A Hybrid Bio-Optical Transformation for Satellite Bathymetry Modeling Using Sentinel-2 Imagery

被引:15
|
作者
Mavraeidopoulos, Athanasios K. [1 ]
Oikonomou, Emmanouil [2 ]
Palikaris, Athanasios [3 ]
Poulos, Serafeim [4 ]
机构
[1] Natl & Kapodistrian Univ Athens, Remote Sensing Lab, Athens 15784, Greece
[2] Univ West Attica, Dept Surveying & Geoinformat Engn, Athens 12243, Greece
[3] Hellen Naval Acad, Nav & Sea Sci Lab, Piraeus 18539, Greece
[4] Natl & Kapodistrian Univ Athens, Lab Phys Geog, Sect Geog & Climatol, Dept Geol & Geoenvironm, Athens, Greece
关键词
satellite derived bathymetry (SDB); nautical charts; IOPs; AOPs; unsupervised classification; INHERENT OPTICAL-PROPERTIES; WATER DEPTH; REFLECTANCE; COLOR;
D O I
10.3390/rs11232746
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The article presents a new hybrid bio-optical transformation (HBT) method for the rapid modelling of bathymetry in coastal areas. The proposed approach exploits free-of-charge multispectral images and their processing by applying limited manpower and resources. The testbed area is a strait between two Greek Islands in the Aegean Sea with many small islets and complex seabed relief. The HBT methodology implements semi-analytical and empirical steps to model sea-water inherent optical properties (IOPs) and apparent optical properties (AOPs) observed by the Sentinel-2A multispectral satellite. The relationships of the calculated IOPs and AOPs are investigated and utilized to classify the study area into sub-regions with similar water optical characteristics, where no environmental observations have previously been collected. The bathymetry model is configured using very few field data (training depths) chosen from existing official nautical charts. The assessment of the HBT indicates the potential for obtaining satellite derived bathymetry with a satisfactory accuracy for depths down to 30 m.
引用
收藏
页数:16
相关论文
共 50 条
  • [31] Analysis of sentinel-2 image time series for enhancing satellite-derived bathymetry
    Zhuang, Qizhi
    Gao, Shanlin
    Liu, Yitong
    Lu, Zixuan
    Chu, Hengyong
    Xiao, Jianbo
    Cheng, Jian
    Hu, Qixin
    Chu, Sensen
    MARINE GEODESY, 2025,
  • [32] ORTHOGONAL TRANSFORMATION OF SEGMENTED IMAGES FROM THE SATELLITE SENTINEL-2
    Nedkov, Roumen
    COMPTES RENDUS DE L ACADEMIE BULGARE DES SCIENCES, 2017, 70 (05): : 687 - 692
  • [33] Modeling of Durum Wheat Yield Based on Sentinel-2 Imagery
    Cavalaris, Chris
    Megoudi, Sofia
    Maxouri, Maria
    Anatolitis, Konstantinos
    Sifakis, Marios
    Levizou, Efi
    Kyparissis, Aris
    AGRONOMY-BASEL, 2021, 11 (08):
  • [34] Extracting Citrus-Growing Regions by Multiscale UNet Using Sentinel-2 Satellite Imagery
    Li, Yong
    Liu, Wenjing
    Ge, Ying
    Yuan, Sai
    Zhang, Tingxuan
    Liu, Xiuhui
    REMOTE SENSING, 2024, 16 (01)
  • [35] ESTIMATION OF EVAPOTRANSPIRATION OF A VINEYARD OF TABLE GRAPES (Vitis vinifera) USING SENTINEL-2 SATELLITE IMAGERY
    Manuel Salvador-Castillo, Jose
    Alejandro Bolanos-Gonzalez, Martin
    Cesar Rodriguez, Julio
    Palacios-Velez, Enrique
    Alberto Palacios-Sanchez, Luis
    Watts, Christopher
    Lizarraga-Celaya, Carlos
    Ortega-Farias, Samuel
    Er-Raki, Salah
    AGROCIENCIA, 2021, 55 (05) : 369 - 387
  • [36] Index-Based Identification of Surface Water Resources Using Sentinel-2 Satellite Imagery
    Sekertekin, Aliihsan
    Cicekli, Sevim Yasemin
    Arslan, Niyazi
    2018 2ND INTERNATIONAL SYMPOSIUM ON MULTIDISCIPLINARY STUDIES AND INNOVATIVE TECHNOLOGIES (ISMSIT), 2018, : 610 - 614
  • [37] Object-based water body extraction model using Sentinel-2 satellite imagery
    Kaplan, Gordana
    Avdan, Ugur
    EUROPEAN JOURNAL OF REMOTE SENSING, 2017, 50 (01) : 137 - 143
  • [38] Satellite-derived bathymetry in optically complex waters using a model inversion approach and Sentinel-2 data
    Casal, Gema
    Hedley, John D.
    Monteys, Xavier
    Harris, Paul
    Cahalane, Conor
    McCarthy, Tim
    ESTUARINE COASTAL AND SHELF SCIENCE, 2020, 241
  • [39] Assessment of empirical algorithms for bathymetry extraction using Sentinel-2 data
    Casal, Gema
    Monteys, Xavier
    Hedley, John
    Harris, Paul
    Cahalane, Conor
    McCarthy, Tim
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2019, 40 (08) : 2855 - 2879
  • [40] Deep Learning and Transfer Learning applied to Sentinel-1 DInSAR and Sentinel-2 optical satellite imagery for change detection
    Karim, Zainoolabadien
    van Zyl, Terence
    2020 INTERNATIONAL SAUPEC/ROBMECH/PRASA CONFERENCE, 2020, : 579 - 585