H. G. Akcay and S. Aksoy, Automatic Detection of Geospatial Objects Using Multiple Hierarchical Segmentations, IEEE Transactions on Geoscience and Remote Sensing, vol.46, issue.7, pp.2097-2111, 2008.
DOI : 10.1109/TGRS.2008.916644

A. Alonso-gonzález, S. Valero, J. Chanussot, C. López-martinez, and P. Salembier, Processing Multidimensional SAR and Hyperspectral Images With Binary Partition Tree, Proceedings of the IEEE, pp.723-747, 2012.
DOI : 10.1109/JPROC.2012.2205209

N. S. Anders, A. C. Seijmonsbergen, and W. Bouten, Segmentation optimization and stratified object-based analysis for semi-automated geomorphological mapping, Remote Sensing of Environment, vol.115, issue.12, pp.2976-2985, 2011.
DOI : 10.1016/j.rse.2011.05.007

M. Baatz and A. Schape, Multiresolution segmentation?An optimization approach for high quality multi-scale image segmentation, Angewandte Geographische Informationsverarbeitung Symposium, pp.12-23, 2000.

K. Bahirat, F. Bovolo, L. Bruzzone, and S. Chaudhuri, A Novel Domain Adaptation Bayesian Classifier for Updating Land-Cover Maps With Class Differences in Source and Target Domains, IEEE Transactions on Geoscience and Remote Sensing, vol.50, issue.7, pp.2810-2826, 2012.
DOI : 10.1109/TGRS.2011.2174154

J. Barlow, S. Franklin, and Y. Martin, High Spatial Resolution Satellite Imagery, DEM Derivatives, and Image Segmentation for the Detection of Mass Wasting Processes, Photogrammetric Engineering & Remote Sensing, vol.72, issue.6, pp.687-692, 2006.
DOI : 10.14358/PERS.72.6.687

J. A. Benediktsson, L. Bruzzone, J. Chanussot, D. Mura, M. Salembier et al., Hierarchical Analysis of Remote Sensing Data: Morphological Attribute Profiles and Binary Partition Trees, Proceedings of the International Symposium on Mathematical Morphology ? ISMM, pp.306-319, 2011.
DOI : 10.1109/TIP.2005.854491

URL : https://hal.archives-ouvertes.fr/hal-00696056

J. A. Benediktsson, J. Chanussot, and W. Moon, Very High-Resolution remote sensing: Challenges and opportunities, Proceedings of the IEEE, 1907.

U. C. Benz, P. Hofmann, G. Willhauck, I. Lingenfelder, and M. Heynen, Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information, ISPRS Journal of Photogrammetry and Remote Sensing, vol.58, issue.3-4, pp.239-258, 2004.
DOI : 10.1016/j.isprsjprs.2003.10.002

T. Blaschke, Object based image analysis for remote sensing, ISPRS Journal of Photogrammetry and Remote Sensing, vol.65, issue.1, pp.2-16, 2010.
DOI : 10.1016/j.isprsjprs.2009.06.004

L. Bruzzone, D. Prieto, and S. Serpico, A neural-statistical approach to multitemporal and multisource remote-sensing image classification, IEEE Transactions on Geoscience and Remote Sensing, vol.37, issue.3, pp.1350-1359, 1999.
DOI : 10.1109/36.763299

Y. L. Chang, L. S. Liang, C. C. Han, J. P. Fang, W. Y. Liang et al., Multisource Data Fusion for Landslide Classification Using Generalized Positive Boolean Functions, IEEE Transactions on Geoscience and Remote Sensing, vol.45, issue.6, pp.1697-1708, 2007.
DOI : 10.1109/TGRS.2007.895832

D. Comaniciu and P. Meer, Mean shift: a robust approach toward feature space analysis, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.24, issue.5, pp.603-619, 2002.
DOI : 10.1109/34.1000236

URL : http://nichol.as/papers/Comaniciu/Mean%20Shift:%20A%20Robust%20Approach%20Toward.pdf

R. Congalton, A review of assessing the accuracy of classifications of remotely sensed data, Remote Sensing of Environment, vol.37, issue.1, pp.35-46, 1991.
DOI : 10.1016/0034-4257(91)90048-B

I. Daumé, H. Marcu, and D. , Domain adaptation for statistical classifiers, Journal of Artificial Intelligence Research, vol.26, pp.101-126, 2006.

