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Orthorectified Radarsat SAR Imagery. Photogrammetric Engineering & Remote Sensing
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the Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and
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for future research. International Journal of Remote Sensing 24, 2805–2815.
https://doi.org/10.1080/0143116031000066954
LeCun, Y., Bengio, Y., Hinton, G., 2015. Deep Learning. Nature 521, 436–44.
https://doi.org/10.1038/nature14539
Lecun, Y., Bottou, L., Bengio, Y., Haffner, P., 1998. Gradient-based learning applied to document
recognition. Proceedings of the IEEE 86, 2278–2324. https://doi.org/10.1109/5.726791
Li, W., Pang, J., 2020. Application Test and Analysis of 2m/8m optical satellite in coastal zone
survey. IOP Conf. Ser.: Earth Environ. Sci. 571, 012038. https://doi.org/10.1088/17551315/571/1/012038
Li, Y., Zhang, H., Xue, X., Jiang, Y., Shen, Q., 2018. Deep learning for remote sensing image
classification: A survey. Wiley Interdisciplinary Reviews: Data Mining and Knowledge
Discovery 8, e1264. https://doi.org/10.1002/widm.1264
Lillesand, T., Kiefer, R., Chipman, J., 2004. Remote sensing and image interpretation., 15th. Ed.,
John Wiley and Son, USA.704. ed.
Liu, H., Jezek, K.C., 2004. A Complete High-Resolution Coastline of Antarctica Extracted from
Orthorectified Radarsat SAR Imagery. Photogrammetric Engineering & Remote Sensing
70, 605–616. https://doi.org/10.14358/PERS.70.5.605
Liu, T., Abd-Elrahman, A., Morton, J., Wilhelm, V.L., 2018. Comparing fully convolutional
networks, random forest, support vector machine, and patch-based deep convolutional
neural networks for object-based wetland mapping using images from small unmanned
aircraft
system.
GIScience
&
Remote
Sensing
55,
243–264.
https://doi.org/10.1080/15481603.2018.1426091
Liu, X., Zhang, Z., Peterson, J., Chandra, S., 2007. The effect of LiDAR data density on DEM
accuracy, in: Oxley, L., Kulasiri, D. (Eds.), Proceedings of the International Congress on
Modelling and Simulation (MODSIM07). Presented at the MODSIM07: International
Congress on Modelling and Simulation: Land, Water and Environmental Management:
Integrated Systems for Sustainability, Modelling and Simulation Society of Australia and
New Zealand Inc., Canberra, Australia, pp. 1363–1369.
Luijendijk, A., Hagenaars, G., Ranasinghe, R., Baart, F., Donchyts, G., Aarninkhof, S., 2018. The
State of the World’s Beaches. Sci Rep 8, 6641. https://doi.org/10.1038/s41598-018-246306
Ma, J., Sun, S., 2012. Centralized Fusion Estimators for Multi-sensor Systems with Multiplicative
Noises and Missing Measurements. J. Networks. https://doi.org/10.4304/jnw.7.10.15381545
MacQueen, J., 1967. Some methods for classification and analysis of multivariate observations. in
the Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and
Probability: Weather modification. University of California Press.
Mallet, C., Michot, A., La Torre, Y., Lafon, V., Robin, M., Prevoteaux, B., 2012. Synthèse de
référence des techniques de suivi du trait de côte - Rapport (No. RP-60616-FR). BRGM.
Malthus, T.J., Mumby, P.J., 2003. Remote sensing of the coastal zone: An overview and priorities
for future research. International Journal of Remote Sensing 24, 2805–2815.
https://doi.org/10.1080/0143116031000066954