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Remote Sensing and Geographic Information System (GIS) for Coastal Environment

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A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Marine Environmental Science".

Deadline for manuscript submissions: closed (10 January 2023) | Viewed by 17360

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Prof. Dr. Yuanzhi Zhang

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School of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing, China
Interests: coastal environment; carbon neutrality; subsidence; erosion; coastline change
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Prof. Dr. Lin Li

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Guest Editor

Department of Earth Sciences, Indiana University-Purdue University Indianapolis, Indianapolis, IN 46202, USA
Interests: remote sensing; lunar and planetary geology; environmental sciences; data processing; radiative transfer models
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Prof. Dr. Dongmei Chen

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Department of Geography and Planning, Queen’s University, Kingston, ON K7L 3N6, Canada
Interests: spatial model; land use change; coastal environments; wetland and mangrove
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Xiaojuan Li

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Guest Editor

College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China
Interests: GIS application; land subsidence; seawater invasion; coastline change

Special Issue Information

Dear Colleagues,

Remote sensing and geographic information systems (GIS) play an important role in monitoring coastal environments. In recent years, coastal environments have drawn increasing awareness globally, regionally, or locally as many coastal regions experience dramatic changes in land use and land cover (LULC) and various water pollution resulting from the rapid industrial, urban, and agricultural development. Such environmental consequences caused by human activities exacerbate the effects of climate change and natural disasters on the coastal environment, which have led to the frequent destruction of coastal ecosystems around the world.

This Special Issue on “Remote Sensing and Geographic Information System (GIS) for Coastal Environments” invites original research articles as well as review articles that focus ongoing efforts on monitoring and understanding the land-ocean interaction, coastal response to global climate change, and conservation effects on the coastal landscape through Earth observation and in situ measurement. The suggested topics are relevant but not limited to the study of coastal environment monitoring, coastal land use change, land subsidence, sea-level rise, wetland and mangrove, coastal carbon neutrality, estuarine/coastal water quality, offshore aquaculture, coastline change and coastal erosion, green and red tides, oil spill, and typhoon impacts.

Prof. Dr. Yuanzhi Zhang
Prof. Dr. Lin Li
Prof. Dr. Dongmei Chen
Prof. Dr. Xiaojuan Li
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Marine Science and Engineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

coastal environments
coastal carbon neutrality
coastal land use change
coastal wetland and mangrove
coastal sediments, erosion and coastline change
estuarine and coastal infrastructures
harmful algal blooms
sea level rise and land subsidence
typhoon impacts

Published Papers (10 papers)

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Research

26 pages, 32816 KiB

Open AccessArticle

Multiscale Analysis and Prediction of Sea Level in the Northern South China Sea Based on Tide Gauge and Satellite Data

by Yilin Yang, Qiuming Cheng, Jin-Yeu Tsou, Ka-Po Wong, Yanzhuo Men and Yuanzhi Zhang

J. Mar. Sci. Eng. 2023, 11(6), 1203; https://doi.org/10.3390/jmse11061203 - 09 Jun 2023

Cited by 2 | Viewed by 1342

Abstract

Under the influence of global warming, the problem of sea-level rise is becoming increasingly prominent. The northern part of the South China Sea (SCS) is low lying, with intense economic development, and densely populated. These characteristics make the region extremely sensitive to the consequences of rising sea levels. This study aims to reveal the trends of sea-level changes in the northern SCS and provide scientific insights into the potential flooding risks in low-lying areas. To achieve this, the Ensemble Empirical Mode Decomposition (EEMD) method is used to analyze the water level time series data from three tide gauges along the coast of Hong Kong. This analysis reveals the multidimensional change characteristics and response mechanisms of the sea level in the SCS. The findings reveal distinct seasonal, interannual, decadal, and interdecadal variations in sea-level changes. Furthermore, we explore the impact of the El Niño-Southern Oscillation (ENSO) on sea-level changes in the study area, finding a 6-month lagged correlation between the sea level and ENSO. Spatially, the rate of sea-level change is faster in nearshore areas than in the open ocean and higher in the northern regions than in the southern regions. The Multifractal Detrended Fluctuation Analysis (MF-DFA) method is employed to analyze the sea-level change time series, revealing long-range correlations and multifractal characteristics. In addition, we propose a sea-level prediction method that combines EEMD with Long Short-Term Memory (LSTM) neural networks and conducts empirical research on sea-level changes in the northern South China Sea. The results indicate that the EEMD-LSTM model outperforms the standalone LSTM model in terms of predictive accuracy, effectively eliminating noise from signals and providing a valuable reference. In summary, this research delves into the multiscale characteristics and influencing factors of sea-level changes in the northern SCS, proposing an improved sea-level prediction method that integrates EEMD and LSTM. The findings lay the groundwork for evaluating the risks of sea-level rise in low-lying regions of the northern SCS and inform future response strategies. Full article

