Articles | Volume 16, issue 11
https://doi.org/10.5194/essd-16-5311-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-5311-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Spatio-temporal changes in China's mainland shorelines over 30 years using Landsat time series data (1990–2019)
Gang Yang
Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo 315211, China
State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Ke Huang
Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo 315211, China
Lin Zhu
Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo 315211, China
Weiwei Sun
CORRESPONDING AUTHOR
Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo 315211, China
Chao Chen
School of Geography Science and Geomatics Engineering, Suzhou University of Science and Technology, Suzhou 215009, China
Xiangchao Meng
Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo 315211, China
Lihua Wang
Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo 315211, China
Yong Ge
State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Related authors
No articles found.
Yuehong Chen, Congcong Xu, Yong Ge, Xiaoxiang Zhang, and Ya'nan Zhou
Earth Syst. Sci. Data, 16, 3705–3718, https://doi.org/10.5194/essd-16-3705-2024, https://doi.org/10.5194/essd-16-3705-2024, 2024
Short summary
Short summary
Population data is crucial for human–nature interactions. Gridded population data can address limitations of census data in irregular units. In China, rapid urbanization necessitates timely and accurate population grids. However, existing datasets for China are either outdated or lack recent census data. Hence, a novel approach was developed to disaggregate China’s seventh census data into 100 m population grids. The resulting dataset outperformed the existing LandScan and WorldPop datasets.
Zhixiang Yin, Xiaodong Li, Yong Ge, Cheng Shang, Xinyan Li, Yun Du, and Feng Ling
The Cryosphere, 15, 2835–2856, https://doi.org/10.5194/tc-15-2835-2021, https://doi.org/10.5194/tc-15-2835-2021, 2021
Short summary
Short summary
MODIS thermal infrared (TIR) imagery provides promising data to study the rapid variations in the Arctic turbulent heat flux (THF). The accuracy of estimated THF, however, is low (especially for small leads) due to the coarse resolution of the MODIS TIR data. We train a deep neural network to enhance the spatial resolution of estimated THF over leads from MODIS TIR imagery. The method is found to be effective and can generate a result which is close to that derived from Landsat-8 TIR imagery.
Related subject area
Domain: ESSD – Ocean | Subject: Physical oceanography
ISASO2: recent trends and regional patterns of ocean dissolved oxygen change
Constructing a 22-year internal wave dataset for the northern South China Sea: spatiotemporal analysis using MODIS imagery and deep learning
Near-real-time atmospheric and oceanic science products of Himawari-8 and Himawari-9 geostationary satellites over the South China Sea
High-resolution observations of the ocean upper layer south of Cape St. Vincent, the western northern margin of the Gulf of Cádiz
Catalogue of coastal-based instances with bathymetric and topographic data
Oceanographic monitoring in Hornsund fjord, Svalbard
Salinity and Stratification at the Sea Ice Edge (SASSIE): an oceanographic field campaign in the Beaufort Sea
Weekly green tide mapping in the Yellow Sea with deep learning: integrating optical and synthetic aperture radar ocean imagery
IAPv4 ocean temperature and ocean heat content gridded dataset
Probabilistic reconstruction of sea-level changes and their causes since 1900
Global Coastal Characteristics (GCC): a global dataset of geophysical, hydrodynamic, and socioeconomic coastal indicators
Insights from a topo-bathymetric and oceanographic dataset for coastal flooding studies: the French Flooding Prevention Action Program of Saint-Malo
A Moored Array Observation Dataset for Air-Sea·Surface, Upper and Bottom Ocean in the Northern South China Sea during 2014–2015 (MASCS 1.0)
Gap-filling techniques applied to the GOCI-derived daily sea surface salinity product for the Changjiang diluted water front in the East China Sea
A daily reconstructed chlorophyll-a dataset in the South China Sea from MODIS using OI-SwinUnet
Coastal Atmosphere & Sea Time Series (CoASTS) and Bio-Optical mapping of Marine optical Properties (BiOMaP): the CoASTS-BiOMaP dataset
Underwater light environment in Arctic fjords
A new multi-resolution bathymetric dataset of the Gulf of Naples (Italy) from complementary multi-beam echosounders
Multiyear surface wave dataset from the subsurface “DeepLev” eastern Levantine moored station
A Submesoscale Eddy Identification Dataset in the Northwest Pacific Ocean Derived from GOCI I Chlorophyll–a Data based on Deep Learning
SDUST2020MGCR: a global marine gravity change rate model determined from multi-satellite altimeter data
Lagrangian surface drifter observations in the North Sea: an overview of high-resolution tidal dynamics and surface currents
The physical and biogeochemical parameters along the coastal waters of Saudi Arabia during field surveys in summer, 2021
A Lagrangian coherent eddy atlas for biogeochemical applications in the North Pacific Subtropical Gyre
Global marine gravity gradient tensor inverted from altimetry-derived deflections of the vertical: CUGB2023GRAD
Reconstruction of hourly coastal water levels and counterfactuals without sea level rise for impact attribution
3D reconstruction of horizontal and vertical quasi-geostrophic currents in the North Atlantic Ocean
Laboratory data linking the reconfiguration of and drag on individual plants to the velocity structure and wave dissipation over a meadow of salt marsh plants under waves with and without current
Exploring multi-decadal time series of temperature extremes in Australian coastal waters
Measurements of morphodynamics of a sheltered beach along the Dutch Wadden Sea
Lagoon hydrodynamics of pearl farming islands: the case of Gambier (French Polynesia)
Oceanographic dataset collected during the 2021 scientific expedition of the Canadian Coast Guard Ship Amundsen
Reprocessing of XBT profiles from the Ligurian and Tyrrhenian seas over the time period 1999–2019 with full metadata upgrade
Extension of a high temporal resolution sea level time series at Socoa (Saint-Jean-de-Luz, France) back to 1875
Hyperspectral reflectance of pristine, ocean weathered and biofouled plastics from a dry to wet and submerged state
Lagoon hydrodynamics of pearl farming atolls: the case of Raroia, Takapoto, Apataki and Takaroa (French Polynesia)
Measurements of nearshore ocean-surface kinematics through coherent arrays of free-drifting buoys
A Mediterranean drifter dataset
The DTU21 global mean sea surface and first evaluation
A dataset for investigating socio-ecological changes in Arctic fjords
Dataset of depth and temperature profiles obtained from 2012 to 2020 using commercial fishing vessels of the AdriFOOS fleet in the Adriatic Sea
Measurements and modeling of water levels, currents, density, and wave climate on a semi-enclosed tidal bay, Cádiz (southwest Spain)
Wind wave and water level dataset for Hornsund, Svalbard (2013–2021)
Deep-water hydrodynamic observations around a cold-water coral habitat in a submarine canyon in the eastern Ligurian Sea (Mediterranean Sea)
Ocean cross-validated observations from R/Vs L'Atalante, Maria S. Merian, and Meteor and related platforms as part of the EUREC4A-OA/ATOMIC campaign
A global Lagrangian eddy dataset based on satellite altimetry
The sea level time series of Trieste, Molo Sartorio, Italy (1869–2021)
Southern Europe and western Asian marine heatwaves (SEWA-MHWs): a dataset based on macroevents
An evaluation of long-term physical and hydrochemical measurements at the Sylt Roads Marine Observatory (1973–2019), Wadden Sea, North Sea
Annual hydrographic variability in Antarctic coastal waters infused with glacial inflow
Nicolas Kolodziejczyk, Esther Portela, Virginie Thierry, and Annaig Prigent
Earth Syst. Sci. Data, 16, 5191–5206, https://doi.org/10.5194/essd-16-5191-2024, https://doi.org/10.5194/essd-16-5191-2024, 2024
Short summary
Short summary
Oceanic dissolved oxygen (DO) is fundamental for ocean biogeochemical cycles and marine life. To ease the computation of the ocean oxygen budget from in situ DO data, mapping of data on a regular 3D grid is useful. Here, we present a new DO gridded product from the Argo database. We compare it with existing DO mapping from a historical dataset. We suggest that the ocean has generally been losing oxygen since the 1980s, but large interannual and regional variabilities should be considered.
Xudong Zhang and Xiaofeng Li
Earth Syst. Sci. Data, 16, 5131–5144, https://doi.org/10.5194/essd-16-5131-2024, https://doi.org/10.5194/essd-16-5131-2024, 2024
Short summary
Short summary
Internal wave (IW) is an important ocean process and is frequently observed in the South China Sea (SCS). This study presents a detailed IW dataset for the northern SCS spanning from 2000 to 2022, with a spatial resolution of 250 m, comprising 3085 IW MODIS images. This dataset can enhance understanding of IW dynamics and serve as a valuable resource for studying ocean dynamics, validating numerical models, and advancing AI-driven model building, fostering further exploration into IW phenomena.
