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Semi-automatic segmentation of NATURA 2000 habitats in Sentinel-2 satellite images by evolving open curves
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An automated segmentation of NATURA 2000 habitats from Sentinel-2 optical data
1. | Department of Mathematics, Slovak University of Technology, Radlinského 11,810 05 Bratislava, Slovakia, Algoritmy:SK, s.r.o., Šulekova 6,811 06 Bratislava, Slovakia |
2. | Institute of Botany, Slovak Academy of Sciences, Dúbravská cesta 9,845 23 Bratislava, Slovakia |
In this paper, we present a mathematical model and numerical method designed for the segmentation of satellite images, namely to obtain in an automated way borders of Natura 2000 habitats from Sentinel-2 optical data. The segmentation model is based on the evolving closed plane curve approach in the Lagrangian formulation including the efficient treatment of topological changes. The model contains the term expanding the curve in its outer normal direction up to the region of habitat boundary edges, the term attracting the curve accurately to the edges and the smoothing term given by the influence of local curvature. For the numerical solution, we use the flowing finite volume method discretizing the arising advection-diffusion intrinsic partial differential equation including the asymptotically uniform tangential redistribution of curve grid points. We present segmentation results for satellite data from a selected area of Western Slovakia (Záhorie) where the so-called riparian forests represent the important European Natura 2000 habitat. The automatic segmentation results are compared with the semi-automatic segmentation performed by the botany expert and with the GPS tracks obtained in the field. The comparisons show the ability of our numerical model to segment the habitat areas with the accuracy comparable to the pixel resolution of the Sentinel-2 optical data.
References:
[1] |
M. Ambroz, M. Balažovjech, M. Medla and K. Mikula,
Numerical modeling of wildland surface fire propagation by evolving surface curves, Adv. Comput. Math., 45 (2019), 1067-1103.
doi: 10.1007/s10444-018-9650-4. |
[2] |
M. Balažovjech, K. Mikula, M. Petrášová and J. Urbán, Lagrangean method with topological changes for numerical modelling of forest fire propagation, 19th Conference on Scientific Computing, Slovakia, 2012. Google Scholar |
[3] |
V. Caselles, R. Kimmel and G. Sapiro,
Geodesic active contours, Internat. J. Comput. Vision, 22 (1997), 61-79.
doi: 10.1109/ICCV.1995.466871. |
[4] |
E. Faure et al., A workflow to process 3D+time microscopy images of developing organisms and reconstruct their cell lineage, Nat. Commun., 7 (2016).
doi: 10.1038/ncomms9674. |
[5] |
M.A. Finney, et al., FARSITE: Fire Area Simulator–model development and evaluation, U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Ogden, UT, 1998.
doi: 10.2737/RMRS-RP-4. |
[6] |
T.Y. Hou, J. Lowengrub and M. Shelley,
Removing the stiffness from interfacial flows with surface tension, J. Comput. Phys., 114 (1994), 312-338.
doi: 10.1006/jcph.1994.1170. |
[7] |
S. Kichenassamy, A. Kumar, P. Olver, A. Tannenbaum and A. Yezzi,
Conformal curvature flows: From phase transitions to active vision, Arch. Rational Mech. Anal., 134 (1996), 275-301.
doi: 10.1007/BF00379537. |
[8] |
M. Kimura,
Numerical analysis for moving boundary problems using the boundary tracking method, Japan J. Indust. Appl. Math., 14 (1997), 373-398.
doi: 10.1007/BF03167390. |
[9] |
K. Mikula and M. Ohlberger, Inflow-implicit/outflow-explicit scheme for solving advection equations, in Finite Volumes for Complex Applications VI. Problems & Perspectives. Volume 1, 2, Springer Proc. Math., 4, Springer, Heidelberg, 2011,683–691.
doi: 10.1007/978-3-642-20671-9_72. |
[10] |
K. Mikula, M. Ohlberger and J. Urbán,
Inflow-implicit/outflow-explicit finite volume methods for solving advection equations, Appl. Numer. Math., 85 (2014), 16-37.
doi: 10.1016/j.apnum.2014.06.002. |
[11] |
K. Mikula and D. Ševčovič,
Evolution of plane curves driven by a nonlinear function of curvature and anisotropy, SIAM J. Appl. Math., 61 (2001), 1473-1501.
doi: 10.1137/S0036139999359288. |
[12] |
K. Mikula and D. Ševčovič,
A direct method for solving an anisotropic mean curvature flow of plane curves with an external force, Math. Methods Appl. Sci., 27 (2004), 1545-1565.
doi: 10.1002/mma.514. |
[13] |
K. Mikula, D. Ševčovič and M. Balažovjech,
A simple, fast and stabilized flowing finite volume method for solving general curve evolution equations, Commun. Comput. Phys., 7 (2010), 195-211.
doi: 10.4208/cicp.2009.08.169. |
[14] |
K. Mikula and J. Urbán, New fast and stable Lagrangean method for image segmentation, 5th International Congress on Image and Signal Processing, Chongqing, China, 2012.