(This article belongs to the Special Issue Remote Sensing and Geographic Information System (GIS) for Coastal Environment)

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20 pages, 20842 KiB

Open AccessArticle

Preliminary Investigation on Marine Radar Oil Spill Monitoring Method Using YOLO Model

by Bo Li, Jin Xu, Xinxiang Pan, Rong Chen, Long Ma, Jianchuan Yin, Zhiqiang Liao, Lilin Chu, Zhiqiang Zhao, Jingjing Lian and Haixia Wang

J. Mar. Sci. Eng. 2023, 11(3), 670; https://doi.org/10.3390/jmse11030670 - 22 Mar 2023

Cited by 3 | Viewed by 1468

Abstract

Due to the recent rapid growth of ocean oil development and transportation, the offshore oil spill risk accident probability has increased unevenly. The marine oil spill poses a great threat to the development of coastal cities. Therefore, effective and reliable technologies must be used to monitor oil spills to minimize disaster losses. Based on YOLO deep learning network, an automatic oil spill detection method was proposed. The experimental data preprocessing operations include noise reduction, gray adjustment, and local contrast enhancement. Then, real and synthetically generated marine radar oil spill images were used to make slice samples for training the model in the YOLOv5 network. The detection model can identify the effective oil spill monitoring region. Finally, an adaptive threshold was applied to extract the oil slicks in the effective oil spill monitoring regions. The YOLOv5 detection model generated had the advantage of high efficiency compared with existing methods. The offshore oil spill detection method proposed can support real-time and effective data for routine patrol inspection and accident emergency response. Full article

(This article belongs to the Special Issue Remote Sensing and Geographic Information System (GIS) for Coastal Environment)

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18 pages, 5196 KiB

Open AccessArticle

Monitoring the Kotychi Lagoon in Western Peloponnese, Greece, Using Remote Sensing Techniques and Environmental Assessment

by Dionysios N. Apostolopoulos, Dionysios Giannikopoulos, Alexis Ramfos, Sara Faulwetter, Dionisios Panagiotaras, Konstantinos G. Nikolakopoulos and Pavlos Avramidis

J. Mar. Sci. Eng. 2023, 11(2), 411; https://doi.org/10.3390/jmse11020411 - 13 Feb 2023

Cited by 4 | Viewed by 1875

Abstract

The Kotychi Lagoon (western Peloponnese, Greece), together with other coastal wetlands such as Pappas, Prokopos and Lamia, is part of the wider area of the Strofylia Wetlands National Park and Protected Areas of Western Peloponnese, which has been protected by the Ramsar convention since 1971 and classified as a Natura 2000 area due to its high diversity and ecological value. This study aimed to estimate the water surface evolution of the Kotychi Lagoon using optical remote sensing techniques to record parameters and indices related to the geometrical and landscape orientation features for the 1945–2016 period and to evaluate the ecological and environmental status of the lagoon through in-situ measurement and sample analysis. High-resolution aerial photos at a scale of 1:30,000, orthomosaics, and satellite images were used and linear regression rates (LRR) were calculated to determine the changes. Seasonal sampling of water, sediment, and macrofaunal organisms in the lagoon was performed to monitor environmental and ecological parameters. The results showed that the lagoon’s water surface shrank during the 1945–2016 period, showing different rates in four segments. The shrinkage prevailed in the northeastern and southern parts of the lagoon, with rates of 17.75 and 6.46 m/year, respectively. The ecological status was determined to be poor, although nutrient input seemed to have been moderate over the study period. We conclude that applying remote sensing techniques using a combination of high-resolution images constitutes an effective and accurate method for the spatiotemporal mapping of wetlands. The ecological problems of the Kotychi Lagoon were highlighted and confirmed through complementary in-situ analyses. These problems need to be addressed by the respective managerial bodies in order to restore the lagoon to good ecological status. Full article

(This article belongs to the Special Issue Remote Sensing and Geographic Information System (GIS) for Coastal Environment)