Jian Liu, Jingjing Yu, Chuyong Lin, Min He, Haiyan Liu, Wei Wang, and Min Min
Earth Syst. Sci. Data, 16, 4949–4969, https://doi.org/10.5194/essd-16-4949-2024, https://doi.org/10.5194/essd-16-4949-2024, 2024
Short summary
Short summary
The Japanese Himawari-8 and Himawari-9 (H8/9) geostationary (GEO) satellites are strategically positioned over the South China Sea (SCS), spanning from 3 November 2022 to the present. They mainly provide cloud mask, fraction, height, phase, optical, and microphysical property; layered precipitable water; and sea surface temperature products within a temporal resolution of 10 min and a gridded resolution of 0.05° × 0.05°.
Sarah A. Rautenbach, Carlos Mendes de Sousa, Mafalda Carapuço, and Paulo Relvas
Earth Syst. Sci. Data, 16, 4641–4654, https://doi.org/10.5194/essd-16-4641-2024, https://doi.org/10.5194/essd-16-4641-2024, 2024
Short summary
Short summary
This article presents the data of a 4-month observation of the Iberian Margin Cape St. Vincent ocean observatory, in Portugal (2022), a European Multidisciplinary Seafloor and water column Observatory node. Three instruments at depths between 150 and 200 m collected physical/biogeochemical parameters at different spatial and temporal scales. EMSO-ERIC aims at developing strategies to enable sustainable ocean observation with regards to costs, time, and resolution.
Owein Thuillier, Nicolas Le Josse, Alexandru-Liviu Olteanu, Marc Sevaux, and Hervé Tanguy
Earth Syst. Sci. Data, 16, 4529–4556, https://doi.org/10.5194/essd-16-4529-2024, https://doi.org/10.5194/essd-16-4529-2024, 2024
Short summary
Short summary
Our study unveils a comprehensive catalogue of 17 700 unique coastal digital elevation models (DEMs) derived from the General Bathymetric Chart of the Oceans (GEBCO) as of 2022. These DEMs are designed to support a variety of scientific and educational purposes. Organised into three libraries, they cover a wide range of coastal geometries and different sizes. Data and custom colour palettes for visualisation are made freely available online, promoting open science and collaboration.
Meri Korhonen, Mateusz Moskalik, Oskar Głowacki, and Vineet Jain
Earth Syst. Sci. Data, 16, 4511–4527, https://doi.org/10.5194/essd-16-4511-2024, https://doi.org/10.5194/essd-16-4511-2024, 2024
Short summary
Short summary
Since 2015, temperature and salinity have been monitored in Hornsund fjord (Svalbard), where retreating glaciers add meltwater and terrestrial matter to coastal waters. Therefore, turbidity and water sampling for suspended sediment concentration and sediment deposition are measured. The monitoring spans from May to October, enabling studies on seasonality and its variability over the years, and the dataset covers the whole fjord, including the inner basins in close proximity to the glaciers.
Kyla Drushka, Elizabeth Westbrook, Frederick M. Bingham, Peter Gaube, Suzanne Dickinson, Severine Fournier, Viviane Menezes, Sidharth Misra, Jaynice Pérez Valentín, Edwin J. Rainville, Julian J. Schanze, Carlyn Schmidgall, Andrey Shcherbina, Michael Steele, Jim Thomson, and Seth Zippel
Earth Syst. Sci. Data, 16, 4209–4242, https://doi.org/10.5194/essd-16-4209-2024, https://doi.org/10.5194/essd-16-4209-2024, 2024
Short summary
Short summary
The NASA SASSIE mission aims to understand the role of salinity in modifying sea ice formation in early autumn. The 2022 SASSIE campaign collected measurements of upper-ocean properties, including stratification (layering of the ocean) and air–sea fluxes in the Beaufort Sea. These data are presented here and made publicly available on the NASA Physical Oceanography Distributed Active Archive Center (PO.DAAC), along with code to manipulate the data and generate the figures presented herein.
Le Gao, Yuan Guo, and Xiaofeng Li
Earth Syst. Sci. Data, 16, 4189–4207, https://doi.org/10.5194/essd-16-4189-2024, https://doi.org/10.5194/essd-16-4189-2024, 2024
Short summary
Short summary
Since 2008, the Yellow Sea has faced a significant ecological issue, the green tide, which has become one of the world's largest marine disasters. Satellite remote sensing plays a pivotal role in detecting this phenomenon. This study uses AI-based models to extract the daily green tide from MODIS and SAR images and integrates these daily data to introduce a continuous weekly dataset, which aids research in disaster simulation, forecasting, and prevention.
Lijing Cheng, Yuying Pan, Zhetao Tan, Huayi Zheng, Yujing Zhu, Wangxu Wei, Juan Du, Huifeng Yuan, Guancheng Li, Hanlin Ye, Viktor Gouretski, Yuanlong Li, Kevin E. Trenberth, John Abraham, Yuchun Jin, Franco Reseghetti, Xiaopei Lin, Bin Zhang, Gengxin Chen, Michael E. Mann, and Jiang Zhu
Earth Syst. Sci. Data, 16, 3517–3546, https://doi.org/10.5194/essd-16-3517-2024, https://doi.org/10.5194/essd-16-3517-2024, 2024
Short summary
Short summary
Observational gridded products are essential for understanding the ocean, the atmosphere, and climate change; they support policy decisions and socioeconomic developments. This study provides an update of an ocean subsurface temperature and ocean heat content gridded product, named the IAPv4 data product, which is available for the upper 6000 m (119 levels) since 1940 (more reliable after ~1955) for monthly and 1° × 1° temporal and spatial resolutions.
Sönke Dangendorf, Qiang Sun, Thomas Wahl, Philip Thompson, Jerry X. Mitrovica, and Ben Hamlington
Earth Syst. Sci. Data, 16, 3471–3494, https://doi.org/10.5194/essd-16-3471-2024, https://doi.org/10.5194/essd-16-3471-2024, 2024
Short summary
Short summary
Sea-level information from the global ocean is sparse in time and space, with comprehensive data being limited to the period since 2005. Here we provide a novel reconstruction of sea level and its contributing causes, as determined by a Kalman smoother approach applied to tide gauge records over the period 1900–2021. The new reconstruction shows a continuing acceleration in global mean sea-level rise since 1970 that is dominated by melting land ice. Contributors vary significantly by region.
Panagiotis Athanasiou, Ap van Dongeren, Maarten Pronk, Alessio Giardino, Michalis Vousdoukas, and Roshanka Ranasinghe
Earth Syst. Sci. Data, 16, 3433–3452, https://doi.org/10.5194/essd-16-3433-2024, https://doi.org/10.5194/essd-16-3433-2024, 2024
Short summary
Short summary
The shape of the coast, the intensity of waves, the height of the water levels, the presence of people or critical infrastructure, and the land use are important information to assess the vulnerability of the coast to coastal hazards. Here, we provide 80 indicators of this kind at consistent locations along the global ice-free coastline using open-access global datasets. These can be valuable for quick assessments of the vulnerability of the coast and at data-poor locations.
Léo Seyfried, Laurie Biscara, Héloïse Michaud, Fabien Leckler, Audrey Pasquet, Marc Pezerat, and Clément Gicquel
Earth Syst. Sci. Data, 16, 3345–3367, https://doi.org/10.5194/essd-16-3345-2024, https://doi.org/10.5194/essd-16-3345-2024, 2024
Short summary
Short summary
In Saint-Malo, France, an initiative to enhance marine submersion prevention began in 2018. Shom conducted an extensive sea campaign, mapping the bay's topography and exploring coastal processes. High-resolution data improve knowledge of the interactions between waves, tide and surge and determine processes responsible for submersion. Beyond science, these findings contribute crucially to a local warning system, providing a tangible solution to protect the community from coastal threats.
Han Zhang, Dake Chen, Tongya Liu, Di Tian, Min He, Qi Li, and Jian Liu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-224, https://doi.org/10.5194/essd-2024-224, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
The manuscript provides a moored array dataset (MASCS 1.0) of the observation that consists of five buoys and four moorings in the northern South China Sea during 2014 to 2015. The moored array is influenced by atmospheric forcing such as tropical cyclones and monsoon, as well as oceanic tides and flows. The data reveals variations of air-sea interface and ocean itself, which are valuable for studies on air-sea interactions and ocean dynamics in the northern South China Sea.