F. Fiorucci, M. Cardinali, R. Carlà, M. Rossi, A. C. Mondini et al., Seasonal landslide mapping and estimation of landslide mobilization rates using aerial and satellite images, Geomorphology, vol.129, issue.1-2, pp.59-70, 2011.
DOI : 10.1016/j.geomorph.2011.01.013

R. Gaetano, G. Scarpa, and G. Poggi, Hierarchical Texture-Based Segmentation of Multiresolution Remote-Sensing Images, IEEE Transactions on Geoscience and Remote Sensing, vol.47, issue.7, pp.2129-2141, 2009.
DOI : 10.1109/TGRS.2008.2010708

M. Galli, F. Ardizzone, M. Cardinali, F. Guzzetti, and P. Reichenbach, Comparing landslide inventory maps, Geomorphology, vol.94, issue.3-4, pp.268-289, 2008.
DOI : 10.1016/j.geomorph.2006.09.023

L. Garrido, P. Salembier, and D. Garcia, Extensive operators in partition lattices for image sequence analysis, Signal Processing, vol.66, issue.2, pp.157-180, 1998.
DOI : 10.1016/S0165-1684(98)00004-8

F. Guzzetti, A. C. Mondini, M. Cardinali, F. Fiorucci, M. Santangelo et al., Landslide inventory maps: New tools for an old problem, Earth-Science Reviews, vol.112, issue.1-2, pp.42-66, 2012.
DOI : 10.1016/j.earscirev.2012.02.001

URL : https://doi.org/10.1016/j.earscirev.2012.02.001

D. Hölbling, P. Füreder, F. Antolini, F. Cigna, N. Casagli et al., A Semi-Automated Object-Based Approach for Landslide Detection Validated by Persistent Scatterer Interferometry Measures and Landslide Inventories, Remote Sensing, vol.11, issue.142, pp.1310-1336, 2012.
DOI : 10.5194/nhess-11-865-2011

P. Kayastha, M. R. Dhital, and F. De-smedt, Application of the analytical hierarchy process (AHP) for landslide susceptibility mapping: A case study from the Tinau watershed, west Nepal, Computers & Geosciences, vol.52, pp.398-408, 2013.
DOI : 10.1016/j.cageo.2012.11.003

C. Kurtz, N. Passat, P. Gançarski, and A. Puissant, Multi-resolution region-based clustering for urban analysis, International Journal of Remote Sensing, vol.1, issue.22, pp.5941-5973, 2010.
DOI : 10.1109/LGRS.2009.2020825

URL : https://hal.archives-ouvertes.fr/hal-01694411

C. Kurtz, N. Passat, P. Gançarski, and A. Puissant, Extraction of complex patterns from multiresolution remote sensing images: A hierarchical top-down methodology, Pattern Recognition, vol.45, issue.2, pp.685-706, 2012.
DOI : 10.1016/j.patcog.2011.07.017

URL : https://hal.archives-ouvertes.fr/hal-01694409

C. Kurtz, N. Passat, A. Puissant, and P. Gançarski, Hierarchical Segmentation of Multiresolution Remote Sensing Images, Proceedings of the International Symposium on Mathematical Morphology ? ISMM, pp.343-354, 2011.
DOI : 10.1109/TIP.2008.2002841

URL : https://hal.archives-ouvertes.fr/hal-01718349

T. Lahousse, K. T. Chang, and Y. H. Lin, Landslide mapping with multi-scale object-based image analysis ??? a case study in the Baichi watershed, Taiwan, Natural Hazards and Earth System Science, vol.11, issue.10, pp.2715-2726, 2011.
DOI : 10.5194/nhess-11-2715-2011

P. Lu, A. Stumpf, N. Kerle, and N. Casagli, Object-Oriented Change Detection for Landslide Rapid Mapping, IEEE Geoscience and Remote Sensing Letters, vol.8, issue.4, pp.701-705, 2011.
DOI : 10.1109/LGRS.2010.2101045

F. De-lussy, P. Kubik, D. Greslou, V. Pascal, P. Gigord et al., PLEIADES-HR image system products and geometric accuracy, Proceedings of the ISPRS Hannover Workshop on High-Resolution Earth Imaging for Geospatial Information ? WHREI, pp.50-57, 2005.

