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Earth Observations for Coastal Resilience

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

Deadline for manuscript submissions: closed (31 May 2020) | Viewed by 21607

Special Issue Editors


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Guest Editor
Department of Political Science & Geography, Institute for Coastal Adaptation and Resilience (ICAR), Old Dominion University, Norfolk, VA 23529, USA
Interests: coastal and estuarine mapping; marine and coastal GIS; natural hazards
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Earth and Ocean Sciences, University of North Carolina Wilmington, 601 S College Rd., Wilmington, NC 28403, USA
Interests: geographic information science; spatial statistics; coastal ecosystems; applications of remote sensing and UAS; population dynamics; ecosystem health
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Geology and Geography, Georgia Southern University, Statesboro, GA 30460, USA
Interests: habitat mapping, multi-sensor data integration; LiDAR DEM accuracy; tidal marsh restoration

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Guest Editor
Department of Geography, Virginia Tech, Blacksburg, VA 24061, USA
Interests: coastal geography; hazards; spatial analysis; vulnerability and resilience

Special Issue Information

Dear Colleagues,

Coastal landscapes, communities and places, and component ecosystems are under increasing threat from a variety of chronic stressors and acute disasters. Recent issues of Remote Sensing and other journals have highlighted the strong capabilities for remote sensing to inventory, monitor and retrieve critical parameters pertaining to coastal resources and habitats, yet there remains a niche to be explored and research to be highlighted that specifically addresses “resilience” in coastal systems. Broad interpretations typical of the concept must be refined and operationalized in order to advance their application in remote sensing science and applied practice. We invite high quality and innovative research articles that explore, asses, or implement concepts of resilience in coastal systems, including natural or built coastal environments. An array of concepts directly or indirectly incorporating principles of resilience are highlighted below, and we encourage potential authors to correspond with the guest editors to refine submission foci and build toward a synthesis article to identify future remote sensing and resilience research. The following topics are particularly encouraged:

  • Exposure: Use of remote sensing to quantify the degree to which natural habitats, resources, or human populations or coastal development are potentially affected by hazards and threats (e.g., sea level rise).
  • Susceptibility: Quantitative estimation of coastal system sensitivity or adjustment to climate-sensitive changes in coastal processes which connote damage, disruption or reduce service or functional capacity (e.g., ecosystem functions under stressors such as estuarine water quality or salinization).
  • Vulnerability: Remote sensing assessments that quantify the diminished tolerance or coping capabilities to climate stressors, disasters, variability or extremes. Vulnerability assessments may include risk mapping or analytic approaches juxtaposing climate extremes and receptor systems (e.g., storm surges and transgression with sea level rise, increasing extremes in rainfall, or tidal inundation).
  • Resiliency: Systemic or multi-parameter studies that evaluate the ability of a coastal system to anticipate, prepare, respond, recover or adapt while minimizing damage to the system under threat (coastal environmental, economic, or social). Such articles may impart remote sensing data and methods within wider inter- or multi-disciplinary problems (e.g., integrated assessments, emergency management, or coastal planning.)

Dr. Thomas R. Allen
Dr. Joanne Halls
Dr. Christine Hladik
Dr. Thomas Crawford
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

  • Sea level rise
  • Storm surge
  • Shoreline change
  • Coastal geomorphology
  • Coastal land use/land cover change
  • Risk and vulnerability assessment
  • Resilience, adaptation and mitigation

Published Papers (5 papers)