Jisun Shin, Dae-Won Kim, So-Hyun Kim, Gi Seop Lee, Boo-Keun Khim, and Young-Heon Jo
Earth Syst. Sci. Data, 16, 3193–3211, https://doi.org/10.5194/essd-16-3193-2024, https://doi.org/10.5194/essd-16-3193-2024, 2024
Short summary
Short summary
We overcame the limitations of satellite and reanalysis sea surface salinity (SSS) datasets and produced a gap-free gridded SSS product with reasonable accuracy and a spatial resolution of 1 km using a machine learning model. Our data enabled the recognition of SSS distribution and movement patterns of the Changjiang diluted water (CDW) front in the East China Sea (ECS) during summer. These results will further advance our understanding and monitoring of long-term SSS variations in the ECS.
Haibin Ye, Chaoyu Yang, Yuan Dong, Shilin Tang, and Chuqun Chen
Earth Syst. Sci. Data, 16, 3125–3147, https://doi.org/10.5194/essd-16-3125-2024, https://doi.org/10.5194/essd-16-3125-2024, 2024
Short summary
Short summary
A deep-learning model for gap-filling based on expected variance was developed. OI-SwinUnet achieves good performance reconstructing chlorophyll-a concentration data on the South China Sea. The reconstructed dataset depicts both the spatiotemporal patterns at the seasonal scale and a fast-change process at the weather scale. Reconstructed data show chlorophyll perturbations of individual eddies at different life stages, giving academics a unique and complete perspective on eddy studies.
Giuseppe Zibordi and Jean-François Berthon
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-240, https://doi.org/10.5194/essd-2024-240, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
The Coastal Atmosphere & Sea Time Series (CoASTS) and the Bio-Optical mapping of Marine optical Properties (BiOMaP) programs produced bio-optical data supporting satellite ocean color applications across European seas for almost two decades. CoASTS and BiOMaP applied equal standardized instruments, measurement methods, quality control schemes and processing codes to ensure temporal and spatial consistency to data products.
Robert W. Schlegel, Rakesh Kumar Singh, Bernard Gentili, Simon Bélanger, Laura Castro de la Guardia, Dorte Krause-Jensen, Cale A. Miller, Mikael Sejr, and Jean-Pierre Gattuso
Earth Syst. Sci. Data, 16, 2773–2788, https://doi.org/10.5194/essd-16-2773-2024, https://doi.org/10.5194/essd-16-2773-2024, 2024
Short summary
Short summary
Fjords play a vital role in the Arctic ecosystems and human communities. It is therefore important to have as clear of an understanding of the processes within these systems as possible. While temperature and salinity tend to be well measured, light is usually not. The dataset described in this paper uses remotely sensed data from 2003 to 2022 to address this problem by providing high-spatial-resolution surface, water column, and seafloor light data for several well-studied Arctic fjords.
Federica Foglini, Marzia Rovere, Renato Tonielli, Giorgio Castellan, Mariacristina Prampolini, Francesca Budillon, Marco Cuffaro, Gabriella Di Martino, Valentina Grande, Sara Innangi, Maria Filomena Loreto, Leonardo Langone, Fantina Madricardo, Alessandra Mercorella, Paolo Montagna, Camilla Palmiotto, Claudio Pellegrini, Antonio Petrizzo, Lorenzo Petracchini, Alessandro Remia, Marco Sacchi, Daphnie Sanchez Galvez, Anna Nora Tassetti, and Fabio Trincardi
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-135, https://doi.org/10.5194/essd-2024-135, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
In 2022, the new CNR Research Vessel GAIA BLU explored the seafloor of the Naples and Pozzuoli Gulfs, and the Amalfi coastal area (Tyrrhenian Sea, Italy) from 50 to 2000 m water depth, covering 5000 m2 of seafloor. This paper describes data acquisition and processing and provides maps in unprecedented detail of this area abrupt to geological changes and human impacts. These findings support future geological and geomorphological investigations and mapping and monitoring seafloor and habitats.
Nir Haim, Vika Grigorieva, Rotem Soffer, Boaz Mayzel, Timor Katz, Ronen Alkalay, Eli Biton, Ayah Lazar, Hezi Gildor, Ilana Berman-Frank, Yishai Weinstein, Barak Herut, and Yaron Toledo
Earth Syst. Sci. Data, 16, 2659–2668, https://doi.org/10.5194/essd-16-2659-2024, https://doi.org/10.5194/essd-16-2659-2024, 2024
Short summary
Short summary
This paper outlines the process of creating an open-access surface wave dataset, drawing from deep-sea research station observations located 50 km off the coast of Israel. The discussion covers the wave monitoring procedure, from instrument configuration to wave field retrieval, and aspects of quality assurance. The dataset presented spans over 5 years, offering uncommon in situ wave measurements in the deep sea, and addresses the existing gap in wave information within the region.
Yan Wang, Jie Yang, and Ge Chen
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-188, https://doi.org/10.5194/essd-2024-188, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
Mesoscale eddies are ubiquitous in the ocean and account for 90 % of its kinetic energy, but their generation and dissipation struggle to observe with current remote sensing technology. Our submesoscale eddy dataset, formed by suppressing large-scale circulation signals and enhancing small-scale chlorophyll structures, has important implications for understanding marine environments and ecosystems, as well as improving climate model predictions.
Fengshun Zhu, Jinyun Guo, Huiying Zhang, Lingyong Huang, Heping Sun, and Xin Liu
Earth Syst. Sci. Data, 16, 2281–2296, https://doi.org/10.5194/essd-16-2281-2024, https://doi.org/10.5194/essd-16-2281-2024, 2024
Short summary
Short summary
We used multi-satellite altimeter data to construct a high-resolution marine gravity change rate (MGCR) model on 5′×5′ grids, named SDUST2020MGCR. The spatial distribution of SDUST2020MGCR and GRACE MGCR are similar, such as in the eastern seas of Japan (dipole), western seas of the Nicobar Islands (rising), and southern seas of Greenland (falling). The SDUST2020MGCR can provide a detailed view of long-term marine gravity change, which will help to study the seawater mass migration.
Lisa Deyle, Thomas H. Badewien, Oliver Wurl, and Jens Meyerjürgens
Earth Syst. Sci. Data, 16, 2099–2112, https://doi.org/10.5194/essd-16-2099-2024, https://doi.org/10.5194/essd-16-2099-2024, 2024
Short summary
Short summary
A dataset from the North Sea of 85 surface drifters from 2017–2021 is presented. Surface drifters enable the analysis of ocean currents by determining the velocities of surface currents and tidal effects. The entire North Sea has not been studied using drifters before, but the analysis of ocean currents is essential, e.g., to understand the pathways of plastic. The results show that there are strong tidal effects in the shallow North Sea area and strong surface currents in the deep areas.
Yasser O. Abualnaja, Alexandra Pavlidou, James H. Churchill, Ioannis Hatzianestis, Dimitris Velaoras, Harilaos Kontoyiannis, Vassilis P. Papadopoulos, Aristomenis P. Karageorgis, Georgia Assimakopoulou, Helen Kaberi, Theodoros Kannelopoulos, Constantine Parinos, Christina Zeri, Dionysios Ballas, Elli Pitta, Vassiliki Paraskevopoulou, Afroditi Androni, Styliani Chourdaki, Vassileia Fioraki, Stylianos Iliakis, Georgia Kabouri, Angeliki Konstantinopoulou, Georgios Krokos, Dimitra Papageorgiou, Alkiviadis Papageorgiou, Georgios Pappas, Elvira Plakidi, Eleni Rousselaki, Ioanna Stavrakaki, Eleni Tzempelikou, Panagiota Zachioti, Anthi Yfanti, Theodore Zoulias, Abdulah Al Amoudi, Yasser Alshehri, Ahmad Alharbi, Hammad Al Sulami, Taha Boksmati, Rayan Mutwalli, and Ibrahim Hoteit
Earth Syst. Sci. Data, 16, 1703–1731, https://doi.org/10.5194/essd-16-1703-2024, https://doi.org/10.5194/essd-16-1703-2024, 2024
Short summary
Short summary
We present oceanographic measurements obtained during two surveillance cruises conducted in June and September 2021 in the Red Sea and the Arabian Gulf. It is the first multidisciplinary survey within the Saudi Arabian coastal zone, extending from near the Saudi–Jordanian border in the north of the Red Sea to the south close to the Saudi--Yemen border and in the Arabian Gulf. The objective was to record the pollution status along the coastal zone of the kingdom related to specific pressures.
