A. Abellán, J. M. Vilaplana, and J. Martínez, Application of a long-range terrestrial laser scanner to a detailed rockfall study at vall de núria (eastern pyrenees, spain) Engineering Geology, pp.3-4136, 2006.

A. Abellán, J. Calvet, J. M. Vilaplana, and J. Blanchard, Detection and spatial prediction of rockfalls by means of terrestrial laser scanner monitoring, Geomorphology, vol.119, issue.3-4, pp.3-4162, 2010.
DOI : 10.1016/j.geomorph.2010.03.016

A. S. Antonarakis, K. S. Richards, and J. Brasington, Object-based land cover classification using airborne LiDAR, Remote Sensing of Environment, vol.112, issue.6, pp.2988-2998, 2008.
DOI : 10.1016/j.rse.2008.02.004

A. S. Antonarakis, K. S. Richards, J. Brasington, and M. Bithell, Leafless roughness of complex tree morphology using terrestrial lidar, Water Resources Research, vol.133, issue.2, p.10401, 2009.
DOI : 10.1029/2008WR007666

A. S. Antonarakis, K. S. Richards, J. Brasington, and E. Muller, Determining leaf area index and leafy tree roughness using terrestrial laser scanning, Water Resources Research, vol.133, issue.2, pp.1-12, 2010.
DOI : 10.1029/2009WR008318
URL : http://cadair.aber.ac.uk/dspace/bitstream/2160/6791/2/Determining_leaf_area_index_and_leafy_tree_roughness_using_terrestrial_laser_scanning.pdf

S. Barnea, S. Filin, and V. Alchanatis, A supervised approach for object extraction from terrestrial laser point clouds demonstrated on trees. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, pp.135-140, 2007.

B. Boser, I. Guyon, and V. Vapnik, A training algorithm for optimal margin classifiers, Proceedings of the fifth annual workshop on Computational learning theory , COLT '92, pp.144-152, 1992.
DOI : 10.1145/130385.130401

P. A. Burrough, Fractal dimensions of landscapes and other environmental data, Nature, vol.28, issue.5838, pp.240-242, 1981.
DOI : 10.1038/294240a0

M. Carlberg, P. Gao, G. Chen, and A. Zakhor, Classifying urban landscape in aerial LiDAR using 3D shape analysis, 2009 16th IEEE International Conference on Image Processing (ICIP), pp.1701-1704, 2009.
DOI : 10.1109/ICIP.2009.5413385

M. Dalponte, L. Bruzzone, and D. Gianelle, Fusion of Hyperspectral and LIDAR Remote Sensing Data for Classification of Complex Forest Areas, IEEE Transactions on Geoscience and Remote Sensing, vol.46, issue.5, pp.1416-1427, 2008.
DOI : 10.1109/TGRS.2008.916480

M. Franceschi, G. Teza, N. Preto, A. Pesci, A. Galgaro et al., Discrimination between marls and limestones using intensity data from terrestrial laser scanner, ISPRS Journal of Photogrammetry and Remote Sensing, vol.64, issue.6, pp.522-528, 2009.
DOI : 10.1016/j.isprsjprs.2009.03.003

D. Girardeau-montaut, Cloudcompare, a 3d point cloud and mesh processing free software, 2011.

]. A. Guarnieri, A. Vettore, F. Pirotti, M. Menenti, and M. Marani, Retrieval of small-relief marsh morphology from Terrestrial Laser Scanner, optimal spatial filtering, and laser return intensity, Geomorphology, vol.113, issue.1-2, pp.12-20, 2009.
DOI : 10.1016/j.geomorph.2009.06.005

H. Hasegawa, Evaluations of lidar reflectance amplitude sensitivity towards land cover conditions, Bulletin of the Geographical Survey Institute (Japan), vol.53, issue.6, pp.43-50, 2006.