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15 pages, 2872 KiB

Open AccessArticle

Tsunami Risk Change Analysis for Qidong County of China Based on Land Use Classification

by Jingming Hou, Yi Gao, Tingting Fan, Peitao Wang, Yuchen Wang, Juncheng Wang and Wei Lu

J. Mar. Sci. Eng. 2023, 11(2), 379; https://doi.org/10.3390/jmse11020379 - 08 Feb 2023

Viewed by 1267

Abstract

Tsunamis can cause high numbers of casualties, as well as direct and indirect economic losses to coastal regions. The huge destructiveness of tsunamis requires us to study tsunami risk and its temporal change. We adopt the tsunami scenarios of the Ryukyu Trench as an example to analyze the temporal change in tsunami risk. According to the tsunami numerical model results, the tsunami inundation in the worst tsunami scenario covered an area of 82.83 km². Satellite data including Landsat 8 images from July 2013 and Landsat 9 images from March 2022 were used with the random forest (RF) method to analyze land use and tsunami vulnerability in 2013 and 2022. The tsunami risk and its temporal change were analyzed by integrating tsunami hazard and tsunami vulnerability. The tsunami risk change analysis results show that the area of tsunami risk level 1 increased by 4.57 km², and the area of tsunami risk level 4 decreased by 7.31 km². By analyzing changes in land use and land cover (LULC) and tsunami risk, we concluded that the expansion of constructed land and the increase in coastal population were responsible for the increase in tsunami risk. The results of tsunami risk change analysis will help us understand the current tsunami risk and predict possible future risk change. In addition, it is necessary to prepare tsunami prevention measures in advance and produce tsunami emergency response plans for Qidong County and other regions under potential tsunami threat. Full article

(This article belongs to the Special Issue Remote Sensing and Geographic Information System (GIS) for Coastal Environment)

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13 pages, 11822 KiB

Open AccessArticle

Effects of Anticyclonic Eddies on the Unique Tropical Storm Deliwe (2014) in the Mozambique Channel

by Linfei Bai, Haibin Lü, Haojie Huang, Shahzad Muhammad Imran, Xiaoqi Ding and Yuanzhi Zhang

J. Mar. Sci. Eng. 2023, 11(1), 129; https://doi.org/10.3390/jmse11010129 - 06 Jan 2023

Cited by 2 | Viewed by 1603

Abstract

The unique tropical storm (TS) Deliwe (2014) occurred in the northern Mozambique Channel on 17 January 2014 and turned right during its whole life cycle, moving south along the west coast of Madagascar Island. During the development of the TS, the anticyclonic eddies in the Mozambique Channel had an important influence on the intensity and track of Deliwe, which existed for months. In this study, multisource reanalysis, conductivity temperature depth (CTD) and Argo buoy data were used to investigate the mechanism of dynamics. The results showed that the anticyclonic eddies in the Mozambique Channel were a major cause of Deliwe strengthening, weakening and then deflection to the right. On 17 January, the maximum latent heat flux of anticyclonic eddy W1 reached 103.1 w/m². After Deliwe passed, the tropical cyclone heat potential (TCHP) of anticyclonic eddy W1 was significantly reduced by 3 kJ/cm². The mixed layer of anticyclonic eddy W1 was deeper than the surrounding waters, supporting the development of Deliwe. As the TS intensity decreased, the low-pressure center of 500 hPa moved above anticyclonic eddy W2, and the westerly wind belt moved northward to form a westerly trough of low pressure, which caused the TS to keep turning right and formed a unique TS track. This study provides a new understanding of the influence of marine anticyclonic eddies on the development of tropical cyclones (TCs) in the Mozambique channel. Full article

(This article belongs to the Special Issue Remote Sensing and Geographic Information System (GIS) for Coastal Environment)

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26 pages, 4559 KiB

Open AccessArticle

Decreasing Vulnerability of Storm Surge Disasters in Coastal Cities of China over the Past 30 Years

by Dan Meng, Yueming Liu, Zhihua Wang, Xiaomei Yang, Xiaoliang Liu, Junyao Zhang and Ku Gao