Alexandra E. Jones-Kellett and Michael J. Follows
Earth Syst. Sci. Data, 16, 1475–1501, https://doi.org/10.5194/essd-16-1475-2024, https://doi.org/10.5194/essd-16-1475-2024, 2024
Short summary
Short summary
Ocean eddies can limit horizontal mixing, potentially isolating phytoplankton populations and affecting their concentration. We used two decades of satellite data and computer simulations to identify and track eddy-trapping boundaries in the Pacific Ocean for application in phytoplankton research. Although some eddies trap water masses for months, many continuously mix with surrounding waters. A case study shows how eddy trapping can enhance the signature of a phytoplankton bloom.
Richard Fiifi Annan, Xiaoyun Wan, Ruijie Hao, and Fei Wang
Earth Syst. Sci. Data, 16, 1167–1176, https://doi.org/10.5194/essd-16-1167-2024, https://doi.org/10.5194/essd-16-1167-2024, 2024
Short summary
Short summary
Gravity gradient tensor, a set of six unique gravity signals, is suitable for detecting undersea features. However, due to poor spatial resolution in past years, it has received less research interest and investment. However, current datasets have better accuracy and resolutions, thereby necessitating a revisit. Our analysis shows comparable results with reference models. We conclude that current-generation altimetry datasets can precisely resolve all six gravity gradients.
Simon Treu, Sanne Muis, Sönke Dangendorf, Thomas Wahl, Julius Oelsmann, Stefanie Heinicke, Katja Frieler, and Matthias Mengel
Earth Syst. Sci. Data, 16, 1121–1136, https://doi.org/10.5194/essd-16-1121-2024, https://doi.org/10.5194/essd-16-1121-2024, 2024
Short summary
Short summary
This article describes a reconstruction of monthly coastal water levels from 1900–2015 and hourly data from 1979–2015, both with and without long-term sea level rise. The dataset is based on a combination of three datasets that are focused on different aspects of coastal water levels. Comparison with tide gauge records shows that this combination brings reconstructions closer to the observations compared to the individual datasets.
Sarah Asdar, Daniele Ciani, and Bruno Buongiorno Nardelli
Earth Syst. Sci. Data, 16, 1029–1046, https://doi.org/10.5194/essd-16-1029-2024, https://doi.org/10.5194/essd-16-1029-2024, 2024
Short summary
Short summary
Estimating 3D currents is crucial for the understanding of ocean dynamics, and a precise knowledge of ocean circulation is essential to ensure a sustainable ocean. In this context, a new high-resolution (1 / 10°) data-driven dataset of 3D ocean currents has been developed within the European Space Agency World Ocean Circulation project, providing 10 years (2010–2019) of horizontal and vertical quasi-geostrophic currents at daily resolution over the North Atlantic Ocean, down to 1500 m depth.
Xiaoxia Zhang and Heidi Nepf
Earth Syst. Sci. Data, 16, 1047–1062, https://doi.org/10.5194/essd-16-1047-2024, https://doi.org/10.5194/essd-16-1047-2024, 2024
Short summary
Short summary
This study measured the wave-induced plant drag, flow structure, turbulent intensity, and wave energy attenuation in the presence of a salt marsh. We showed that leaves contribute to most of the total plant drag and wave dissipation. Plant resistance significantly reshapes the velocity profile and enhances turbulence intensity. Adding current obviously impact the plants' wave decay capacity. The dataset can be reused to develop and calibrate marsh-flow theoretical and numerical models.
Michael Hemming, Moninya Roughan, and Amandine Schaeffer
Earth Syst. Sci. Data, 16, 887–901, https://doi.org/10.5194/essd-16-887-2024, https://doi.org/10.5194/essd-16-887-2024, 2024
Short summary
Short summary
We present new datasets that are useful for exploring extreme ocean temperature events in Australian coastal waters. These datasets span multiple decades, starting from the 1940s and 1950s, and include observations from the surface to the bottom at four coastal sites. The datasets provide valuable insights into the intensity, frequency and timing of extreme warm and cold temperature events and include event characteristics such as duration, onset and decline rates and their categorisation.
Marlies A. van der Lugt, Jorn W. Bosma, Matthieu A. de Schipper, Timothy D. Price, Marcel C. G. van Maarseveen, Pieter van der Gaag, Gerben Ruessink, Ad J. H. M. Reniers, and Stefan G. J. Aarninkhof
Earth Syst. Sci. Data, 16, 903–918, https://doi.org/10.5194/essd-16-903-2024, https://doi.org/10.5194/essd-16-903-2024, 2024
Short summary
Short summary
A 6-week field campaign was carried out at a sheltered sandy beach on Texel along the Dutch Wadden Sea with the aim of gaining new insights into the driving processes behind sheltered beach morphodynamics. Detailed measurements of the local hydrodynamics, bed-level changes and sediment composition were collected. The morphological evolution on this sheltered site is the result of the subtle interplay between waves, currents and bed composition.
Oriane Bruyère, Romain Le Gendre, Vetea Liao, and Serge Andréfouët
Earth Syst. Sci. Data, 16, 667–679, https://doi.org/10.5194/essd-16-667-2024, https://doi.org/10.5194/essd-16-667-2024, 2024
Short summary
Short summary
During 2019–2020, the lagoon and forereefs of Gambier Island (French Polynesia) were monitored with oceanographic instruments to measure lagoon hydrodynamics and ocean–lagoon water exchanges. Gambier Island is a key black pearl producer and the study goal was to understand the processes influencing spat collection of pearl oyster Pinctada margaritifera, the species used to produce black pearls. The data set is provided to address local pearl farming questions and other investigations as well.
Tahiana Ratsimbazafy, Thibaud Dezutter, Amélie Desmarais, Daniel Amirault, Pascal Guillot, and Simon Morisset
Earth Syst. Sci. Data, 16, 471–499, https://doi.org/10.5194/essd-16-471-2024, https://doi.org/10.5194/essd-16-471-2024, 2024
Short summary
Short summary
The Canadian Coast Guard Ship has collected oceanographic data across the Canadian Arctic annually since 2003. Such activity aims to support Canadian and international researchers. The ship has several instruments with cutting-edge technology available for research each year during the summer. The data presented here include measurements of physical, chemical and biological variables during the year 2021. Datasets collected from each expedition are available free of charge for the public.
Simona Simoncelli, Franco Reseghetti, Claudia Fratianni, Lijing Cheng, and Giancarlo Raiteri
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-525, https://doi.org/10.5194/essd-2023-525, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
This data review is about the reprocessing of historical XBT profiles from the Ligurian and Tyrrhenian seas over the time period 1999–2019. A thorough data analysis has been performed starting from the original raw data and operational log sheets. The data have been first formatted and standardized according to the latest community best practices and all available metadata have been inserted, including calibration information never used before. A new Quality Control procedure has been applied.
Md Jamal Uddin Khan, Inge Van Den Beld, Guy Wöppelmann, Laurent Testut, Alexa Latapy, and Nicolas Pouvreau
Earth Syst. Sci. Data, 15, 5739–5753, https://doi.org/10.5194/essd-15-5739-2023, https://doi.org/10.5194/essd-15-5739-2023, 2023
Short summary
Short summary
Established in the southwest of France in 1875, the Socoa tide gauge is part of the national sea level monitoring network in France. Through a data archaeology exercise, a large part of the records of this gauge in paper format have been rescued and digitized. The digitized data were processed and quality controlled to produce a uniform hourly sea level time series covering 1875 to the present day. This new dataset is important for climate research on sea level rise, tides, and storm surges.
Robin V. F. de Vries, Shungudzemwoyo P. Garaba, and Sarah-Jeanne Royer
Earth Syst. Sci. Data, 15, 5575–5596, https://doi.org/10.5194/essd-15-5575-2023, https://doi.org/10.5194/essd-15-5575-2023, 2023
Short summary
Short summary
We present a high-quality dataset of hyperspectral point and multipixel reflectance observations of virgin, ocean-harvested, and biofouled multipurpose plastics. Biofouling and a submerged scenario of the dataset further extend the variability in open-access spectral reference libraries that are important in algorithm development with relevance to remote sensing use cases.
Oriane Bruyère, Romain Le Gendre, Mathilde Chauveau, Bertrand Bourgeois, David Varillon, John Butscher, Thomas Trophime, Yann Follin, Jérôme Aucan, Vetea Liao, and Serge Andréfouët
Earth Syst. Sci. Data, 15, 5553–5573, https://doi.org/10.5194/essd-15-5553-2023, https://doi.org/10.5194/essd-15-5553-2023, 2023
Short summary
Short summary
During 2018–2022, four pearl farming Tuamotu atolls (French Polynesia) were studied with oceanographic instruments to measure lagoon hydrodynamics and ocean-lagoon water exchanges. The goal was to gain knowledge on the processes influencing the spat collection of the pearl oyster Pinctada margaritifera, the species used to produce black pearls. A worldwide unique oceanographic atoll data set is provided to address local pearl farming questions and other fundamental and applied investigations.
