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Satellite-Based Assessment of Geomorphological Dynamics of Coastline Using Optical and Near-Infrared Instruments

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".

Deadline for manuscript submissions: closed (31 August 2022) | Viewed by 6267

Special Issue Editors

Prof. Dr. Scot Smith

E-Mail Website
Guest Editor
School of Forest Resources & Conservation, University of Florida, Gainesville, FL 32611, USA
Interests: remote sensing; GIS; photogrammetry; AI
Special Issues, Collections and Topics in MDPI journals
Dr. Kamal Darwish

E-Mail Website
Guest Editor
Geography Department, Minia University, Al Minia 61519, Egypt
Interests: GIS; AI; geospatial technologies; coastal remote sensing
Special Issues, Collections and Topics in MDPI journals
Dr. Yiming Xu

E-Mail Website
Guest Editor
School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
Interests: soil nutrients; soil; agriculture; remote sensing; satellites; statistical analysis

Special Issue Information

Dear Colleagues,

The Earth’s coastlines have always been dynamic, but are especially so these days due to sea level rise and increased storm strength. Entire beaches and islands are being wiped out, disrupting entire communities. Since most of the world’s population lives close to the sea, it is vital to constantly monitor the dynamics of coastlines. There are many ways of monitoring coasts using remote sensing techniques ranging from drones equipped with cameras to high attitude LiDAR aircraft to earth-looking remote sensing satellites. This Special Issue will focus on the latest satellite imagery and compare the imageries available from them for the application of coastal monitoring. There are new earth-looking remote sensing satellites such as Landsat 9, the latest Sentinel and PlanetScope, which are very promising potentially for coastal monitoring.

The Aim of this SI is to evaluate the newest series of earth looking optical and near-IR sensors onboard the latest satellites (Landsat 9, Sentinel 2A and Planet Scope, among other) for coastal geomorphological dynamics assessment.

Dr. Scot Smith
Dr. Kamal Darwish
Dr. Yiming Xu
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. Remote Sensing is an international peer-reviewed open access semimonthly 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 2700 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

  • coastline
  • optical remote sensing
  • shoreline extraction
  • Sentinel
  • PlanetScope
  • Landsat

Published Papers (3 papers)

