References

• Blue Marble Geographics. 2022. “Global mapper user guide.” Available from https://www.bluemarblegeo.com/knowledgebase/global-mapper-24/GlobalMapper.htm. (accessed October 15, 2022).
   Google Scholar
• Brock, J.C., and Purkis, S.J. 2009. “The emerging role of Lidar remote sensing in coastal research and resource management.” Journal of Coastal Research, Vol. 10053 (No. SI): pp. 1–5. doi:10.2112/SI53-001.1.
   Google Scholar
• Chust, G., Grande, M., Galparsoro, I., Uriarte, A., and Borja, Á. 2010. “Capabilities of the bathymetric Hawk Eye LiDAR for coastal habitat mapping: A case study within a Basque estuary.” Estuarine, Coastal and Shelf Science, Vol. 89(No. 3): pp. 200–213. doi:10.1016/j.ecss.2010.07.002.
   Web of Science ®Google Scholar
• CloudCompare. 2015. “CloudCompare user documentation: SOR filter.” Available from https://www.cloudcompare.org/doc/wiki/index.php/SOR_filter (accessed August 1, 2022).
   Google Scholar
• Daniele, T., Mckean, J.A., Benjankar, R.M., Wright, C.W., Goode, J.R., Chen, Q.W., Reeder, W.J., Carmichael, R.A., and Edmondson, M.R. 2019. “Mapping river bathymetries: Evaluating topobathymetric LiDAR survey.” Earth Surface Processes and Landforms, Vol. 44(No. 2): pp. 507–520. doi:10.1002/esp.4513.
   Web of Science ®Google Scholar
• Guenther, G. C. 1985. Airborne Laser Hydrography: System Design and Performance Factors. Rockville, MD: NOAA Professional Paper Series, National Ocean Service 1, National Oceanic and Atmospheric Administration.
   Google Scholar
• Guo, K., Xu, W., Liu, Y., He, X., and Tian, Z. 2017. “Gaussian half-wavelength progressive decomposition method for waveform processing of airborne laser bathymetry.” Remote Sensing, Vol. 10(No. 2): pp. 35. doi:10.3390/rs10010035.
   Google Scholar
• Jung, J., Lee, J., and Parrish, C.E. 2021. “Inverse histogram-based clustering approach to seafloor segmentation from bathymetric LiDAR data.” Remote Sensing, Vol. 13(No. 18): pp. 3665. doi:10.3390/rs13183665.
   Web of Science ®Google Scholar
• Kim, H., Lee, J., Kim, Y., and Wie, G. 2021. “Waveform decomposition of airborne bathymetric LiDAR by estimating potential peaks.” Korean Journal of Remote Sensing, Vol. 37(No. 6–1): pp. 1709–1718. doi:10.7780/kjrs.2021.37.6.1.18.
   Web of Science ®Google Scholar
• Kim, H., Tuell, G.H., Park, J.Y., Brown, E., and We, G. 2019. “Overview of SEAHAWK: A bathymetric LiDAR airborne mapping system for localization in Korea.” Journal of Coastal Research, Vol. 91(No. sp1): pp. 376–380. doi:10.2112/SI91-076.1.
   Google Scholar
• Kogut, T., and Weistock, M. 2019. “Classifying airborne bathymetry data using the Random Forest algorithm.” Remote Sensing Letters, Vol. 10(No. 9): pp. 874–882. doi:10.1080/2150704X.2019.1629710.
   Web of Science ®Google Scholar
• Kogut, T., Tomczak, A., Słowik, A., and Oberski, T. 2022. “Seabed Modelling by Means of Airborne Laser Bathymetry Data and Imbalanced Learning for Offshore Mapping.” Sensors, Vol. 22(No. 9): pp. 3121. doi:10.3390/s22093121.
   PubMed Web of Science ®Google Scholar
• Kumpumäki, T., Ruusuvuori, P., Kangasniemi, V., and Lipping, T. 2015. “Data-driven approach to benthic cover type classification using bathymetric LiDAR waveform analysis.” Remote Sensing, Vol. 7(No. 10): pp. 13390–13409. doi:10.3390/rs71013390.
   Web of Science ®Google Scholar
• Li, X., Liu, C., Wang, Z., Xie, X., Li, D., and Xu, L. 2021. “Airborne LiDAR: State-of-the-art of system design, technology and application.” Measurement Science and Technology, Vol. 32(No. 3): pp. 032002. doi:10.1088/1361-6501/abc867.
   Web of Science ®Google Scholar
• Lloyd, S. 1982. “Least squares quantization in PCM.” IEEE Transactions on Information Theory, Vol. 28(No. 2): pp. 129–137. doi:10.1109/TIT.1982.1056489.
   Web of Science ®Google Scholar
• Lowell, K., and Calder, B. 2021a. “Assessing marginal shallow-water bathymetric information content of lidar sounding attribute data and derived seafloor geomorphometry.” Remote Sensing, Vol. 13(No. 9): pp. 1604. doi:10.3390/rs13091604.
   Web of Science ®Google Scholar
• Lowell, K., and Calder, B. 2021b. “Extracting shallow-water bathymetry from lidar point clouds using pulse attribute data: merging density-based and machine learning approaches.” Marine Geodesy, Vol. 44(No. 4): pp. 259–286. doi:10.1080/01490419.2021.1925790.
   Web of Science ®Google Scholar
• Ma, Y., Zhang, J., Zhang, Z., and Zhang, J.Y. 2019. “Bathymetry retrieval method of LiDAR waveform based on multi-Gaussian functions.” Journal of Coastal Research, Vol. 90(No. sp1): pp. 324–331. doi:10.2112/SI90-041.1.