Edwin Rainville, Jim Thomson, Melissa Moulton, and Morteza Derakhti
Earth Syst. Sci. Data, 15, 5135–5151, https://doi.org/10.5194/essd-15-5135-2023, https://doi.org/10.5194/essd-15-5135-2023, 2023
Short summary
Short summary
Measuring ocean waves nearshore is essential for understanding how the waves impact our coastlines. We designed and deployed many small wave buoys in the nearshore ocean over 27 d in Duck, North Carolina, USA, in 2021. The wave buoys measure their motion as they drift. In this paper, we describe multiple levels of data processing. We explain how this dataset can be used in future studies to investigate nearshore wave kinematics, transport of buoyant particles, and wave-breaking processes.
Alberto Ribotti, Antonio Bussani, Milena Menna, Andrea Satta, Roberto Sorgente, Andrea Cucco, and Riccardo Gerin
Earth Syst. Sci. Data, 15, 4651–4659, https://doi.org/10.5194/essd-15-4651-2023, https://doi.org/10.5194/essd-15-4651-2023, 2023
Short summary
Short summary
Over 100 experiments were realized between 1998 and 2022 in the Mediterranean Sea using surface coastal and offshore Lagrangian drifters. Raw data were initially unified and pre-processed. Then, the integrity of the received data packages was checked and incomplete ones were discarded. Deployment information was retrieved and integrated into the PostgreSQL database. Data were interpolated at defined time intervals, providing a dataset of 158 trajectories, available in different formats.
Ole Baltazar Andersen, Stine Kildegaard Rose, Adili Abulaitijiang, Shengjun Zhang, and Sara Fleury
Earth Syst. Sci. Data, 15, 4065–4075, https://doi.org/10.5194/essd-15-4065-2023, https://doi.org/10.5194/essd-15-4065-2023, 2023
Short summary
Short summary
The mean sea surface (MSS) is an important reference for mapping sea-level changes across the global oceans. It is widely used by space agencies in the definition of sea-level anomalies as mapped by satellite altimetry from space. Here a new fully global high-resolution mean sea surface called DTU21MSS is presented, and a suite of evaluations are performed to demonstrate its performance.
Robert W. Schlegel and Jean-Pierre Gattuso
Earth Syst. Sci. Data, 15, 3733–3746, https://doi.org/10.5194/essd-15-3733-2023, https://doi.org/10.5194/essd-15-3733-2023, 2023
Short summary
Short summary
A single dataset was created for investigations of changes in the socio-ecological systems within seven Arctic fjords by amalgamating roughly 1400 datasets from a number of sources. The many variables in these data were organised into five distinct categories and classified into 14 key drivers. Data for seawater temperature and salinity are available from the late 19th century, with some other drivers having data available from the 1950s and 1960s and the others starting from the 1990s onward.
Pierluigi Penna, Filippo Domenichetti, Andrea Belardinelli, and Michela Martinelli
Earth Syst. Sci. Data, 15, 3513–3527, https://doi.org/10.5194/essd-15-3513-2023, https://doi.org/10.5194/essd-15-3513-2023, 2023
Short summary
Short summary
This work presents the pressure (depth) and temperature profile dataset provided by the AdriFOOS infrastructure in the Adriatic Sea (Mediterranean basin) from 2012 to 2020. Data were subject to quality assurance (QA) and quality control (QC). This infrastructure, based on the ships of opportunity principle and involving the use of commercial fishing vessels, is able to produce huge amounts of useful data both for operational oceanography and fishery biology purposes.
Carmen Zarzuelo, Alejandro López-Ruiz, María Bermúdez, and Miguel Ortega-Sánchez
Earth Syst. Sci. Data, 15, 3095–3110, https://doi.org/10.5194/essd-15-3095-2023, https://doi.org/10.5194/essd-15-3095-2023, 2023
Short summary
Short summary
This paper presents a hydrodynamic dataset for the Bay of Cádiz in southern Spain, a paradigmatic example of a tidal bay of complex geometry under high anthropogenic pressure. The dataset brings together measured and modeled data on water levels, currents, density, and waves for the period 2012–2015. It allows the characterization of the bay dynamics from intratidal to seasonal scales. Potential applications include the study of ocean–bay interactions, wave propagation, or energy assessments.
Zuzanna M. Swirad, Mateusz Moskalik, and Agnieszka Herman
Earth Syst. Sci. Data, 15, 2623–2633, https://doi.org/10.5194/essd-15-2623-2023, https://doi.org/10.5194/essd-15-2623-2023, 2023
Short summary
Short summary
Monitoring ocean waves is important for understanding wave climate and seasonal to longer-term (years to decades) changes. In the Arctic, there is limited freely available observational wave information. We placed sensors at the sea bottom of six bays in Hornsund fjord, Svalbard, and calculated wave energy, wave height and wave period for full hours between July 2013 and February 2021. In this paper, we present the procedure of deriving wave properties from raw pressure measurements.
Tiziana Ciuffardi, Zoi Kokkini, Maristella Berta, Marina Locritani, Andrea Bordone, Ivana Delbono, Mireno Borghini, Maurizio Demarte, Roberta Ivaldi, Federica Pannacciulli, Anna Vetrano, Davide Marini, and Giovanni Caprino
Earth Syst. Sci. Data, 15, 1933–1946, https://doi.org/10.5194/essd-15-1933-2023, https://doi.org/10.5194/essd-15-1933-2023, 2023
Short summary
Short summary
This paper presents the results of the first 2 years of the Levante Canyon Mooring, a mooring line placed since 2020 in the eastern Ligurian Sea, to study a canyon area at about 600 m depth characterized by the presence of cold-water living corals. It provides hydrodynamic and thermohaline measurements along the water column, describing a water-mass distribution coherent with previous evidence in the Ligurian Sea. The data also show a Northern Current episodic and local reversal during summer.
Pierre L'Hégaret, Florian Schütte, Sabrina Speich, Gilles Reverdin, Dariusz B. Baranowski, Rena Czeschel, Tim Fischer, Gregory R. Foltz, Karen J. Heywood, Gerd Krahmann, Rémi Laxenaire, Caroline Le Bihan, Philippe Le Bot, Stéphane Leizour, Callum Rollo, Michael Schlundt, Elizabeth Siddle, Corentin Subirade, Dongxiao Zhang, and Johannes Karstensen
Earth Syst. Sci. Data, 15, 1801–1830, https://doi.org/10.5194/essd-15-1801-2023, https://doi.org/10.5194/essd-15-1801-2023, 2023
Short summary
Short summary
In early 2020, the EUREC4A-OA/ATOMIC experiment took place in the northwestern Tropical Atlantic Ocean, a dynamical region where different water masses interact. Four oceanographic vessels and a fleet of autonomous devices were deployed to study the processes at play and sample the upper ocean, each with its own observing capability. The article first describes the data calibration and validation and second their cross-validation, using a hierarchy of instruments and estimating the uncertainty.
Tongya Liu and Ryan Abernathey
Earth Syst. Sci. Data, 15, 1765–1778, https://doi.org/10.5194/essd-15-1765-2023, https://doi.org/10.5194/essd-15-1765-2023, 2023
Short summary
Short summary
Nearly all existing datasets of mesoscale eddies are based on the Eulerian method because of its operational simplicity. Using satellite observations and a Lagrangian method, we present a global Lagrangian eddy dataset (GLED v1.0). We conduct the statistical comparison between two types of eddies and the dataset validation. Our dataset offers relief from dilemma that the Eulerian eddy dataset is nearly the only option for studying mesoscale eddies.
Fabio Raicich
Earth Syst. Sci. Data, 15, 1749–1763, https://doi.org/10.5194/essd-15-1749-2023, https://doi.org/10.5194/essd-15-1749-2023, 2023
Short summary
Short summary
In the changing climate, long sea level time series are essential for studying the variability of the mean sea level and the occurrence of extreme events on different timescales. This work summarizes the rescue and quality control of the ultra-centennial sea level data set of Trieste, Italy. The whole time series is characterized by a linear trend of about 1.4 mm yr−1, the period corresponding to the altimetry coverage by a trend of about 3.0 mm yr−1, similarly to the global ocean.
