference on Data Engineering, 2001.

A. Peng and W. Pieczynski, Adaptive Mixture Estimation and Unsupervised Local Bayesian Image Segmentation, Graphical Models and Image Processing, vol.57, issue.5, p.57
DOI : 10.1006/gmip.1995.1033

N. Pettorelli, J. O. Vik, A. Mysterud, J. Gaillard, C. J. Tucker et al., Using the satellite-derived NDVI to assess ecological responses to environmental change, Annals of the Association of American Geographers, pp.503-510, 1994.
DOI : 10.1016/j.tree.2005.05.011

URL : https://hal.archives-ouvertes.fr/hal-00427841

D. Peuquet and N. Duan, An event-based spatiotemporal data model (ESTDM) for temporal analysis of geographical data, International journal of geographical information systems, vol.21, issue.1, pp.7-24, 1995.
DOI : 10.1111/j.1467-8306.1994.tb01869.x

J. Piwowar, D. Peddle, and D. Sauchyn, Identifying Ecological Variability in Vegetation Dynamics Through Temporal Mixture Analysis, 2006 IEEE International Symposium on Geoscience and Remote Sensing, pp.3766-3769, 2006.
DOI : 10.1109/IGARSS.2006.965

A. Prakash and R. Gupta, Land-use mapping and change detection in a coal mining area - a case study in the Jharia coalfield, India, International Journal of Remote Sensing, vol.19, issue.3, pp.391-410, 1998.
DOI : 10.1080/014311698216053

J. Qi, A. Chehbouni, A. Huete, Y. Kerr, and S. Sorooshian, A modified soil adjusted vegetation index, Remote Sensing of Environment, vol.48, issue.2, pp.119-126, 1994.
DOI : 10.1016/0034-4257(94)90134-1

A. Raza, W. Kainz, and R. Sliuzas, Design and Implementation of a Temporal GIS For Monitoring Urban Land Use, Change, pp.41742-41749, 1996.

A. Raza, W. Kainz, and R. Sliuzas, Design and Implementation of a Temporal GIS for Monitoring the Urban Land Use Change, Proceedings of the Spatial Information Technology Towards, pp.417-427, 2000.

A. Renolen, History graphs : Conceptual modelling of spatiotemporal data, Proceedings of GIS Frontiers in Business and Science, 1996.

E. Reusens, Joint optimization of representation model and frame segmentation for generic video compression, Signal Processing, vol.46, issue.1, pp.105-117, 1995.
DOI : 10.1016/0165-1684(95)00075-O

D. Rey, G. Subsol, H. Delingette, N. Ayache, M. Ridd et al., Automatic detection and segmentation of evolving processes in 3D medical images: Application to multiple sclerosis, Medical Image Analysis, vol.6, issue.2, pp.163-17995, 1998.
DOI : 10.1016/S1361-8415(02)00056-7

URL : https://hal.archives-ouvertes.fr/inria-00615024

E. Rignot and J. Van-zyl, Change detection techniques for ers-1 sar data. Geoscience and Remote Sensing, IEEE Transactions on, vol.31, issue.4, pp.896-906, 1993.

J. Rissanen, Modeling by shortest data description, Automatica, vol.14, issue.5, pp.465-471, 1978.
DOI : 10.1016/0005-1098(78)90005-5

J. Rissanen, A universal prior for integers and estimation by minimum description length. The Annals of Statistics, pp.416-431, 1983.

J. Rissanen, Stochastic Complexity in Statistical Inquiry Theory, 0201.

A. Robin, S. Le-hegarat-mascle, and L. Moisan, Unsupervised subpixelic classification using coarse-resolution time series and structural information. Geoscience and Remote Sensing, IEEE Transactions on, vol.46, issue.5, pp.1359-1374, 2008.
URL : https://hal.archives-ouvertes.fr/hal-00624504

A. Robin, L. Moisan, and S. Le-hégarat-mascle, An a-contrario approach for sub-pixel change detection in satellite imagery, 2009.
URL : https://hal.archives-ouvertes.fr/hal-00399698

A. Rosenfeld, R. A. Hummel, and S. W. Zucker, Scene labeling by relaxation operations. Systems, Man and Cybernetics, IEEE Transactions on, vol.6, issue.6, pp.420-433, 1976.