   Google Scholar
• Mader, D., Richter, K., Westfeld, P., Weiß, R., and Maas, H.G. 2019. “Detection and extraction of water bottom topography from laser bathymetry data by using full-waveform-stacking techniques.” The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XLII-2/W13: pp. 1053–1059. doi:10.5194/isprs-archives-XLII-2-W13-1053-2019.
   Google Scholar
• Mallet, C., and Bretar, F. 2009. “Full-waveform topographic lidar: State-of-the-art.” ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 64(No. 1): pp. 1–16. doi:10.1016/j.isprsjprs.2008.09.007.
   Web of Science ®Google Scholar
• Mandlburger, G., Hauer, C., Wieser, M., and Pfeifer, N. 2015. “Topo-bathymetric LiDAR for monitoring river morphodynamics and instream habitats—A case study at the Pielach River.” Remote Sensing, Vol. 7(No. 5): pp. 6160–6195. doi:10.3390/rs70506160.
   Web of Science ®Google Scholar
• Mandlburger, G. 2020. “A review of airborne laser bathymetry for mapping of inland and coastal waters.” Hydrographische Nachrichten, Vol. 116: pp. 6–15. doi:10.23784/HN116-01.
   Google Scholar
• MathWorks. 2007. “MATLAB documentation: Findpeaks.” Available from https://mathworks.com/help/signal/ref/findpeaks.html (accessed October 1, 2022).
   Google Scholar
• Muss, J.D., Mladenoff, D.J., and Townsend, P.A. 2011. “A pseudo-waveform technique to assess forest structure using discrete lidar data.” Remote Sensing of Environment, Vol. 115(No. 3): pp. 824–835. doi:10.1016/j.rse.2010.11.008.
   Web of Science ®Google Scholar
• NOAA National Geodetic Survey (NGS). 2022. “2016 NOAA NGS topobathy lidar: Marco Island (FL).” Available from https://www.fisheries.noaa.gov/inport/item/48178 (accessed August 3, 2022).
   Google Scholar
• Pe’eri, S., and Philpot, W. 2007. “Increasing the existence of very shallow-water LIDAR measurements using the red-channel waveforms.” IEEE Transactions on Geoscience and Remote Sensing, Vol. 45(No. 5): pp. 1217–1223. doi:10.1109/TGRS.2007.894584.
   Web of Science ®Google Scholar
• Schwarz, R., Mandlburger, G., Pfennigbauer, M., and Pfeifer, N. 2019. “Design and evaluation of a full-wave surface and bottom-detection algorithm for LiDAR bathymetry of very shallow waters.” ISPRS journal of Photogrammetry and Remote Sensing, Vol. 150: pp. 1–10. doi:10.1016/j.isprsjprs.2019.02.002.
   Web of Science ®Google Scholar
• Tan, S.H., and Tan, S.B. 2010. “The correct interpretation of confidence intervals.” Proceedings of Singapore Healthcare, Vol. 19(No. 3): pp. 276–278. doi:10.1177/201010581001900316.
   Google Scholar
• Terrasolid. 2022. “TerraScan user guide.” Available from https://terrasolid.com/guides/tscan.pdf (accessed October 15, 2022).
   Google Scholar
• Wang, C., Li, Q., Liu, Y., Wu, G., Liu, P., and Ding, X. 2015. “A comparison of waveform processing algorithms for single-wavelength LiDAR bathymetry.” ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 101: pp. 22–35. doi:10.1016/j.isprsjprs.2014.11.005.
   Web of Science ®Google Scholar
• Wedding, L.M., Friedlander, A.M., McGranaghan, M., Yost, R.S., and Monaco, M.E. 2008. “Using bathymetric lidar to define nearshore benthic habitat complexity: Implications for management of reef fish assemblages in Hawaii.” Remote Sensing of Environment, Vol. 112(No. 11): pp. 4159–4165. doi:10.1016/j.rse.2008.01.025.
   Web of Science ®Google Scholar
• Weinstein, M.P., and Heck, K.L. 1979. “Ichthyofauna of seagrass meadows along the Caribbean coast of Panama and in the Gulf of Mexico: Composition, structure and community ecology.” Marine Biology, Vol. 50(No. 2): pp. 97–107. doi:10.1007/BF00397814.
   Web of Science ®Google Scholar
• Xing, S., Wang, D., Xu, Q., Lin, Y., Li, P., Jiao, L., Zhang, X., and Liu, C. 2019. “A depth-adaptive waveform decomposition method for airborne LiDAR bathymetry.” Sensors, Vol. 19(No. 23): pp. 5065. doi:10.3390/s19235065.
   PubMed Web of Science ®Google Scholar
• Yang, A., Wu, Z., Yang, F., Su, D., Ma, Y., Zhao, D., and Qi, C. 2020. “Filtering of airborne LiDAR bathymetry based on bidirectional cloth simulation.” ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 163: pp. 49–61. doi:10.1016/j.isprsjprs.2020.03.004.
   Web of Science ®Google Scholar
• Yang, F., Qi, C., Su, D., Ding, S., He, Y., and Ma, Y. 2022. “An airborne LiDAR bathymetric waveform decomposition method in very shallow water: A case study around Yuanzhi Island in the South China Sea.” International Journal of Applied Earth Observation and Geoinformation, Vol. 109: pp. 102788. doi:10.1016/j.jag.2022.102788.
   Web of Science ®Google Scholar
• Zhou, T., and Popescu, S.C. 2017. “Bayesian decomposition of full waveform LiDAR data with uncertainty analysis.” Remote Sensing of Environment, Vol. 200: pp. 43–62. doi:10.1016/j.rse.2017.08.012.
   Web of Science ®Google Scholar