Giulia Bonino, Simona Masina, Giuliano Galimberti, and Matteo Moretti
Earth Syst. Sci. Data, 15, 1269–1285, https://doi.org/10.5194/essd-15-1269-2023, https://doi.org/10.5194/essd-15-1269-2023, 2023
Short summary
Short summary
We present a unique observational dataset of marine heat wave (MHW) macroevents and their characteristics over southern Europe and western Asian (SEWA) basins in the SEWA-MHW dataset. This dataset is the first effort in the literature to archive extremely hot sea surface temperature macroevents. The advantages of the availability of SEWA-MHWs are avoiding the waste of computational resources to detect MHWs and building a consistent framework which would increase comparability among MHW studies.
Johannes J. Rick, Mirco Scharfe, Tatyana Romanova, Justus E. E. van Beusekom, Ragnhild Asmus, Harald Asmus, Finn Mielck, Anja Kamp, Rainer Sieger, and Karen H. Wiltshire
Earth Syst. Sci. Data, 15, 1037–1057, https://doi.org/10.5194/essd-15-1037-2023, https://doi.org/10.5194/essd-15-1037-2023, 2023
Short summary
Short summary
The Sylt Roads (Wadden Sea) time series is illustrated. Since 1984, the water temperature has risen by 1.1 °C, while pH and salinity decreased by 0.2 and 0.3 units. Nutrients (P, N) displayed a period of high eutrophication until 1998 and have decreased since 1999, while Si showed a parallel increase. Chlorophyll did not mirror these changes, probably due to a switch in nutrient limitation. Until 1998, algae were primarily limited by Si, and since 1999, P limitation has become more important.
Maria Osińska, Kornelia A. Wójcik-Długoborska, and Robert J. Bialik
Earth Syst. Sci. Data, 15, 607–616, https://doi.org/10.5194/essd-15-607-2023, https://doi.org/10.5194/essd-15-607-2023, 2023
Short summary
Short summary
Water properties, including temperature, conductivity, turbidity and pH as well as the dissolved oxygen, dissolved organic matter, chlorophyll-a and phycoerythrin contents, were investigated in 31 different locations at up to 100 m depth over a period of 38 months in a glacial bay in Antarctica. These investigations were carried out 142 times in all seasons of the year, resulting in a unique dataset of information about seasonal and long-term changes in polar water properties.
Cited articles
Abdelsamea, M. M., Gnecco, G., and Gaber, M. M.: An efficient Self-Organizing Active Contour model for image segmentation, Neurocomputing, 149, 820–835, 2015.
Aedla, R., Dwarakish, G., and Reddy, D. V.: Automatic shoreline detection and change detection analysis of netravati-gurpurrivermouth using histogram equalization and adaptive thresholding techniques, Aquat. Pr., 4, 563–570, 2015.
Airouche, M., Bentabet, L., and Zelmat, M.: Image segmentation using active contour model and level set method applied to detect oil spills, in: Proceedings of the World Congress on Engineering, London, UK, 1–3 July 2009, WCE 2009, 1–5, ISBN: 978-988-17012-5-1, 2009.
Apostolopoulos, D. N. and Nikolakopoulos, K. G.: Assessment and quantification of the accuracy of low-and high-resolution remote sensing data for shoreline monitoring, ISPRS Int. J. Geo-Inf., 9, 391, https://doi.org/10.3390/ijgi9060391, 2020.
Baig, M. R. I., Ahmad, I. A., Shahfahad, Tayyab, M., and Rahman, A.: Analysis of shoreline changes in Vishakhapatnam coastal tract of Andhra Pradesh, India: an application of digital shoreline analysis system (DSAS), Annals of GIS, 26, 361–376, 2020.
Bishop-Taylor, R., Nanson, R., Sagar, S., and Lymburner, L.: Mapping Australia's dynamic coastline at mean sea level using three decades of Landsat imagery, Remote Sens. Environ., 267, 112734, https://doi.org/10.1016/j.rse.2021.112734, 2021.
Cai, H., Li, C., Luan, X., Ai, B., Yan, L., and Wen, Z.: Analysis of the spatiotemporal evolution of the coastline of Jiaozhou Bay and its driving factors, Ocean Coast. Manage., 226, 106246, https://doi.org/10.1016/j.ocecoaman.2022.106246, 2022.
Cao, W., Zhou, Y., Li, R., and Li, X.: Mapping changes in coastlines and tidal flats in developing islands using the full time series of Landsat images, Remote Sens. Environ., 239, 111665, https://doi.org/10.1016/j.rse.2020.111665, 2020.
Chaudhry, M. H.: Open-channel flow, Springer, https://doi.org/10.1007/978-3-030-96447-4, 2008.
Chen, C., Bu, J., Zhang, Y., Zhuang, Y., Chu, Y., Hu, J., and Guo, B.: The application of the tasseled cap transformation and feature knowledge for the extraction of coastline information from remote sensing images, Adv. Space Res., 64, 1780–1791, 2019.
Chen, C., Liang, J., Xie, F., Hu, Z., Sun, W., Yang, G., Yu, J., Chen, L., Wang, L., and Wang, L.: Temporal and spatial variation of coastline using remote sensing images for Zhoushan archipelago, China, Int. J. Appl. Earth Obs., 107, 102711, https://doi.org/10.1016/j.jag.2022.102711, 2022.
Dai, C., Howat, I. M., Larour, E., and Husby, E.: Coastline extraction from repeat high resolution satellite imagery, Remote Sens. Environ., 229, 260–270, 2019.
Dang, K. B., Vu, K. C., Nguyen, H., Nguyen, D. A., Nguyen, T. D. L., Pham, T. P. N., Giang, T. L., Nguyen, H. D., and Do, T. H.: Application of deep learning models to detect coastlines and shorelines, J. Environ. Manage., 320, 115732, https://doi.org/10.1016/j.jenvman.2022.115732, 2022.
Department of Natural Resources of Zhejiang Province: https://zrzyt.zj.gov.cn/art/2019/4/29/art_1229098242_256518.html (last access: 12 November 2024), 2019.
Dike, E. C., Ameme, B. G., and Efeovbokhan, O.: Shoreline position trends in the Niger Delta: analyzing spatial and temporal changes through Sentinel-1 SAR imagery, Geomat. Nat. Haz. Risk, 15, 2346150, https://doi.org/10.1080/19475705.2024.2346150, 2024.
Dillenburg, S. R., Roy, P. S., Cowell, P. J., and Tomazelli, L. J.: Influence of antecedent topography on coastal evolution as tested by the shoreface translation-barrier model (STM), J. Coastal Res., 16, 71–81, 2000.
Ding, Y., Yang, X., Jin, H., Wang, Z., Liu, Y., Liu, B., Zhang, J., Liu, X., Gao, K., and Meng, D.: Monitoring coastline changes of the Malay Islands based on Google Earth Engine and dense time-series remote sensing images, Remote Sensing, 13, 3842, https://doi.org/10.3390/rs13193842, 2021.
Donchyts, G., Baart, F., Winsemius, H., Gorelick, N., Kwadijk, J., and Van De Giesen, N.: Earth's surface water change over the past 30 years, Nat. Clim. Change, 6, 810–813, 2016.
Fogarin, S., Zanetti, M., Dal Barco, M., Zennaro, F., Furlan, E., Torresan, S., Pham, H., and Critto, A.: Combining remote sensing analysis with machine learning to evaluate short-term coastal evolution trend in the shoreline of Venice, Sci. Total Environ., 859, 160293, https://doi.org/10.1016/j.scitotenv.2022.160293, 2023.
Ge, X., Sun, X., and Liu, Z.: Object-oriented coastline classification and extraction from remote sensing imagery, in: Remote Sensing of the Environment: 18th National Symposium on Remote Sensing of China, Wuhan, China, 20–23 October 2012, Proc. SPIE 9158, 131–137, https://doi.org/10.1117/12.2063845, 2014.
Hong Kong And Macao Office Of The State Council: https://gdii.gd.gov.cn/zcgh3227/content/mpost_937988.html (last access: 12 November 2024) 2009.
Hu, R., Yao, L., Yu, J., Chen, P., and Wang, D.: Remote Sensing of the Coastline Variation of the Guangdong–Hongkong–Macao Greater Bay Area in the Past Four Decades, Journal of Marine Science and Engineering, 9, 1318, https://doi.org/10.3390/jmse9121318, 2021.
Hu, X. and Wang, Y.: Monitoring coastline variations in the Pearl River Estuary from 1978 to 2018 by integrating Canny edge detection and Otsu methods using long time series Landsat dataset, Catena, 209, 105840, https://doi.org/10.1016/j.catena.2021.105840, 2022.