G. L. Heritage and D. J. Milan, Terrestrial Laser Scanning of grain roughness in a gravel-bed river, Geomorphology, vol.113, issue.1-2, pp.4-11, 2009.
DOI : 10.1016/j.geomorph.2009.03.021

R. Hodge, J. Brasington, and K. Richards, Analysing laser-scanned digital terrain models of gravel bed surfaces: linking morphology to sediment transport processes and hydraulics, -situ characterisation of grainscale fluvial morphology using terrestrial laser scanning. Earth Surface Processes and Landforms, pp.2024-2043, 2009.
DOI : 10.1111/j.1365-3091.2009.01068.x

B. Hofle and N. Pfeifer, Correction of laser scanning intensity data: Data and model-driven approaches, ISPRS Journal of Photogrammetry and Remote Sensing, vol.62, issue.6, pp.415-433, 2007.
DOI : 10.1016/j.isprsjprs.2007.05.008

S. Kaasalainen, A. Jaakkola, M. Kaasalainen, A. Krooks, and A. Kukko, Analysis of Incidence Angle and Distance Effects on Terrestrial Laser Scanner Intensity: Search for Correction Methods, Remote Sensing, vol.3, issue.12, pp.2207-2221, 2011.
DOI : 10.3390/rs3102207

E. Kim and G. Medioni, Urban scene understanding from aerial and ground LIDAR data, Machine Vision and Applications, vol.44, issue.9, pp.691-703, 2011.
DOI : 10.1007/s00138-010-0279-7

D. E. King, Dlib-ml: A machine learning toolkit, Journal of Machine Learning Research, vol.10, pp.1755-1758, 2009.

R. Labourdette and R. R. Jones, Characterization of fluvial architectural elements using a three-dimensional outcrop data set: Escanilla braided system, South-Central Pyrenees, Spain, Geosphere, vol.3, issue.6, pp.422-434, 2007.
DOI : 10.1130/GES00087.S3

J. Lalonde, N. Vandapel, D. F. Huber, and M. Hebert, Natural terrain classification using three-dimensional ladar data for ground robot mobility, Journal of Field Robotics, vol.59, issue.10, pp.839-861, 2006.
DOI : 10.1002/rob.20134

D. D. Lichti, Spectral filtering and classification of terrestrial laser scanner point clouds. The Photogrammetric Record, pp.218-240, 2005.

D. D. Lichti, Error modelling, calibration and analysis of an AM???CW terrestrial laser scanner system, ISPRS Journal of Photogrammetry and Remote Sensing, vol.61, issue.5, pp.61307-324, 2007.
DOI : 10.1016/j.isprsjprs.2006.10.004

E. Hui, L. , and D. Suter, 3d terrestrial lidar classifications with super-voxels and multi-scale conditional random fields, Computer-Aided Design, vol.41, issue.10, pp.701-710, 2009.

T. Maszczyk and W. Duch, Support Vector Machines for Visualization and Dimensionality Reduction, Proceeding of the International Conference on Artificial Neural Networks, pp.346-356, 2008.
DOI : 10.1007/978-3-540-87536-9_36

D. J. Milan, G. L. Heritage, A. R. Large, and N. S. Entwistle, Mapping hydraulic biotopes using terrestrial laser scan data of water surface properties, Earth Surface Processes and Landforms, pp.918-931, 2010.
DOI : 10.1002/esp.1948

D. J. Milan, G. L. Heritage, and D. Hetherington, Application of a 3D laser scanner in the assessment of erosion and deposition volumes and channel change in a proglacial river, Earth Surface Processes and Landforms, pp.1657-1674, 2007.
DOI : 10.1002/esp.1592

S. Nagihara, K. R. Mulligan, and W. Xiong, Use of a three-dimensional laser scanner to digitally capture the topography of sand dunes in high spatial resolution, Earth Surface Processes and Landforms, vol.29, issue.3, pp.391-398, 2004.
DOI : 10.1002/esp.1026

J. M. Nield, G. F. Wiggs, and R. S. Squirrell, Aeolian sand strip mobility and protodune development on a drying beach: examining surface moisture and surface roughness patterns measured by terrestrial laser scanning, Earth Surface Processes and Landforms, pp.513-522, 2011.
DOI : 10.1002/esp.2071

A. Pesci and G. Teza, Effects of surface irregularities on intensity data from laser scanning: an experimental approach, Annals of Geophysics, vol.51, pp.5-6839, 2008.