J. Mar. Sci. Eng. 2023, 11(1), 128; https://doi.org/10.3390/jmse11010128 - 06 Jan 2023

Cited by 2 | Viewed by 1286

Abstract

From 2000 to 2020, storm surges occurred 397 times in China, resulting in direct economic losses of up to CNY 220.64 billion. Storm surges not only threaten safety but also cause property damage; hence, it is necessary to assess the changes in vulnerability to storm surges in order to understand how to reduce said vulnerability. Fifteen coastal cities of four types were chosen, with different levels of urban development, rapid expansion of impervious surface, high extent of agricultural land, and high fishery output value. Viewing vulnerability through the dimensions of exposure, sensitivity, and adaptability, a GIS and RS were used to evaluate and assess the vulnerability in 15 coastal cities in China over the past 30 years. The results indicated that the vulnerability of these 15 Chinese cities presented the characteristics of a continuous downward trend from 1990 to 2020, and the average rate of reduction in vulnerability over the 10 years from 2005 to 2015 was the highest, at 2.23%. The areas of high vulnerability shifted from the southern region to the northern region. The vulnerabilities in the southern region, with Shanghai, Shenzhen, and Dongguan, changed significantly, to 3.30%, 3.20%, and 3.45%, respectively. An important factor in determining vulnerability reductions is a city’s ability to adapt to storm surges. Coastal cities can improve their adaptability to storm surge disasters through general public budget expenditure, investment in fixed assets, GDP, and medical and health services, thereby alleviating their vulnerability. Due to China’s frequent storm surge disasters during the 2005–2015 period, government departments have strengthened the investment of relevant resources in adaptive indicators, ultimately causing the cities’ vulnerability to rapidly decrease during this period. Full article

(This article belongs to the Special Issue Remote Sensing and Geographic Information System (GIS) for Coastal Environment)

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20 pages, 4622 KiB

Open AccessArticle

Marine GIS as a Tool to Support Backscatter Data Analysis for Zooplankton Investigations

by Roberto Nardini, Paola Picco, Tiziana Ciuffardi, Roberto Bozzano, Maurizio Demarte, Giancarlo Raiteri, Andrea Bordone and Sara Pensieri

J. Mar. Sci. Eng. 2023, 11(1), 22; https://doi.org/10.3390/jmse11010022 - 24 Dec 2022

Viewed by 1771

Abstract

Echo-sounders and Vessel-Mounted Acoustic Doppler Current Profilers (VM-ADCP) are widely operating onboard research vessels with the aim of providing real-time backscatter and ocean current profiles along the route, while the vessel is moving. Backscatter data are exploited to infer important information about zooplankton presence and distribution. Nevertheless, as these organisms daily vertically migrate even below the depth of the instrument range, the combination of space and time variability make their mapping from a moving vessel quite complex. The objective of this work is to describe a GIS application developed for the management and analysis of these data. The GIS capability as a tool to facilitate zooplankton investigations is assessed by means of a test-case in the area of the Ligurian Sea (Western Mediterranean) by using VM-ADCP backscatter data made available during oceanographic campaigns. The system, which includes a high-resolution bathymetry, environmental parameters, ephemeris, allows to select and visualize data sorted according to all the possible layer combinations. Moreover, different backscatter profiles, characterizing the identified migration phases can be enlightened by means of false color scale representation. Full article

(This article belongs to the Special Issue Remote Sensing and Geographic Information System (GIS) for Coastal Environment)

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18 pages, 9489 KiB

Open AccessArticle

Land Subsidence Evolution and Simulation in the Western Coastal Area of Bohai Bay, China

by Can Lu, Lin Zhu, Xiaojuan Li, Huili Gong, Dong Du, Haigang Wang and Pietro Teatini

J. Mar. Sci. Eng. 2022, 10(10), 1549; https://doi.org/10.3390/jmse10101549 - 20 Oct 2022

Cited by 3 | Viewed by 1616

Abstract

Groundwater overexploitation and loading of buildings have been the main factors triggering land subsidence along the west coast of Bohai Bay, China, since the 2000s. Uneven subsidence has been causing damage to buildings and civil facilities, loss of elevation, increasing the risk of flood and seawater intrusion, and threatening the safety of people’s lives and property. This paper analyzed the spatial and temporal features of land subsidence along the coastal area from 2003 to 2010 and from 2015 to 2020, respectively. The relations between the initiating factors and land subsidence were explored. Then, the simulation model of land subsidence was constructed through a deep learning method. During the process, multiple data were collected, including land satellite (Landsat), environmental satellite advanced synthetic aperture radar (ENVISAT ASAR) and Sentinel-1 images, leveling data, lithological data, and groundwater level data. The area occupied by buildings and vertical displacement were extracted by using supervised classification, small baseline subset (SBAS), and persistent scatterer interferometry (PSI) technologies. The gated recurrent unit (GRU) neural network was adopted to simulate the evolution of land subsidence. Results showed that the maximum annual vertical displacement rate decreased from −94 mm/yr during 2003–2010 to −87 mm/yr during 2015–2020. The correlation efficiency between the groundwater level of the third confined aquifer group and land subsidence was larger than the area occupied by buildings and the compressible layer thickness with subsidence. The constructed GRU neural network model can simulate subsidence from September 2019 to December 2019, with the overall RMSE and MAE being 3.16 mm and 2.19 mm, respectively. This work can facilitate an understanding of the evolution and prevention of land subsidence along the west coast of Bohai Bay, which will provide information for policy decisions and flood-fighting plans of the worldwide coastal cities. Full article

