Mathematical Modelling of the Black Sea Coastline Considering its Fractal Structure and Grid Generation
https://doi.org/2587-8999-2026-10-3-31-40
Abstract
Introduction. The coastline of a reservoir is a complex natural object, which geometry has irregularity and signs of selfsimilarity, and the length depends on the scale of measurement. Despite the widespread study of its fractal properties, the transition to a digital representation of the coastline is a complex procedure and is a current topic of research. The purpose of the article is to develop a mathematical-algorithmic scheme for analyzing the coastline, including geometry validation, geodetic measurement, scale dependence analysis, fractal dimension assessment and selection of an adaptive quadrilateral grid using the example of the Black Sea. Materials and Methods. Normalization and validation procedures are applied to the coastline represented as a finite sequence of geographic points to obtain an intermediate, geometrically plausible contour. The contour length is calculated on a sphere using the haversine formula. The “box-counting” method is used to address the coastline՚s multi-scale nature and fractal characteristics. To transition from the line to a 2D representation of the water area, the Lambert azimuthal equal-area (LAEA) projection is used, followed by the construction of a grid with the required cell size. Subsequently, detailed and coarse full-quadrilateral grids are generated using the Delaunay, Frontal-Delaunay for Quads, and Packing of Parallelograms algorithms. A comparison of the grid generators is then conducted. Results. A computational experiment was conducted using Black Sea coastline data. A comparison of two sets of grids demonstrated that Delaunay is the superior generator based on the specified multi-criteria metric. The Delaunay method with a range of 125–250 m should be used to preserve significant coastal features across the entire water area. A highresolution Delaunay configuration with a range of 50–250 m should be selected when accurate reconstruction of the seabed topography is the priority. Discussion. The practical significance lies in the ability to prepare verified contours and grids for seabed topography modelling, geoinformation analysis, and subsequent hydrodynamic calculations. Conclusions. Future research prospects involve expanding the range of coastal systems analyzed, comparing various methods for estimating fractal dimension, investigating the impact of source geodata spatial resolution on the stability of calculated metrics, and adapting the approach for multi-scale monitoring of coastal dynamics.
Keywords
About the Authors
N. M. KodatskRussian Federation
Nikita M. Kodatsky, PhD student, Department of Mathematics and Informatics
1, Gagarin Sq., Rostov-on-Don, 344003
Yu. V. Belova
Russian Federation
Yulia V. Belova, Candidate of Physical and Mathematical Sciences, Associate Professor, Department of Mathematics and Informatics
1, Gagarin Sq., Rostov-on-Don, 344003
References
1. Mandelbrot B.B. The Fractal Geometry of Nature. New York: W.H. Freeman; 1982. 460 p.
2. Falconer K. Fractal Geometry: Mathematical Foundations and Applications. Chichester: John Wiley & Sons; 2003. 337 p. https://doi.org/10.1002/0470013850
3. Snyder J.P. Map Projections: A Working Manual. Washington: U.S. Geological Survey; 1987. 283 p. https://doi.org/10.3133/pp1395
4. Bomford G. Geodesy. 4th ed. Oxford: Clarendon Press; 1980. 663 p.
5. Longley P.A., Goodchild M.F., Maguire D.J., Rhind D.W. Geographical Information Systems and Science. 3rd ed. Chichester: Wiley; 2011. 612 p.
6. Marine Regions. Standardized marine georeferenced database. URL: https://marineregions.org/ (accessed: 09.04.2026).
7. De Berg M., Cheong O., van Kreveld M., Overmars M. Computational Geometry: Algorithms and Applications. 3rd ed. Berlin: Springer; 2008. 386 p. https://doi.org/10.1007/978-3-540-77974-2
8. O’Rourke J. Computational Geometry in C. 2nd ed. Cambridge: Cambridge University Press; 1998. 362 p. https://doi.org/10.1017/CBO9780511804120
9. Preparata F.P., Shamos M.I. Computational Geometry: An Introduction. New York: Springer; 1985. 400 p. https://doi.org/10.1007/978-1-4612-1098-6
10. Richardson L.F. The problem of contiguity: an appendix to statistics of deadly quarrels. General Systems Yearbook. 1961;6:139–187.
11. Geuzaine C., Remacle J.-F. Gmsh: a three-dimensional finite element mesh generator with built-in pre- and post-processing facilities. International Journal for Numerical Methods in Engineering. 2009;79(11):1309–1331. https://doi.org/10.1002/nme.2579
12. GEBCO Compilation Group. GEBCO 2024 Grid. 2024. https://doi.org/10.5285/1c44ce99-0a0d-5f4f-e063-7086abc0ea0f
13. Knupp P.M. Algebraic mesh quality metrics for unstructured initial meshes. Finite Elements in Analysis and Design. 2003;39(3):217–241. https://doi.org/10.1016/S0168-874X(02)00070-7
14. Karperien A., Jelinek H. F. Box-Counting Fractal Analysis: A Primer for the Clinician. In: The Fractal Geometry of the Brain. New York: Springer, 2024. https://doi.org/10.1007/978-3-031-47606-8_2
15. Jiang B., Brandt S.A. A fractal perspective on scale in geography. International Journal of Geographical Information Science. 2016;30(1): 17–30. https://doi.org/10.1080/13658816.2015.1082532
16. Press W.H., Teukolsky S.A., Vetterling W.T., Flannery B.P. Numerical Recipes: The Art of Scientific Computing. 3rd ed. Cambridge: Cambridge University Press; 2007. 994 с.
17. Samarskii A.A. Theory of Difference Schemes. Moscow: Nauka; 1989. 616 p.
18. Kalitkin N.N. Numerical Methods. 2nd ed., revised. St. Petersburg: BHV-Peterburg; 2011. 586 p.
19. Samarskii A.A., Gulin A.V. Numerical Methods. Moscow: Nauka; 1989. 432 p.
20. Quarteroni A., Sacco R., Saleri F. Numerical Mathematics. 2nd ed. New York: Springer; 2007. 654 p. https://doi.org/10.1007/b98885
21. Burden R.L., Faires J.D. Numerical Analysis. 9th ed. Boston: Brooks/Cole; 2011. 872 p.
22. Atkinson K.E. An Introduction to Numerical Analysis. New York: John Wiley & Sons; 1989. 23. Hofmann-Wellenhof B., Moritz H.Physical Geodesy.Wien; New York: Springer; 2005. 403 p.https://doi.org/10.1007/b139113
23. Li Z., Zhu Q., Gold C. Digital Terrain Modeling: Principles and Methodology. Boca Raton: CRC Press; 2005. 448 p. https://doi.org/10.1201/9780203357132
Review
For citations:
Kodatsk N.M., Belova Yu.V. Mathematical Modelling of the Black Sea Coastline Considering its Fractal Structure and Grid Generation. Computational Mathematics and Information Technologies. 2026;10(3):31-40. https://doi.org/2587-8999-2026-10-3-31-40
JATS XML