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Research

24 pages, 4686 KiB  
Article
Coastal Erosion and Human Perceptions of Revetment Protection in the Lower Meghna Estuary of Bangladesh
by Thomas W. Crawford, Md Sariful Islam, Munshi Khaledur Rahman, Bimal Kanti Paul, Scott Curtis, Md. Giashuddin Miah and Md. Rafiqul Islam
Remote Sens. 2020, 12(18), 3108; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12183108 - 22 Sep 2020
Cited by 16 | Viewed by 5131
Abstract
This study investigates coastal erosion, revetment as a shoreline protection strategy, and human perceptions of revetments in the Lower Meghna estuary of the Bangladesh where new revetments were recently constructed. Questions addressed were: (1) How do rates of shoreline change vary over the [...] Read more.
This study investigates coastal erosion, revetment as a shoreline protection strategy, and human perceptions of revetments in the Lower Meghna estuary of the Bangladesh where new revetments were recently constructed. Questions addressed were: (1) How do rates of shoreline change vary over the period 2011–2019? (2) Did new revetments effectively halt erosion and what were the magnitudes of erosion change? (3) How have erosion rates changed for shorelines within 1 km of revetments, and (4) How do households perceive revetments? High-resolution Planet Lab imagery was used to quantify shoreline change rates. Analysis of household survey data assessed human perceptions of the revetment’s desirability and efficacy. Results revealed high rates of erosion for 2011–2019 with declining erosion after 2013. New revetments effectively halted erosion for protected shorelines. Significant spatial trends for erosion rates existed for shorelines adjacent to revetments. Survey respondents overwhelmingly had positive attitudes about a desire for revetment protection; however, upstream respondents expressed a strong majority perception that revetment acts to make erosion worse. Highlights of the research include integration of remote sensing with social science methods, the timing of the social survey shortly after revetment construction, and results showing significant erosion change upstream and downstream of new revetments. Full article
(This article belongs to the Special Issue Earth Observations for Coastal Resilience)
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20 pages, 4926 KiB  
Article
Inundation Exposure Assessment for Majuro Atoll, Republic of the Marshall Islands Using A High-Accuracy Digital Elevation Model
by Dean Gesch, Monica Palaseanu-Lovejoy, Jeffrey Danielson, Charles Fletcher, Maria Kottermair, Matthew Barbee and Andrea Jalandoni
Remote Sens. 2020, 12(1), 154; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12010154 - 02 Jan 2020
Cited by 9 | Viewed by 5127
Abstract
Majuro Atoll in the central Pacific has high coastal vulnerability due to low-lying islands, rising sea level, high wave events, eroding shorelines, a dense population center, and limited freshwater resources. Land elevation is the primary geophysical variable that determines exposure to inundation in [...] Read more.
Majuro Atoll in the central Pacific has high coastal vulnerability due to low-lying islands, rising sea level, high wave events, eroding shorelines, a dense population center, and limited freshwater resources. Land elevation is the primary geophysical variable that determines exposure to inundation in coastal settings. Accordingly, coastal elevation data (with accuracy information) are critical for assessments of inundation exposure. Previous research has demonstrated the importance of using high-accuracy elevation data and rigorously accounting for uncertainty in inundation assessments. A quantitative analysis of inundation exposure was conducted for Majuro Atoll, including accounting for the cumulative vertical uncertainty from the input digital elevation model (DEM) and datum transformation. The project employed a recently produced and validated DEM derived from structure-from-motion processing of very-high-resolution aerial imagery. Areas subject to marine inundation (direct hydrologic connection to the ocean) and low-lying lands (disconnected hydrologically from the ocean) were mapped and characterized for three inundation levels using deterministic and probabilistic methods. At the highest water level modeled (3.75 ft, or 1.143 m), more than 34% of the atoll study area is likely to be exposed to inundation (68% chance or greater), while more than 20% of the atoll is extremely likely to be exposed (95% chance or greater). The study demonstrates the substantial value of a high-accuracy DEM for assessing inundation exposure of low-relief islands and the enhanced information from accounting for vertical uncertainty. Full article
(This article belongs to the Special Issue Earth Observations for Coastal Resilience)
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14 pages, 2960 KiB  
Article
Wetland Dynamics Inferred from Spectral Analyses of Hydro-Meteorological Signals and Landsat Derived Vegetation Indices
by Subrina Tahsin, Stephen C. Medeiros and Arvind Singh
Remote Sens. 2020, 12(1), 12; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12010012 - 18 Dec 2019
Cited by 7 | Viewed by 2941
Abstract
The dynamic response of coastal wetlands (CWs) to hydro-meteorological signals is a key indicator for understanding climate driven variations in wetland ecosystems. This study explored the response of CW dynamics to hydro-meteorological signals using time series of Landsat-derived normalized difference vegetation index (NDVI) [...] Read more.
The dynamic response of coastal wetlands (CWs) to hydro-meteorological signals is a key indicator for understanding climate driven variations in wetland ecosystems. This study explored the response of CW dynamics to hydro-meteorological signals using time series of Landsat-derived normalized difference vegetation index (NDVI) values at six locations and hydro-meteorological time-series from 1984 to 2015 in Apalachicola Bay, Florida. Spectral analysis revealed more persistence in NDVI values for forested wetlands in the annual frequency domain, compared to scrub and emergent wetlands. This behavior reversed in the decadal frequency domain, where scrub and emergent wetlands had a more persistent NDVI than forested wetlands. The wetland dynamics were found to be driven mostly by the Apalachicola Bay water level and precipitation. Cross-spectral analysis indicated a maximum time-lag of 2.7 months between temperature and NDVI, whereas NDVI lagged water level by a maximum of 2.2 months. The quantification of persistent behavior and subsequent understanding that CW dynamics are mostly driven by water level and precipitation suggests that the severity of droughts, floods, and storm surges will be a driving factor in the future sustainability of CW ecosystems. Full article