doi: 10.1109/CISP.2012.6469852. |
[15] |
K. Mikula, et al., Report on semi-automatic segmentation methods and software tool for static data, ESA PECS project NaturaSat Deliverable 2.1, 2018. Google Scholar |
[16] |
G. Nakamura and R. Potthast, Inverse Modeling, IOP Expanding Physics, IOP Publishing, Bristol, 2015, 2053–2563.
doi: 10.1088/978-0-7503-1218-9. |
[17] |
P. Pauš, M. Beneš, Algorithm for topological changes of parametrically described curves, Proceedings of ALGORITMY, 2009,176–184. Google Scholar |
[18] |
A. Sarti, R. Malladi and J. A. Sethian:,
Subjective surfaces: A method for completing missing boundaries, Proc. Natl. Acad. Sci. USA, 97 (2000), 6258-6263.
doi: 10.1073/pnas.110135797. |
show all references
References:
[1] |
M. Ambroz, M. Balažovjech, M. Medla and K. Mikula,
Numerical modeling of wildland surface fire propagation by evolving surface curves, Adv. Comput. Math., 45 (2019), 1067-1103.
doi: 10.1007/s10444-018-9650-4. |
[2] |
M. Balažovjech, K. Mikula, M. Petrášová and J. Urbán, Lagrangean method with topological changes for numerical modelling of forest fire propagation, 19th Conference on Scientific Computing, Slovakia, 2012. Google Scholar |
[3] |
V. Caselles, R. Kimmel and G. Sapiro,
Geodesic active contours, Internat. J. Comput. Vision, 22 (1997), 61-79.
doi: 10.1109/ICCV.1995.466871. |
[4] |
E. Faure et al., A workflow to process 3D+time microscopy images of developing organisms and reconstruct their cell lineage, Nat. Commun., 7 (2016).
doi: 10.1038/ncomms9674. |
[5] |
M.A. Finney, et al., FARSITE: Fire Area Simulator–model development and evaluation, U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Ogden, UT, 1998.
doi: 10.2737/RMRS-RP-4. |
[6] |
T.Y. Hou, J. Lowengrub and M. Shelley,
Removing the stiffness from interfacial flows with surface tension, J. Comput. Phys., 114 (1994), 312-338.
doi: 10.1006/jcph.1994.1170. |
[7] |
S. Kichenassamy, A. Kumar, P. Olver, A. Tannenbaum and A. Yezzi,
Conformal curvature flows: From phase transitions to active vision, Arch. Rational Mech. Anal., 134 (1996), 275-301.
doi: 10.1007/BF00379537. |
[8] |
M. Kimura,
Numerical analysis for moving boundary problems using the boundary tracking method, Japan J. Indust. Appl. Math., 14 (1997), 373-398.
doi: 10.1007/BF03167390. |
[9] |
K. Mikula and M. Ohlberger, Inflow-implicit/outflow-explicit scheme for solving advection equations, in Finite Volumes for Complex Applications VI. Problems & Perspectives. Volume 1, 2, Springer Proc. Math., 4, Springer, Heidelberg, 2011,683–691.
doi: 10.1007/978-3-642-20671-9_72. |
[10] |
K. Mikula, M. Ohlberger and J. Urbán,
Inflow-implicit/outflow-explicit finite volume methods for solving advection equations, Appl. Numer. Math., 85 (2014), 16-37.
doi: 10.1016/j.apnum.2014.06.002. |
[11] |
K. Mikula and D. Ševčovič,
Evolution of plane curves driven by a nonlinear function of curvature and anisotropy, SIAM J. Appl. Math., 61 (2001), 1473-1501.
doi: 10.1137/S0036139999359288. |
[12] |
K. Mikula and D. Ševčovič,
A direct method for solving an anisotropic mean curvature flow of plane curves with an external force, Math. Methods Appl. Sci., 27 (2004), 1545-1565.
doi: 10.1002/mma.514. |
[13] |
K. Mikula, D. Ševčovič and M. Balažovjech,
A simple, fast and stabilized flowing finite volume method for solving general curve evolution equations, Commun. Comput. Phys., 7 (2010), 195-211.
doi: 10.4208/cicp.2009.08.169. |
[14] |
K. Mikula and J. Urbán, New fast and stable Lagrangean method for image segmentation, 5th International Congress on Image and Signal Processing, Chongqing, China, 2012.
doi: 10.1109/CISP.2012.6469852. |
[15] |
K. Mikula, et al., Report on semi-automatic segmentation methods and software tool for static data, ESA PECS project NaturaSat Deliverable 2.1, 2018. Google Scholar |
[16] |
G. Nakamura and R. Potthast, Inverse Modeling, IOP Expanding Physics, IOP Publishing, Bristol, 2015, 2053–2563.
doi: 10.1088/978-0-7503-1218-9. |
[17] |
P. Pauš, M. Beneš, Algorithm for topological changes of parametrically described curves, Proceedings of ALGORITMY, 2009,176–184. Google Scholar |
[18] |
A. Sarti, R. Malladi and J. A. Sethian:,
Subjective surfaces: A method for completing missing boundaries, Proc. Natl. Acad. Sci. USA, 97 (2000), 6258-6263.
doi: 10.1073/pnas.110135797. |








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