P. Salembier, F. Marques, M. Pardas, J. Morros, I. Corset et al., Segmentation-based video coding system allowing the manipulation of objects. Circuits and Systems for Video Technology, IEEE Transactions on, vol.7, issue.1, pp.60-74, 1997.

A. Savasere, E. Omiecinski, and S. Navathe, An Efficient Algorithm for Mining Association Rules in Large Databases, Int. Conf. Very Large Data Bases (VLDB'95), pp.432-443, 1995.

M. Schroder, H. Rehrauer, K. Seidel, and M. Datcu, Spatial information retrieval from remote-sensing images. ii. gibbs-markov random fields. Geoscience and Remote Sensing, IEEE Transactions on, vol.36, issue.5, pp.1446-1455, 1998.

J. Settle and N. Drake, Linear mixing and the estimation of ground cover proportions, International Journal of Remote Sensing, vol.27, issue.6, pp.1159-1177, 1993.
DOI : 10.1109/36.103288

L. S. Shapiro and M. Brady, Rejecting Outliers and Estimating Errors in an Orthogonal-Regression Framework, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, vol.350, issue.1694, pp.407-439, 1995.
DOI : 10.1098/rsta.1995.0022

P. Shenoy, J. Haritsa, S. Sudarshan, G. Bhalotia, M. Bawa et al., Turbo-charging vertical mining of large databases, ACM SIGMOD Record, vol.29, issue.2, pp.22-33, 2000.
DOI : 10.1145/335191.335376

J. Shi and J. Malik, Normalized cuts and image segmentation. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.22, issue.8, pp.888-905, 2000.

A. Singh, Change detection in the tropical forest environment of northeastern India using Landsat. Remote sensing and tropical land management, pp.237-254, 1986.

P. Smits and A. Annoni, Toward specification-driven change detection, IEEE Transactions on Geoscience and Remote Sensing, vol.38, issue.3, pp.1484-1488, 2000.
DOI : 10.1109/36.843048

URL : http://publications.jrc.ec.europa.eu/repository/handle/JRC19216

R. T. Snodgrass, Theories and methods of spatio-temporal reasoning in geographic space, Temporal databases, pp.22-64, 1992.

M. Spanner, L. Pierce, S. Running, and D. Peterson, The seasonality of AVHRR data of temperate coniferous forests: Relationship with leaf area index, Remote Sensing of Environment, vol.33, issue.2, pp.97-112, 1990.
DOI : 10.1016/0034-4257(90)90036-L

R. Srikant and R. Agrawal, Mining sequential patterns: Generalizations and performance improvements, Advances in Database Technology?EDBT'96 : 5th International Conference on Extending Database Technology : Proceedings , page 3, 1996.
DOI : 10.1007/BFb0014140

D. Stewart, H. Dodge, and M. Frimer, Quantitative analysis of regional myocardial performance in coronary artery disease. Cardiovascular imaging and image processing : Theory and practice-1975, pp.217-224, 1975.

D. Suter, Motion estimation and vector splines, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition CVPR-94, pp.939-942, 1994.
DOI : 10.1109/CVPR.1994.323929

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

D. Swets, B. Reed, J. Rowland, and S. Marko, A weighted least-squares approach to temporal NDVI smoothing, Proceedings of the 1999 ASPRS Annual Conference : From Image to Information, 1999.

A. Tait and X. Zheng, Mapping Frost Occurrence Using Satellite Data, Journal of Applied Meteorology, vol.42, issue.2, pp.193-203, 2003.
DOI : 10.1175/1520-0450(2003)042<0193:MFOUSD>2.0.CO;2

J. Thirion, Image matching as a diffusion process: an analogy with Maxwell's demons, Medical Image Analysis, vol.2, issue.3, pp.243-260, 1998.
DOI : 10.1016/S1361-8415(98)80022-4

H. Toivonen, Sampling large databases for association rules, Proceedings of the International Conference on Very Large Data Bases, pp.134-145, 1996.

C. Tucker, C. Vanpraet, E. Boerwinkel, and A. Gaston, Satellite remote sensing of total dry matter production in the Senegalese Sahel, Remote Sensing of Environment, vol.13, issue.6, 1983.
DOI : 10.1016/0034-4257(83)90053-6

A. Van-dijk, S. Callis, C. Sakamoto, and W. Decker, Smoothing vegetation index profiles : an alternative method for reducing radiometric disturbance in NOAA/AVHRR data Photogrammetric engineering and remote sensing (USA), 1987.