J. B. Macqueen, Some methods of classification and analysis of multivariate observations, Proceedings of the Berkeley Symposium on Mathematical Statistics and Probability ? BSMSP, pp.281-297, 1967.

J. P. Malet, D. Laigle, A. Remaître, and O. Maquaire, Triggering conditions and mobility of debris flows associated to complex earthflows, Geomorphology, vol.66, issue.1-4, pp.215-235, 2005.
DOI : 10.1016/j.geomorph.2004.09.014

URL : https://hal.archives-ouvertes.fr/hal-01132503

G. Mallinis, N. Koutsias, M. Tsakiri-strati, and M. Karteris, Object-based classification using Quickbird imagery for delineating forest vegetation polygons in a Mediterranean test site, ISPRS Journal of Photogrammetry and Remote Sensing, vol.63, issue.2, pp.237-250, 2008.
DOI : 10.1016/j.isprsjprs.2007.08.007

T. R. Martha, N. Kerle, V. Jetten, C. J. Van-westen, and K. V. Kumar, Characterising spectral, spatial and morphometric properties of landslides for semi-automatic detection using object-oriented methods, Geomorphology, vol.116, issue.1-2, pp.24-36, 2010.
DOI : 10.1016/j.geomorph.2009.10.004

T. R. Martha, N. Kerle, C. J. Van-westen, V. Jetten, and K. V. Kumar, Object-oriented analysis of multi-temporal panchromatic images for creation of historical landslide inventories, ISPRS Journal of Photogrammetry and Remote Sensing, vol.67, pp.105-119, 2012.
DOI : 10.1016/j.isprsjprs.2011.11.004

T. R. Martha and K. V. Kumar, landslide events in Okhimath, India ? An assessment of landslide consequences using very high resolution satellite data, pp.469-479, 2012.

A. C. Mondini, F. Guzzetti, P. Reichenbach, M. Rossi, M. Cardinali et al., Semi-automatic recognition and mapping of rainfall induced shallow landslides using optical satellite images, Remote Sensing of Environment, vol.115, issue.7, pp.1743-1757, 2011.
DOI : 10.1016/j.rse.2011.03.006

A. C. Mondini, I. Marchesini, M. Rossi, K. T. Chang, G. Pasquariello et al., Bayesian framework for mapping and classifying shallow landslides exploiting remote sensing and topographic data. Geomorphology (In press), 2013.
DOI : 10.1016/j.geomorph.2013.06.015

J. Nichol and M. S. Wong, Satellite remote sensing for detailed landslide inventories using change detection and image fusion, International Journal of Remote Sensing, vol.24, issue.9, pp.1913-1926, 2005.
DOI : 10.1080/01431160010014260

URL : http://hdl.handle.net/10397/15185

F. Petitjean and P. Gançarski, Summarizing a set of time series by averaging: From Steiner sequence to compact multiple alignment, Theoretical Computer Science, vol.414, issue.1, pp.76-91, 2012.
DOI : 10.1016/j.tcs.2011.09.029

F. Petitjean, J. Inglada, and P. Gançarski, Satellite Image Time Series Analysis Under Time Warping, IEEE Transactions on Geoscience and Remote Sensing, vol.50, issue.8, pp.3081-3095, 2012.
DOI : 10.1109/TGRS.2011.2179050

URL : https://hal.archives-ouvertes.fr/hal-00940767

F. Petitjean, A. Ketterlin, and P. Gançarski, A global averaging method for dynamic time warping, with applications to clustering, Pattern Recognition, vol.44, issue.3, pp.678-693, 2011.
DOI : 10.1016/j.patcog.2010.09.013