(This article belongs to the Special Issue Remote Sensing and Geographic Information System (GIS) for Coastal Environment)

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24 pages, 9167 KiB

Open AccessArticle

Vertical Structure and Seasonal Variability of Shear on the Southwestern Continental Slope of the East China Sea

by Zhiling Ouyang, Ze Liu and Yijun Hou

J. Mar. Sci. Eng. 2022, 10(7), 902; https://doi.org/10.3390/jmse10070902 - 30 Jun 2022

Viewed by 1220

Abstract

The vertical structure and seasonal variability of shear were examined using nearly three years of mooring ADCP (acoustic Doppler current profiler) data on the southwestern continental slope of the East China Sea (ECS). Shear spectra suggest that the sub-inertial currents (SICs); near-inertial waves (NIWs); and diurnal (D1), semidiurnal (D2), and tridiurnal (D3) internal tides (ITs) dominate the local shear field. The shear exhibits a remarkable surface-intensified pattern with high values occurring mostly in the upper 200 m. Significant seasonal variations can be found in the shear, but with differences between the upper (50–200 m averaged) and lower layers (210–570 m averaged). Satellite altimeter data indicate that the meander of the Kuroshio mainstream and the Kuroshio intrusion affect the seasonal variation of total shear by mainly influencing the shear caused by SICs. In addition, the shear efficiency (SE) of D2 ITs is obviously less than that of NIWs and that of D1 and D3 ITs via analyzing the kinetic energy (KE) densities and shear caused by these motions, since the predominant mode of the former is the first baroclinic mode, while the latter is dominated by higher baroclinic modes with large vertical wavenumbers. Moreover, the SE of incoherent ITs is relatively stronger than that of coherent ITs as a result of a larger proportion of high baroclinic modes in the incoherent component compared to the coherent component, based on modal decomposition. Full article

(This article belongs to the Special Issue Remote Sensing and Geographic Information System (GIS) for Coastal Environment)

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16 pages, 2135 KiB

Open AccessArticle

Satellite-Based Monitoring of Coastal Wetlands in Yancheng, Jiangsu Province, China

by Chen Chen, Jiajun Feng, Changyou Wang, Longjiang Mao and Yuanzhi Zhang

J. Mar. Sci. Eng. 2022, 10(6), 829; https://doi.org/10.3390/jmse10060829 - 17 Jun 2022

Cited by 7 | Viewed by 2645

Abstract

The dynamic process of the wetland can reflect its impact on the environment, and finding a balance point supporting harmonious coexistence between man and nature has become an issue of increasing concern. On the basis of previous studies that have focused on local coastal wetlands, the temporal and spatial changes and driving forces of wetlands in the Yancheng coastal area from 1991 to 2021 were analyzed over a larger area. According to the study findings: (1) The results of the study of the Yancheng coastal wetland with a larger scope differed significantly from findings resulting from a study of coastal wetland only. This difference was mainly reflected in the relatively stable situation of wetland ecology as a whole, while the changes in local surface features were more significant. (2) Natural wetlands were transformed into artificial wetlands and non-wetland types, and artificial wetlands were transformed into non-wetland types; additionally, reverse transformations and internal transformations of surface features also took place. For instance, the saltpan was transformed into mudflats (86.26 km²), and some mudflats into herbaceous vegetation (193.47 km²). (3) When analyzing the impact intensity of human activities on the Yancheng wetland, it was found that this factor has experienced a process of first rising and then falling. The index was 0.650, 0.653, 0.664, 0.661, and 0.641 in 1991, 2000, 2008, 2016, and 2021, respectively. (4) Lastly, an analysis of factors driving wetland change revealed that human factors were the most critical reasons for wetland landscape change. Our work can play a reference and inspiration role in the monitoring and protection of similar coastal wetlands. Full article

(This article belongs to the Special Issue Remote Sensing and Geographic Information System (GIS) for Coastal Environment)

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