P. F. Velleman, Definition and Comparison of Robust Nonlinear Data Smoothing Algorithms, Journal of the American Statistical Association, vol.70, issue.371, pp.609-615, 1980.
DOI : 10.1080/01621459.1980.10477521

W. Verhoef, M. Menenti, and S. Azzali, Cover A colour composite of NOAA-AVHRR-NDVI based on time series analysis (1981-1992), International Journal of Remote Sensing, vol.17, issue.2, pp.231-235, 1981.
DOI : 10.1016/0273-1177(93)90550-U

L. A. Vese and T. F. Chan, A multiphase level set framework for image segmentation using the mumford and shah model, International Journal of Computer Vision, vol.50, issue.3, pp.271-2931020874308076, 2002.
DOI : 10.1023/A:1020874308076

L. Vincent and P. Soille, Watersheds in digital spaces : an efficient algorithm based onimmersion simulations. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.13, issue.6, pp.583-598, 1991.

M. Wachowicz and R. Healey, Towards temporality in G1S, Innovations in Gis : Selected Papers from the First National Conference on Gis Research Uk, p.105, 1994.

C. Wallace and P. Freeman, Single-factor analysis by minimum message length estimation, Journal of the Royal Statistical Society, B, vol.54, issue.1, pp.195-209, 1992.

V. Walter, Object-based classification of remote sensing data for change detec- tion, ISPRS Journal of Photogrammetry and Remote Sensing, vol.58, issue.2, pp.3-4225, 2004.

D. Wang, Unsupervised video segmentation based on watersheds and temporal tracking, IEEE Transactions on Circuits and Systems for Video Technology, vol.8, issue.5, pp.539-546, 1998.
DOI : 10.1109/76.718501

F. Wang, A knowledge-based vision system for detecting land changes at urban fringes, IEEE Transactions on Geoscience and Remote Sensing, vol.31, issue.1, pp.136-145, 1993.
DOI : 10.1109/36.210454

J. Wang and E. Adelson, Representing moving images with layers, IEEE Transactions on Image Processing, vol.3, issue.5, pp.625-638, 1994.
DOI : 10.1109/83.334981

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

J. Wang, J. Han, and J. Pei, CLOSET+, Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '03, pp.236-245, 2003.
DOI : 10.1145/956750.956779

Q. Wang, M. Watanabe, S. Hayashi, and S. Murakami, Using NOAA AVHRR data to assess flood damage in China, Environmental Monitoring and Assessment, vol.82, issue.2, pp.119-148, 2003.
DOI : 10.1023/A:1021898531229

R. Weismiller, S. Kristof, D. Scholz, P. Anuta, S. Momin et al., Change detection in coastal zone environments(by Landsat MSS data analysis), Photogrammetric Engineering and Remote Sensing, vol.43, pp.1533-1539, 1977.

M. Worboys, A model for spatio-temporal information, Proceedings of the 5th International Symposium on Spatial Data Handling, pp.602-611, 1992.

M. Worboys, A Unified Model for Spatial and Temporal Information, The Computer Journal, vol.37, issue.1, pp.26-34, 1994.
DOI : 10.1093/comjnl/37.1.26

M. Worboys, H. Hearnshaw, and D. Maguire, Object-oriented data modelling for spatial databases, International journal of geographical information systems, vol.54, issue.4, pp.369-383, 1990.
DOI : 10.1080/02693798708927791

Z. Wu and R. Leahy, An optimal graph theoretic approach to data clustering : theory and its application to image segmentation. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.15, issue.11, pp.1101-1113, 1993.

J. Xiao and M. Shah, Motion layer extraction in the presence of occlusion using graph cuts, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.27, issue.10, pp.1644-1659, 2005.
DOI : 10.1109/TPAMI.2005.202

G. Xu, E. Nishimura, and S. Tsuji, Image correspondence and segmentation by epipolar lines : Theory, algorithm and applications, 1993.

