AN AUTOMATED SEGMENTATION OF NATURA 2000 HABITATS FROM SENTINEL-2 OPTICAL DATA

被引:8
作者
Mikula, Karol [1 ,2 ]
Urban, Jozef [1 ,2 ]
Kollar, Michal [1 ,2 ]
Ambroz, Martin [1 ,2 ]
Jarolimek, Ivan [3 ]
Sibik, Jozef [3 ]
Sibikova, Maria [3 ]
机构
[1] Slovak Univ Technol Bratislava, Dept Math, Radlinskeho 11, Bratislava 81005, Slovakia
[2] Algoritmy SK Sro, Sulekova 6, Bratislava 81106, Slovakia
[3] Slovak Acad Sci, Inst Bot, Dubravska Cesta 9, Bratislava 84523, Slovakia
来源
DISCRETE AND CONTINUOUS DYNAMICAL SYSTEMS-SERIES S | 2021年 / 14卷 / 03期
关键词
Image segmentation; curve evolution; numerical method; Natura; 2000; satellite images; Sentinel-2; FLOW;
D O I
10.3934/dcdss.2020348
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
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 (Zahorie) 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.
引用
收藏
页码:1017 / 1032
页数:16
相关论文
共 50 条
  • [21] LEAF CHLOROPHYLL CONTENT ESTIMATION FROM SENTINEL-2 MSI DATA
    Ma, Qingmiao
    Chen, Jing M.
    Li, Yingjie
    Croft, Holly
    Luo, Xiangzhong
    Zheng, Ting
    Zamaria, Sophia
    2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2017, : 2915 - 2918
  • [22] GLCM FEATURES FOR LEARNING FLOODED VEGETATION FROM SENTINEL-1 AND SENTINEL-2 DATA
    Tavus, Beste
    Kocaman, Sultan
    39TH INTERNATIONAL SYMPOSIUM ON REMOTE SENSING OF ENVIRONMENT ISRSE-39 FROM HUMAN NEEDS TO SDGS, VOL. 48-M-1, 2023, : 601 - 607
  • [23] Estimation of the Water Level in the Ili River from Sentinel-2 Optical Data Using Ensemble Machine Learning
    Mukhamediev, Ravil I.
    Terekhov, Alexey
    Sagatdinova, Gulshat
    Amirgaliyev, Yedilkhan
    Gopejenko, Viktors
    Abayev, Nurlan
    Kuchin, Yan
    Popova, Yelena
    Symagulov, Adilkhan
    REMOTE SENSING, 2023, 15 (23)
  • [24] S1S2-Water: A Global Dataset for Semantic Segmentation of Water Bodies From Sentinel-1 and Sentinel-2 Satellite Images
    Wieland, Marc
    Fichtner, Florian
    Martinis, Sandro
    Groth, Sandro
    Krullikowski, Christian
    Plank, Simon
    Motagh, Mahdi
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2024, 17 : 1084 - 1099
  • [25] NATURA 2000 HABITATS FROM OLTENIA AFFECTED BY INVASIVE AND POTENTIALLY INVASIVE SPECIES (I)
    Radutoiu, Daniel
    Baloniu, Laurentiu
    Stan, Ion
    SCIENTIFIC PAPERS-SERIES B-HORTICULTURE, 2023, 67 (01): : 827 - 832
  • [26] NATURA 2000 HABITATS FROM OLTENIA AFFECTED BY INVASIVE AND POTENTIALLY INVASIVE SPECIES (II)
    Radutoiu, Daniel
    Baloniu, Laurentiu
    SCIENTIFIC PAPERS-SERIES B-HORTICULTURE, 2024, 68 (01): : 871 - 877
  • [27] Comparison of an Optimised Multiresolution Segmentation Approach with Deep Neural Networks for Delineating Agricultural Fields from Sentinel-2 Images
    Tetteh, Gideon Okpoti
    Schwieder, Marcel
    Erasmi, Stefan
    Conrad, Christopher
    Gocht, Alexander
    PFG-JOURNAL OF PHOTOGRAMMETRY REMOTE SENSING AND GEOINFORMATION SCIENCE, 2023, 91 (04): : 295 - 312
  • [28] Benchmark for Building Segmentation on Up-Scaled Sentinel-2 Imagery
    Illarionova, Svetlana
    Shadrin, Dmitrii
    Shukhratov, Islomjon
    Evteeva, Ksenia
    Popandopulo, Georgii
    Sotiriadi, Nazar
    Oseledets, Ivan
    Burnaev, Evgeny
    REMOTE SENSING, 2023, 15 (09)
  • [29] SEASONAL FOREST DISTURBANCE DETECTION USING SENTINEL-1 SAR & SENTINEL-2 OPTICAL TIMESERIES DATA AND TRANSFORMERS
    Mullissa, Adugna
    Reiche, Johannes
    Saatchi, Sassan
    IGARSS 2023 - 2023 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2023, : 3122 - 3124
  • [30] PHENOLOGICAL METRICS DERIVED FROM SENTINEL-2 DATA FOR SOLIDAGO GIGANTEA MAPPING
    Chadoulis, Rizos-Theodoros
    Rucinski, Marek
    Katsikis, Eleftherios
    Archicinski, Piotr
    Sala, Szymon
    Gromny, Ewa
    Wozniak, Edyta
    Manakos, Ioannis
    Affek, Andrzej
    Foks-Ryznar, Anna
    IGARSS 2023 - 2023 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2023, : 445 - 447