Hu, Y., Tian, B., Yuan, L., Li, X., Huang, Y., Shi, R., Jiang, X., and Sun, C.: Mapping coastal salt marshes in China using time series of Sentinel-1 SAR, ISPRS J. Photogramm., 173, 122–134, 2021.
Jia, M., Wang, Z., Mao, D., Ren, C., Wang, C., and Wang, Y.: Rapid, robust, and automated mapping of tidal flats in China using time series Sentinel-2 images and Google Earth Engine, Remote Sens. Environ., 255, 112285, https://doi.org/10.1016/j.rse.2021.112285, 2021.
Karantzalos, K., Argialas, D., and Georgopoulos, A.: Towards automatic detection of coastlines from satellite imagery, in: 2002 14th International Conference on Digital Signal Processing Proceedings. DSP 2002 (Cat. No. 02TH8628), Santorini, Greece, 1–3 July 2002, IEEE, 897–900, https://doi.org/10.1109/ICDSP.2002.1028235, 2002.
Kuleli, T., Guneroglu, A., Karsli, F., and Dihkan, M.: Automatic detection of shoreline change on coastal Ramsar wetlands of Turkey, Ocean Eng., 38, 1141–1149, 2011.
Lhermitte, S., Verbesselt, J., Verstraeten, W. W., and Coppin, P.: A comparison of time series similarity measures for classification and change detection of ecosystem dynamics, Remote Sens. Environ., 115, 3129–3152, 2011.
Li, H., Jia, M., Zhang, R., Ren, Y., and Wen, X.: Incorporating the plant phenological trajectory into mangrove species mapping with dense time series Sentinel-2 imagery and the Google Earth Engine platform, Remote Sensing, 11, 2479, https://doi.org/10.3390/rs11212479, 2019.
Li, J., Tian, P., Shao, S., and Zhao, M.: East China Sea Coastline Changes Dataset in Five-Year Increments (1990–2015), Digital Journal of Global Change Data Repository [data set], https://doi.org/10.3974/geodb.2019.04.14.V1, 2019.
Li, J., Ye, M., Pu, R., Liu, Y., Guo, Q., Feng, B., Huang, R., and He, G.: Spatiotemporal change patterns of coastlines in Zhejiang Province, China, over the last twenty-five years, Sustainability, 10, 477, https://doi.org/10.3390/su10020477, 2018.
Li, K., Zhang, L., Chen, B., Zuo, J., Yang, F., and Li, L.: Analysis of China's Coastline Changes during 1990–2020, Remote Sensing, 15, 981, https://doi.org/10.3390/rs15040981, 2023.
Li, W. and Gong, P.: Continuous monitoring of coastline dynamics in western Florida with a 30-year time series of Landsat imagery, Remote Sens. Environ., 179, 196–209, 2016.
Liang, J., Chen, C., Song, Y., Sun, W., and Yang, G.: Long-term mapping of land use and cover changes using Landsat images on the Google Earth Engine Cloud Platform in bay area-A case study of Hangzhou Bay, China, Sustainable Horizons, 7, 100061, https://doi.org/10.1016/j.horiz.2023.100061, 2023.
Liang, L., Liu, Q., Liu, G., Li, X., and Huang, C.: Review of coastline extraction methods based on remote sensing images, J. Geo-Inf. Sci., 20, 1745–1755, 2018.
Lin, S., Yu, X., Li, Y., Zhang, Y., and Zhao, Z.: Fractal characteristics evolution of coastline of the Xiamen island, Adv. Mar. Sci, 38, 121–129, 2020.
Liu, C., Xiao, Y., and Yang, J.: A coastline detection method in polarimetric SAR images mixing the region-based and edge-based active contour models, IEEE T. Geosci. Remote, 55, 3735–3747, 2017.
Liu, C., Shi, R., Zhang, Y., Shen, Y., Ma, J., Wu, L., Chen, W., Doko, T., Chen, L., and Lv, T.: Land Areas, and How Long of Shorelines in the World? – Vector Data Based on Google Earth Images, Journal of Global Change Data & Discovery, 3, 124–148, 2019.
Liu, L., Xu, W., Yue, Q., Teng, X., and Hu, H.: Problems and countermeasures of coastline protection and utilization in China, Ocean Coast. Manage., 153, 124–130, 2018.
Luan, H. L., Ding, P. X., Yang, S. L., and Wang, Z. B.: Accretion-erosion conversion in the subaqueous Yangtze Delta in response to fluvial sediment decline, Geomorphology, 382, 107680, https://doi.org/10.1016/j.geomorph.2021.107680, 2021.
Mandelbrot, B.: How long is the coast of Britain? Statistical self-similarity and fractional dimension, Science, 156, 636–638, 1967.
Mao, D., Liu, M., Wang, Z., Li, L., Man, W., Jia, M., and Zhang, Y.: Rapid invasion of Spartina alterniflora in the coastal zone of mainland China: Spatiotemporal patterns and human prevention, Sensors, 19, 2308, https://doi.org/10.3390/s19102308, 2019.
Mao, D., Wang, Z., Du, B., Li, L., Tian, Y., Jia, M., Zeng, Y., Song, K., Jiang, M., and Wang, Y.: National wetland mapping in China: A new product resulting from object-based and hierarchical classification of Landsat 8 OLI images, ISPRS J. Photogramm., 164, 11–25, 2020.
Mao, Y., Harris, D. L., Xie, Z., and Phinn, S.: Efficient measurement of large-scale decadal shoreline change with increased accuracy in tide-dominated coastal environments with Google Earth Engine, ISPRS J. Photogramm., 181, 385–399, 2021.
Mao, Y., Harris, D. L., Xie, Z., and Phinn, S.: Global coastal geomorphology–integrating earth observation and geospatial data, Remote Sens. Environ., 278, 113082, https://doi.org/10.1016/j.rse.2022.113082, 2022.
Meng, W., Hu, B., He, M., Liu, B., Mo, X., Li, H., Wang, Z., and Zhang, Y.: Temporal-spatial variations and driving factors analysis of coastal reclamation in China, Estuar. Coast. Shelf S., 191, 39–49, 2017.
Mentaschi, L., Vousdoukas, M. I., Pekel, J.-F., Voukouvalas, E., and Feyen, L.: Global long-term observations of coastal erosion and accretion, Scientific Reports, 8, 12876, https://doi.org/10.1038/s41598-018-30904-w, 2018.
Murray, N. J., Clemens, R. S., Phinn, S. R., Possingham, H. P., and Fuller, R. A.: Tracking the rapid loss of tidal wetlands in the Yellow Sea, Front. Ecol. Environ., 12, 267–272, 2014.
Otsu, N.: A threshold selection method from gray-level histograms, IEEE T. Syst. Man Cyb., 9, 62–66, 1979.
Otukei, J. R. and Blaschke, T.: Land cover change assessment using decision trees, support vector machines and maximum likelihood classification algorithms, Int. J. Appl. Earth Obs., 12, S27–S31, 2010.
Paragios, N. and Deriche, R.: Geodesic active contours and level sets for the detection and tracking of moving objects, IEEE T. Pattern Anal., 22, 266–280, 2000.
Pardo-Pascual, J. E., Almonacid-Caballer, J., Ruiz, L. A., and Palomar-Vázquez, J.: Automatic extraction of shorelines from Landsat TM and ETM+ multi-temporal images with subpixel precision, Remote Sens. Environ., 123, 1–11, 2012.
Pekel, J.-F., Cottam, A., Gorelick, N., and Belward, A. S.: High-resolution mapping of global surface water and its long-term changes, Nature, 540, 418–422, 2016.
Peng, J., Chen, S., and Dong, P.: Temporal variation of sediment load in the Yellow River basin, China, and its impacts on the lower reaches and the river delta, Catena, 83, 135–147, 2010.
Qin, G., Fang, Z., Zhao, S., Meng, Y., Sun, W., Yang, G., Wang, L., and Feng, T.: Storm Surge Inundation Modulated by Typhoon Intensities and Tracks: Simulations Using the Regional Ocean Modeling System (ROMS), Journal of Marine Science and Engineering, 11, 1112, https://doi.org/10.3390/jmse11061112, 2023.
Rahman, A. F., Dragoni, D., and El-Masri, B.: Response of the Sundarbans coastline to sea level rise and decreased sediment flow: A remote sensing assessment, Remote Sens. Environ., 115, 3121–3128, 2011.
