Abstract
Most current multibeam echo soundings (MBES) generalization algorithms focus on decreasing the data density and navigational purposes. However, their computational efficiency is not satisfactory for massive amounts of data. Additionally, these methods fail to consider how to harmonize soundings generalized from MBES and existing chart soundings. This paper presents an MBES generalization algorithm with chart soundings as a guiding subset that uses MBES datasets as source data and existing nautical chart soundings as control guidance to generalize soundings. After preliminarily selecting shallow soundings, deep soundings, and background soundings from MBES data, the soundings are then generalized with the constraint of chart soundings. Experiments are implemented with a real dataset and the results are compared with those of soundings generalization algorithms without the guidance of chart soundings. The results show that the proposed algorithm has higher computational efficiency and respectable soundings selection constraints; moreover, the seafloor terrain characteristics are accurately reflected, especially for regions that lack structural changes in topography.
This is a preview of subscription content, log in via an institution to check access.
source data and algorithm results
Similar content being viewed by others
Data availability
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
Code availability
Not applicable.
References
Bannari A, Kadhem G (2017) MBES-CARIS data validation for bathymetric mapping of shallow water in the Kingdom of Bahrain on the Arabian Gulf. Remote Sens. 9(4):385. https://doi.org/10.3390/rs9040385
Calder BR, Mayer LA (2003) Automatic processing of high-rate, high-density multibeam echosounder data. Geochem. Geophys. Geosyst. 4:1048. https://doi.org/10.1029/2002GC000486
Caris S-57 Composer (2019) . http://www.teledynecaris.com/en/products/s-57-composer Accessed 4 March 2019
Douglas DH, Peucker TK (1973) Algorithms for the reduction of the number of points required to represent a digitized line or its caricature. Cartographica: The International Journal for Geographic Information and Geovisualization 10(2):112–122. https://doi.org/10.3138/FM57-6770-U75U-7727
IHO (2014) Special Regulations for electronic navigational chart product specifications of the IHO. In: International Hydrographic Bureau, Monaco
Jia SD, Zhang LH, Dong J, et al (2019). A method for constructing DDM serving for navigation using pre-constructed model surface to control and adjust the selection of DDM nodes. Geomatics and Information Science of Wuhan University 44(11):1715-1722. https://doi.org/10.13203/j.whugis20180087
Li JH (2018) Research on automated cartographic generalization of submarine relief. Dissertation, PLA Strategic Support Force Information Engineering University
Lovrinčević D (2016) Quality assessment of an automatic sounding selection process for navigational charts. The Cartographic Journal Online. https://doi.org/10.1080/00087041.2016.1195031
Lovrinčević D (2018) The development of a new methodology for automated sounding selection on nautical charts. NAŠE MORE 66 (2):70-77. https://doi.org/10.17818/NM/2019/2.4
Liu Y, Zhai JS, Lu Y et al (2005) Automatic generalization of sounding in digital chart. Acta Geodaetica et Cartographica Sinica 34(02):179–184. https://doi.org/10.3321/j.issn:1001-1595.2005.02.016
Lu Y, Zhai JS, Du JH (2000) Sounding selection based on recognition of submarine topography features. Journal of Institute of Surveying and Mapping 17(04):296–300. https://doi.org/10.3969/j.issn.1673-6338.2000.04.017
Naval Press (1998) Specifications for Chinese nautical charts: GB12320-1998. Beijing, pp 156-181
Oraas SR (1975) Automated sounding selection. The International Hydrographic Review 52(2):109–119
Peters R, Ledoux H, Meijers M (2014) A Voronoi-based approach to generating depth-contours for hydrographic charts. Marine Geodesy 37(2):145–166. https://doi.org/10.1080/01490419.2014.902882
Schimel ACG, Healy TR, Johnson D, Immenga D (2010) Quantitative experimental comparison of single-beam, sidescan and multibeam benthic habitat maps. ICES Journal of Marine Science 67:1766–1779. https://doi.org/10.1093/icesjms/fsq102
Sui HG, Zhu XY, Zhang AM (2005a) A system for fast cartographic sounding selection. Marine Geodesy 28(2):159–165. https://doi.org/10.1080/01490410590953695
Sui HG, Hua L, Zhao HT, Zhang YL (2005b) A fast algorithm of cartographic sounding selection. Geo-spatial Information Science 8(4):262–268
Tang GA, Li FY, Liu XJ (2016) Digital elevation model tutorial. China Sciences Press, Beijing
Tang Q (1987) A study on automated generalization of submarine relief. Acta Geodaetica et Cartographica Sinica 16(4):314–320
Tsoulos L, Stefanakis K (1997) Sounding selection for nautical charts: an expert system approach. In: Proceedings of 18th International Cartographic Conference, Stockholm, pp 2021-2028
Wang JY, Tian Z (1999) The cartographic generalization of soundings on chart by artificial neural network techniques. Acta Geodaetica et Cartographica Sinica 28(04):335–339. https://doi.org/10.3321/j.issn:1001-1595.1999.04.011
Wang M, Li SJ, Chen HR, et al. (2016) Irregular sounding network construction method based on the constraint conditions. Geospatial Information 14(05):92-95,8. https://doi.org/10.3969/j.issn.1672-4623.2016.05.029
Wu ZY, Shang JH, Li SJ, et al. (2015) Multi-beam bathymetric chart construction method based on submarine digital depth model feature extraction. Free Patent Online. https://www.freepatentsonline.com/y2015/0039229.html Accessed 5 February 2015
Yan JY, Guilbert E, Saux E (2015) An ontology of the submarine relief for analysis and representation on nautical charts. The Cartographic Journal 52(1):58–66
Yu WH (2017) Automatic sounding generalization in nautical chart considering bathymetry complexity variations. Marine Geodesy. https://doi.org/10.1080/01490419.2017.1393476
Zhang AM (2013) Research on some key techniques of dynamic information services in e-Navigation. Dissertation, Wuhan University
Zoraster S (1990) The automatic selection of prime soundings for nautical chart compilation. Lighthouse 41(1):9–14
Zoraster S, Bayer S (1993) Automated cartographic sounding selection. International Hydrographic Review 69:57–61
Zhai JS, Lu Y (2005) Recognition and measurement of marine topography for sounding generalization in digital nautical chart. Marine Geodesy 28(2):167–174. https://doi.org/10.1080/01490410590953712
Funding
This work was supported by the Basic Research Program of China under Grant [number 613317].
Author information
Authors and Affiliations
Contributions
Yu (first author) and Qian (corresponding author) conceived of the proposed method and wrote this manuscript. Concrete algorithms were designed and implemented by Yu and Du. Zhai and Wu helped Yu estimate the proposed approach and test the applicability of this approach.
Corresponding author
Ethics declarations
Ethics approval
Not applicable
Consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Additional information
Publisher's note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
This article is part of the Topical Collection on Automated map generalization: emerging techniques and new trends
Rights and permissions
About this article
Cite this article
Yu, L., Du, J., Zhai, R. et al. A fast generalization method of multibeam echo soundings for nautical charting. J geovis spat anal 6, 2 (2022). https://doi.org/10.1007/s41651-021-00096-5
Accepted:
Published:
DOI: https://doi.org/10.1007/s41651-021-00096-5