C. John and . Platt, Probabilistic Outputs for Support Vector Machines and Comparisons to Regularized Likelihood Methods, pp.61-74, 1999.

A. Rabatel, P. Deline, S. Jaillet, and L. , Rock falls in high-alpine rock walls quantified by terrestrial lidar measurements: A case study in the Mont Blanc area, Geophysical Research Letters, vol.38, issue.116, p.35, 2008.
DOI : 10.1029/2008GL033424
URL : https://hal.archives-ouvertes.fr/halsde-00292415

F. Renard, C. Voisin, D. Marsan, J. Schmittbuhl, and R. J. Allison, High resolution 3d laser scanner measurements of a strike-slip fault quantify its morphological anisotropy at all scales Terrestrial laser scanning for monitoring the process of hard rock coastal cliff erosion, Geophysical Research Letters Quarterly Journal of Engineering Geology and Hydrogeology, vol.33, issue.384, pp.363-375, 2005.

N. Rosser, M. Lim, D. Petley, S. Dunning, and R. Allison, Patterns of precursory rockfall prior to slope failure, Journal of Geophysical Research, vol.26, issue.2, p.4014, 2007.
DOI : 10.1029/2006JF000642

-. Hanns and . Schuster, Segmentation of lidar data using the tensor voting framework, International Archives of Photogrammetry Remote Sensing and Spatial Information Sciences, pp.1073-1078, 2004.

S. Shalev-shwartz, Y. Singer, and N. Srebro, Pegasos, Proceedings of the 24th international conference on Machine learning, ICML '07, pp.807-814, 2007.
DOI : 10.1145/1273496.1273598

J. A. Peter and . Shaw, Multivariate statistics for the environmental sciences, 2003.

Y. Shiraishi and K. Fukumizu, Statistical approaches to combining binary classifiers for multi-class classification, Neurocomputing, vol.74, issue.5, pp.680-688, 2011.
DOI : 10.1016/j.neucom.2010.09.004

G. Sithole and G. Vosselman, Experimental comparison of filter algorithms for bare-Earth extraction from airborne laser scanning point clouds, ISPRS Journal of Photogrammetry and Remote Sensing, vol.59, issue.1-2, pp.85-101, 2004.
DOI : 10.1016/j.isprsjprs.2004.05.004

G. Teza, A. Pesci, R. Genevois, and A. Galgaro, Characterization of landslide ground surface kinematics from terrestrial laser scanning and strain field computation, Geomorphology, vol.97, issue.3-4, pp.3-4424, 2008.
DOI : 10.1016/j.geomorph.2007.09.003

S. Theodoridis and K. Koutroumbas, Pattern Recognition, Fourth Edition, 2008.

N. Vandapel, D. F. Huber, A. Kapuria, and M. Hebert, Natural terrain classification using 3-d ladar data, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004, pp.5117-5122, 2004.
DOI : 10.1109/ROBOT.2004.1302529

G. Vosselman, B. G. Gorte, G. Sithole, and T. Rabbani, Recognizing structure in laser scanner point clouds. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, pp.4633-4671, 2004.

H. Wendt, P. Abry, and S. Jaffard, Bootstrap for Empirical Multifractal Analysis, IEEE Signal Processing Magazine, vol.24, issue.4, pp.38-48, 2007.
DOI : 10.1109/MSP.2007.4286563

J. M. Wheaton, J. Brasington, S. E. Darby, and D. A. Sear, Accounting for uncertainty in DEMs from repeat topographic surveys: improved sediment budgets, Earth Surface Processes and Landforms, pp.136-156, 2009.
DOI : 10.1002/esp.1886