Sayre, R., Noble, S., Hamann, S., Smith, R., Wright, D., Breyer, S., Butler, K., Van Graafeiland, K., Frye, C., and Karagulle, D.: A new 30 meter resolution global shoreline vector and associated global islands database for the development of standardized ecological coastal units, Journal of Operational Oceanography, 12, S47–S56, 2019.
Schuerch, M., Spencer, T., Temmerman, S., Kirwan, M. L., Wolff, C., Lincke, D., McOwen, C. J., Pickering, M. D., Reef, R., and Vafeidis, A. T.: Future response of global coastal wetlands to sea-level rise, Nature, 561, 231–234, 2018.
Seale, C., Redfern, T., Chatfield, P., Luo, C., and Dempsey, K.: Coastline detection in satellite imagery: A deep learning approach on new benchmark data, Remote Sens. Environ., 278, 113044, https://doi.org/10.1016/j.rse.2022.113044, 2022.
SOA: Statistical Bulletin of Chinese Marine Economy in 2015, SOA Annual Report, https://www.nmdis.org.cn/hygb/zghyjjtjgb/2015nzghyjjtjgb/ (last access: 12 November 2024), 2015.
Sui, L., Wang, J., Yang, X., and Wang, Z.: Spatial-temporal characteristics of coastline changes in Indonesia from 1990 to 2018, Sustainability, 12, 3242, https://doi.org/10.3390/su12083242, 2020.
Tang, S., Song, L., Wan, S., Wang, Y., Jiang, Y., and Liao, J.: Long-Time-Series Evolution and Ecological Effects of Coastline Length in Coastal Zone: A Case Study of the Circum-Bohai Coastal Zone, China, Land, 11, 1291, https://doi.org/10.3390/land11081291, 2022.
Thieler, E. R., Himmelstoss, E. A., Zichichi, J. L., and Ergul, A.: The Digital Shoreline Analysis System (DSAS) version 4.0-an ArcGIS extension for calculating shoreline change (No. 2008-1278), US Geological Survey, https://doi.org/10.3133/ofr20081278, 2009.
Tian, B., Wu, W., Yang, Z., and Zhou, Y.: Drivers, trends, and potential impacts of long-term coastal reclamation in China from 1985 to 2010, Estuar. Coast. Shelf S., 170, 83–90, 2016.
Tiner, R. W.: Tidal wetlands primer: an introduction to their ecology, natural history, status, and conservation, University of Massachusetts Press, ISBN: 9781613762745, 2013.
Toure, S., Diop, O., Kpalma, K., and Maiga, A. S.: Shoreline detection using optical remote sensing: A review, ISPRS Int. J. Geo-Inf., 8, 75, https://doi.org/10.3390/ijgi8020075, 2019.
Vos, K., Harley, M. D., Splinter, K. D., Simmons, J. A., and Turner, I. L.: Sub-annual to multi-decadal shoreline variability from publicly available satellite imagery, Coast. Eng., 150, 160–174, 2019a.
Vos, K., Splinter, K. D., Harley, M. D., Simmons, J. A., and Turner, I. L.: CoastSat: A Google Earth Engine-enabled Python toolkit to extract shorelines from publicly available satellite imagery, Environ. Modell. Softw., 122, 104528, https://doi.org/10.1016/j.envsoft.2019.104528, 2019b.
Wang, M., Mao, D., Xiao, X., Song, K., Jia, M., Ren, C., and Wang, Z.: Interannual changes of coastal aquaculture ponds in China at 10-m spatial resolution during 2016–2021, Remote Sens. Environ., 284, 113347, https://doi.org/10.1016/j.rse.2022.113347, 2023.
Wang, W., Liu, H., Li, Y., and Su, J.: Development and management of land reclamation in China, Ocean Coast. Manage., 102, 415–425, 2014.
Wang, X., Liu, Y., Ling, F., Liu, Y., and Fang, F.: Spatio-temporal change detection of Ningbo coastline using Landsat time-series images during 1976–2015, ISPRS Int. J. Geo-Inf., 6, 68, https://doi.org/10.3390/ijgi6030068, 2017.
Wang, X., Xiao, X., Zou, Z., Hou, L., Qin, Y., Dong, J., Doughty, R. B., Chen, B., Zhang, X., and Chen, Y.: Mapping coastal wetlands of China using time series Landsat images in 2018 and Google Earth Engine, ISPRS J. Photogramm., 163, 312–326, 2020.
Wang, X., Yan, F., and Su, F.: Changes in coastline and coastal reclamation in the three most developed areas of China, 1980–2018, Ocean Coast. Manage., 204, 105542, https://doi.org/10.1016/j.ocecoaman.2021.105542, 2021.
Wei, X., Zheng, W., Xi, C., and Shang, S.: Shoreline extraction in SAR image based on advanced geometric active contour model, Remote Sensing, 13, 642, https://doi.org/10.3390/rs13040642, 2021.
Wu, T., Hou, X., and Xu, X.: Spatio-temporal characteristics of the mainland coastline utilization degree over the last 70 years in China, Ocean Coast. Manage., 98, 150–157, 2014.
Wulder, M. A., Coops, N. C., Roy, D. P., White, J. C., and Hermosilla, T.: Land cover 2.0, Int. J. Remote Sens., 39, 4254–4284, 2018.
Xu, H.: Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery, Int. J. Remote Sens., 27, 3025–3033, 2006.
Yancho, J. M. M., Jones, T. G., Gandhi, S. R., Ferster, C., Lin, A., and Glass, L.: The google earth engine mangrove mapping methodology (Geemmm), Remote Sensing, 12, 3758, https://doi.org/10.3390/rs12223758, 2020.
Yang, G., Huang, K., Sun, W., Meng, X., Mao, D., and Ge, Y.: Enhanced mangrove vegetation index based on hyperspectral images for mapping mangrove, ISPRS J. Photogramm., 189, 236–254, 2022.
Yang, G., Sun, W., Huang, K., Zhu, L., and Chen, C.: China’s Mainland Shorelines Over 30 Years Using Landsat Time Series Data (1990–2019), Science Data Bank [data set], https://doi.org/10.57760/sciencedb.16228, 2024.
Yang, S., Xu, K., Milliman, J., Yang, H., and Wu, C.: Decline of Yangtze River water and sediment discharge: Impact from natural and anthropogenic changes, Scientific Reports, 5, 12581, https://doi.org/10.1038/srep12581, 2015.
Yao, F., Wang, J., Wang, C., and Crétaux, J.-F.: Constructing long-term high-frequency time series of global lake and reservoir areas using Landsat imagery, Remote Sens. Environ., 232, 111210, https://doi.org/10.1016/j.rse.2019.111210, 2019.
Yin, J., Yin, Z., Wang, J., and Xu, S.: National assessment of coastal vulnerability to sea-level rise for the Chinese coast, J. Coast. Conserv., 16, 123–133, 2012.
Zhang, H., Zhang, B., Guo, H., Lu, J., and He, H.: An automatic coastline extraction method based on active contour model, in: 2013 21st International Conference on Geoinformatics, Kaifeng, China, 20–22 June 2013, IEEE, 1–5, https://doi.org/10.1109/Geoinformatics.2013.6626130, 2013.
Zhang, Y., Li, D., Fan, C., Xu, H., and Hou, X.: Southeast Asia island coastline changes and driving forces from 1990 to 2015, Ocean Coast. Manage., 215, 105967, https://doi.org/10.1016/j.ocecoaman.2021.105967, 2021.
Zhou, J., Jia, L., and Menenti, M.: Reconstruction of global MODIS NDVI time series: Performance of Harmonic ANalysis of Time Series (HANTS), Remote Sens. Environ., 163, 217–228, 2015.
Zhu, Q., Li, P., Li, Z., Pu, S., Wu, X., Bi, N., and Wang, H.: Spatiotemporal changes of coastline over the Yellow River Delta in the previous 40 years with Optical and SAR Remote Sensing, Remote Sensing, 13, 1940, https://doi.org/10.3390/rs13101940, 2021.
Zhu, Z. and Woodcock, C. E.: Continuous change detection and classification of land cover using all available Landsat data, Remote Sens. Environ., 144, 152–171, 2014.
Short summary
Continuous monitoring of shoreline dynamics is critical to understanding the drivers of shoreline change and evolution. This study uses long-term sequences of Landsat Landsat Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), and Operational Land Imager (OLI) images to analyze the spatio-temporal evolution characteristics of the coastlines of Hainan, mainland China, Taiwan, and other countries from 1990 to 2019.
Continuous monitoring of shoreline dynamics is critical to understanding the drivers of...
Altmetrics
Final-revised paper
Preprint