Y. Lemeur, Segmentation multitemporelle d'une séquence d'images spot,MsC thesis. Master's thesis, INPG, 2004.

M. Yuan, Use of a Three-Domain Repesentation to Enhance GIS Support for Complex Spatiotemporal Queries, Transactions in GIS, vol.3, issue.2, pp.137-159, 1999.
DOI : 10.1111/1467-9671.00012

R. Zabih, J. Miller, and K. Mai, A feature-based algorithm for detecting and classifying scene breaks, Proceedings of the third ACM international conference on Multimedia , MULTIMEDIA '95, pp.189-200, 1995.
DOI : 10.1145/217279.215266

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

M. Zaki, Sequence mining in categorical domains, Proceedings of the ninth international conference on Information and knowledge management , CIKM '00, pp.422-429, 2000.
DOI : 10.1145/354756.354849

M. Zaki, SPADE : An Efficient Algorithm for Mining Frequent Sequences, Machine Learning, pp.31-60, 2001.

M. Zaki, Efficient enumeration of frequent sequences, Proceedings of the seventh international conference on Information and knowledge management , CIKM '98, pp.68-75, 1998.
DOI : 10.1145/288627.288643

M. Zaki, Generating non-redundant association rules, Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '00, pp.34-43
DOI : 10.1145/347090.347101

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

M. Zaki and K. Gouda, Fast vertical mining using diffsets, Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '03, pp.326-335, 2003.
DOI : 10.1145/956750.956788

M. Zaki, S. Parthasarathy, M. Ogihara, and W. Li, New algorithms for fast discovery of association rules, 3rd Intl. Conf. on Knowledge Discovery and Data Mining, 1997.

M. J. Zaki, Scalable algorithms for association mining, IEEE Transactions on Knowledge and Data Engineering, vol.12, issue.3, pp.372-390, 2000.
DOI : 10.1109/69.846291

H. Zhang, A. Kankanhalli, and S. Smoliar, Automatic partitioning of full-motion video, Readings in Multimedia Computing and Networking, 1993.
DOI : 10.1007/BF01210504

X. Zhang, M. Friedl, C. Schaaf, A. Strahler, J. Hodges et al., Monitoring vegetation phenology using MODIS, Remote Sensing of Environment, vol.84, issue.3, pp.471-475, 2003.
DOI : 10.1016/S0034-4257(02)00135-9

Z. Zhang, R. Deriche, O. Faugeras, and Q. Luong, A robust technique for matching two uncalibrated images through the recovery of the unknown epipolar geometry, Artificial Intelligence, vol.78, issue.1-2, pp.87-119, 1995.
DOI : 10.1016/0004-3702(95)00022-4

URL : https://hal.archives-ouvertes.fr/inria-00074398

C. Zhu, T. S. Lee, and A. L. Yuille, Region competition: unifying snakes, region growing, energy/Bayes/MDL for multi-band image segmentation, Proceedings of IEEE International Conference on Computer Vision, p.416, 1995.
DOI : 10.1109/ICCV.1995.466909

L. Men, H. Maître, and M. Datcu, Spatio-Temporal Segmentation of Satellite Image Time Series, CNES-DLR -CCT workshop, 2008.
URL : https://hal.archives-ouvertes.fr/pastel-00658159

L. Men, A. Julea, N. Méger, M. Datcu, P. Bolon et al., Radiometric evolution classification in high resolution Satellite Image Time Series (STIS), In ESA-EUSC on Image Information Mining : pursuing automation of geospatial intelligence for environment and security, 2008.

L. Men, H. Maître, and M. Datcu, Minimum Description Length principle applied to the segmentation of High Resolution Satellite Image Time Serie, In ESA-EUSC on Image Information Mining : pursuing automation of geospatial intelligence for environment and security, 2008.

L. Men and M. Datcu, Hierarchical concept for reasoning on segmentations of Satellite Image Time Series : first result, ESA-EUSC on Image Information Mining for Security and Intelligence, Torrejon air base -Madrid (Spain), 2006.

C. Gueguen, M. Le-men, and . Datcu, Analysis of Satellite Image Time Series based on Information Bottleneck In 26 th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, 2006.

A. Stis-acquise-par-la-constellation and . Spot, et 4) dans le cadre du projet d'Assimilation de Données pour l'Agro-Modélisation, pp.42-49

A. Ce-terme-fait-référence-À-la-propriété-apriori, et à l'algorithme de recherche de motifs fréquents qui en découle. La propriété stipule qu'aucun motif couvrant d'un motif non-fréquent n'est fréquent. Voire A.3.1 pour une description de l'algorithme, p.104