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Research

18 pages, 34372 KiB  
Article
Landsat-Based Assessment of Morphological Changes along the Sinai Mediterranean Coast between 1990 and 2020
by Kamal Darwish and Scot Smith
Remote Sens. 2023, 15(5), 1392; https://doi.org/10.3390/rs15051392 - 1 Mar 2023
Cited by 4 | Viewed by 2106
Abstract
The objective of this study was to assess coastal dynamics of the Sinai Mediterranean coastline (SMC) between 1990 and 2020. In this study, remote sensing imagery and geographic information systems-based spatial computing methods were used for coastline change analysis. The study found that [...] Read more.
The objective of this study was to assess coastal dynamics of the Sinai Mediterranean coastline (SMC) between 1990 and 2020. In this study, remote sensing imagery and geographic information systems-based spatial computing methods were used for coastline change analysis. The study found that the SMC experienced major morphological changes during the period of study. The results show a spatial heterogeneity of coastline change rate over the study period with some periods of rapid change and other periods of stability. The overall analysis during the period of study indicated that the coastline has retreated landward approximately 555 m; the average annual erosion rate was 2.5 m/year. The percentage of the eroded section in the coastline is 60% with the remaining 40% either advancing or remaining stable. Sections of the coastline accreted as much as 542 m. The GIS-based DSAS model application used in this study is unique because it measured spatial variations of coastline dynamics over time using a multiple statistical approach. Full article
(This article belongs to the Special Issue Satellite-Based Assessment of Geomorphological Dynamics of Coastline Using Optical and Near-Infrared Instruments)
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18 pages, 9650 KiB  
Article
Mapping Morphodynamic Variabilities of a Meso-Tidal Flat in Shanghai Based on Satellite-Derived Data
by Rui Yuan, Hezhenjia Zhang, Cheng Qiu, Yuefeng Wang, Xingjie Guo, Yaping Wang and Shenliang Chen
Remote Sens. 2022, 14(16), 4123; https://doi.org/10.3390/rs14164123 - 22 Aug 2022
Cited by 5 | Viewed by 1887
Abstract
Morphodynamic variabilities of tidal flats (e.g., the variations of pattern, area, and topography) are a key issue in the management of coastal intertidal zones. In this study, the morphodynamic variabilities of the Lin-gang (Shanghai) tidal flat were investigated using waterlines extracted from multi-source [...] Read more.
Morphodynamic variabilities of tidal flats (e.g., the variations of pattern, area, and topography) are a key issue in the management of coastal intertidal zones. In this study, the morphodynamic variabilities of the Lin-gang (Shanghai) tidal flat were investigated using waterlines extracted from multi-source satellite images acquired from 2013 to 2020. The waterlines were evaluated against in situ measurements. The results of our investigation indicated that the tidal flat was in a state of rapid accretion from 2015 to 2018, and in a state of erosion from 2018 to 2020. We found that the accretion of the tidal flat was most likely due to the protection of local vegetation, which prevents the sea bottom from eroding. However, storms have primarily been causing erosion since 2018. The potential mechanisms of the geomorphological variations were further analyzed using the empirical orthogonal function (EOF) method. The analysis revealed that the variation in the tidal flat was dominated by two modes. The first mode accounted for 55% of the variation, while the second mode accounted for 18%. The spatial distribution of the first mode was highly related to the artificial vegetation, indicating that the local variations in the vegetation prevented the sea bottom from eroding, which was dominant in the accretional phase from 2015 to 2018. The second model reflected the extreme meteorological events that resulted in potential changes in the tidal flat’s pattern (i.e., transitioning to an erosion phase from 2018 to 2020). The satellite-derived topographies were demonstrated to be an effective means of mapping the evolution of a meso-tidal flat. Full article
(This article belongs to the Special Issue Satellite-Based Assessment of Geomorphological Dynamics of Coastline Using Optical and Near-Infrared Instruments)
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19 pages, 5881 KiB  
Article
Shoreline Dynamics of Chongming Island and Driving Factor Analysis Based on Landsat Images
by Haobin Wang, Dandan Xu, Dong Zhang, Yihan Pu and Zhaoqing Luan
Remote Sens. 2022, 14(14), 3305; https://doi.org/10.3390/rs14143305 - 8 Jul 2022
Cited by 9 | Viewed by 1718
Abstract
Chongming Island, the third largest island in China, has experienced dramatic shoreline changes due to erosion, river deposits, and human activities. While previous studies have shown the capacity of Landsat series images to extract shoreline dynamics, the spatial variation of shoreline dynamics and [...] Read more.
Chongming Island, the third largest island in China, has experienced dramatic shoreline changes due to erosion, river deposits, and human activities. While previous studies have shown the capacity of Landsat series images to extract shoreline dynamics, the spatial variation of shoreline dynamics and their corresponding driving factors remain unclear. Therefore, we established a method to monitor the shoreline dynamics of Chongming Island from 1984 to 2020 and to evaluate the driving factors of shoreline changes using a novel approach to Landsat image analysis. The method, based on the LISA (local indicator of spatial autocorrelation) concept, automatically extracted the shoreline from Landsat imagery. The results show that the LISA method, based on the SWIR1 band, has a high capacity for shoreline extraction in Chongming Island. By distinguishing the responses of the eastern and northern shorelines to upstream sediment loads and comprehensively analyzing the driving factors of eastern and northern dynamics, we found that: (i) although upstream sediment loads decreased dramatically, the shoreline of Chongming Island is still expanding due to human activities (i.e., reclamation and an estuary project) and sediment re-suspension from near-shore or cross-shore currents; (ii) the expansion of Chongming Island was initially due to the dynamics at the eastern shoreline, but the expansion of the eastern shoreline slowed after 2008 as upstream sedimentation slowed, less construction of cofferdams took place, and the Qingcaosha Reservoir was constructed; (iii) the northern shoreline of Chongming Island expanded rapidly after 1999, due to the merger of Xinlongsha, Xincunsha, and Chongming Island, and the transport of coastal and offshore sediments by hydrodynamic processes; and (iv) the main driving factors of eastern shoreline movement on Chongming Island are cofferdam reclamation and coastal engineering, and the changes at the northern shoreline are mainly affected by reclamation projects, offshore sediment supplies, and upstream sediment inflow. The results of this study provide theoretical fundamentals for land reclamation and future urban planning for Chongming Island. Full article
(This article belongs to the Special Issue Satellite-Based Assessment of Geomorphological Dynamics of Coastline Using Optical and Near-Infrared Instruments)
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