(This article belongs to the Special Issue Earth Observations for Coastal Resilience)
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20 pages, 5889 KiB  
Article
Adjusting Emergent Herbaceous Wetland Elevation with Object-Based Image Analysis, Random Forest and the 2016 NLCD
by David F. Muñoz, Jordan R. Cissell and Hamed Moftakhari
Remote Sens. 2019, 11(20), 2346; https://0-doi-org.brum.beds.ac.uk/10.3390/rs11202346 - 10 Oct 2019
Cited by 15 | Viewed by 3485
Abstract
Emergent herbaceous wetlands are characterized by complex salt marsh ecosystems that play a key role in diverse coastal processes including carbon storage, nutrient cycling, flood attenuation and shoreline protection. Surface elevation characterization and spatiotemporal distribution of these ecosystems are commonly obtained from LiDAR [...] Read more.
Emergent herbaceous wetlands are characterized by complex salt marsh ecosystems that play a key role in diverse coastal processes including carbon storage, nutrient cycling, flood attenuation and shoreline protection. Surface elevation characterization and spatiotemporal distribution of these ecosystems are commonly obtained from LiDAR measurements as this low-cost airborne technique has a wide range of applicability and usefulness in coastal environments. LiDAR techniques, despite significant advantages, show poor performance in generation of digital elevation models (DEMs) in tidal salt marshes due to large vertical errors. In this study, we present a methodology to (i) update emergent herbaceous wetlands (i.e., the ones delineated in the 2016 National Land Cover Database) to present-day conditions; and (ii) automate salt marsh elevation correction in estuarine systems. We integrate object-based image analysis and random forest technique with surface reflectance Landsat imagery to map three emergent U.S. wetlands in Weeks Bay, Alabama, Savannah Estuary, Georgia and Fire Island, New York. Conducting a hyperparameter tuning of random forest and following a hierarchical approach with three nomenclature levels for land cover classification, we are able to better map wetlands and improve overall accuracies in Weeks Bay (0.91), Savannah Estuary (0.97) and Fire Island (0.95). We then develop a tool in ArcGIS to automate salt marsh elevation correction. We use this ‘DEM-correction’ tool to modify an existing DEM (model input) with the calculated elevation correction over salt marsh regions. Our method and tool are validated with real-time kinematic elevation data and helps correct overestimated salt marsh elevation up to 0.50 m in the studied estuaries. The proposed tool can be easily adapted to different vegetation species in wetlands, and thus help provide accurate DEMs for flood inundation mapping in estuarine systems. Full article
(This article belongs to the Special Issue Earth Observations for Coastal Resilience)
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23 pages, 6996 KiB  
Article
A Methodology to Assess Land Use Development, Flooding, and Wetland Change as Indicators of Coastal Vulnerability
by Joanne Nancie Halls and Jessica Lynn Magolan
Remote Sens. 2019, 11(19), 2260; https://0-doi-org.brum.beds.ac.uk/10.3390/rs11192260 - 27 Sep 2019
Cited by 8 | Viewed by 4289
Abstract
Coastal areas around the world are becoming increasingly urban, which has increased stress to both natural and anthropogenic systems. In the United States, 52% of the population lives along the coast, and North Carolina is in the top 10 fastest growing states. Within [...] Read more.
Coastal areas around the world are becoming increasingly urban, which has increased stress to both natural and anthropogenic systems. In the United States, 52% of the population lives along the coast, and North Carolina is in the top 10 fastest growing states. Within North Carolina, the southeastern coast is the fastest growing region in the state. Therefore, this research has developed a methodology that investigates the complex relationship between urbanization, land cover change, and potential flood risk and tested the approach in a rapidly urbanizing region. A variety of data, including satellite (PlanetScope) and airborne imagery (NAIP and Lidar) and vector data (C-CAP, FEMA floodplains, and building permits), were used to assess changes through space and time. The techniques consisted of (1) matrix change analysis, (2) a new approach to analyzing shorelines by computing adjacency statistics for changes in wetland and urban development, and (3) calculating risk using a fishnet, or tessellation, where hexagons of equal size (15 ha) were ranked into high, medium, and low risk and comparing these results with the amount of urbanization. As other research has shown, there was a significant relationship between residential development and wetland loss. Where urban development has yet to occur, most of the remaining area is at risk to flooding. Importantly, the combined methods used in this study have identified at-risk areas and places where wetlands have migrated/transgressed in relationship to urban development. The combination of techniques developed here has resulted in data that local government planners are using to evaluate current development regulations and incorporating into the new long-range plan for the County that will include smart growth and identification of risk. Additionally, results from this study area are being utilized in an application to the Federal Emergency Management Agency’s Community Response System which will provide residents with lower flood insurance costs. Full article
(This article belongs to the Special Issue Earth Observations for Coastal Resilience)
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