F. Petitjean, C. Kurtz, N. Passat, and P. Gançarski, Spatio-temporal reasoning for the classification of satellite image time series, Pattern Recognition Letters, vol.33, issue.13, pp.1805-1815, 2012.
DOI : 10.1016/j.patrec.2012.06.009

URL : https://hal.archives-ouvertes.fr/hal-00636814

D. Raucoules, M. De-michele, J. P. Malet, and P. Ulrich, Time-variable 3D ground displacements from high-resolution synthetic aperture radar (SAR). application to La Valette landslide (South French Alps), Remote Sensing of Environment, vol.139, pp.198-204, 2013.
DOI : 10.1016/j.rse.2013.08.006

URL : https://hal.archives-ouvertes.fr/hal-00863822

H. Sakoe and S. Chiba, Dynamic programming algorithm optimization for spoken word recognition, IEEE Transactions on Acoustics, Speech, and Signal Processing, vol.26, issue.1, pp.43-49, 1978.
DOI : 10.1109/TASSP.1978.1163055

P. Salembier and L. Garrido, Binary partition tree as an efficient representation for image processing, segmentation, and information retrieval, IEEE Transactions on Image Processing, vol.9, issue.4, pp.561-576, 2000.
DOI : 10.1109/83.841934

URL : http://gps-tsc.upc.es/imatge/pub/ps/IEEE_IP00_Salembier_Garrido.pdf

P. Salembier and M. H. Wilkinson, Connected operators, IEEE Signal Processing Magazine, vol.26, issue.6, pp.136-157, 2009.
DOI : 10.1109/MSP.2009.934154

URL : http://arxiv.org/pdf/1710.04476

A. Stumpf and N. Kerle, Object-oriented mapping of landslides using Random Forests, Remote Sensing of Environment, vol.115, issue.10, pp.2564-2577, 2011.
DOI : 10.1016/j.rse.2011.05.013

A. Stumpf, N. Lachiche, J. P. Malet, and A. Puissant, Active Learning in the Spatial Domain for Remote Sensing Image Classification, IEEE Transactions on Geoscience and Remote Sensing, vol.52, issue.5, 2013.
DOI : 10.1109/TGRS.2013.2262052

W. Sun, V. Heidt, P. Gong, and G. Xu, Information fusion for rural land-use classification with High-Resolution satellite imagery, IEEE Transactions on Geoscience and Remote Sensing, vol.41, pp.883-890, 2003.

Y. Thiery, J. P. Malet, S. Sterlacchini, A. Puissant, and O. Maquaire, Landslide susceptibility assessment by bivariate methods at large scales: Application to a complex mountainous environment, Geomorphology, vol.92, issue.1-2, pp.38-59, 2007.
DOI : 10.1016/j.geomorph.2007.02.020

URL : https://hal.archives-ouvertes.fr/hal-00276804

J. R. Townshend, C. Huang, S. N. Kalluri, R. S. Defries, S. Liang et al., Beware of per-pixel characterization of land cover, International Journal of Remote Sensing, vol.21, issue.4, pp.839-843, 2000.
DOI : 10.1080/014311600210641

S. Valero, P. Salembier, and J. Chanussot, New hyperspectral data representation using binary partition tree, 2010 IEEE International Geoscience and Remote Sensing Symposium, pp.80-83, 2010.
DOI : 10.1109/IGARSS.2010.5649780

URL : https://hal.archives-ouvertes.fr/hal-00578960

C. Wemmert, A. Puissant, G. Forestier, and P. Gançarski, Multiresolution Remote Sensing Image Clustering, IEEE Geoscience and Remote Sensing Letters, vol.6, issue.3, pp.533-537, 2009.
DOI : 10.1109/LGRS.2009.2020825

URL : https://hal.archives-ouvertes.fr/halshs-00520632

J. D. Wood, The geomorphological characterisation of digital elevation models, 1996.

I. Yilmaz, Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: A case study from Kat landslides (Tokat???Turkey), Computers & Geosciences, vol.35, issue.6, pp.1125-1138, 2009.
DOI : 10.1016/j.cageo.2008.08.007