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UAV for High-Resolution Salt Marsh Monitoring

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Agriculture and Vegetation".

Deadline for manuscript submissions: closed (31 July 2023) | Viewed by 9412

Special Issue Editors


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Guest Editor
Department of Civil and Coastal Engineering, University of Florida, Gainesville, FL 32611, USA
Interests: remote sensing; coastal & oceanographic eEngineering; nNumerical modeling; estuarine hydrodynamics and morphodynamics; water quality

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Guest Editor
School of Forest Resources and Conservation, University of Florida, Gainesville, FL 32611, USA
Interests: forest ecology; macroecology; remote sensing; machine learning; computer vision

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Guest Editor
Department of Environmental Sciences, Informatics, and Statistics, Ca' Foscari University of Venice, Mestre, 30172 Venice, Italy
Interests: estuarine and fluvial hydrodynamic and morphodynamics; salt-marsh ecomorphodynamics; sediment transport; meandering streamflows

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Guest Editor
Department of Civil, Environmental, and Architectural Engineering, University of Padova, via Marzolo 9, IT-35131, Padova, Italy
Interests: high resolution topography; salt marshes; object based image analysis

Special Issue Information

Dear Colleagues,

Salt marshes are transitional zones between ocean and land, and act as natural buffers against coastal hazards. The survival of salt marshes is governed by the rate of organic and inorganic deposition, which strongly depends on hydrodynamics, sediment supply, biological activity, and vegetation characteristics. Vegetation favors the dissipation of wind waves and storm surges. Animals disturb soil and vegetation with activities such as grazing and burrowing. For these reasons, an accurate description of these processes is critical for their management and conservation. In the past years, UAVs have started to be used to survey salt marshes at centimetric resolution. This Special Issue aims to collect original research using UAVs to characterize marshes from a morphodynamic, hydrodynamic, or ecological standpoint. We are welcoming research using any UAV-borne instrument, such as laser scanners, RGB cameras, hyperspectral cameras, thermal sensors, differential synthetic aperture radar interferometry (DInSAR), among others. We are particularly interested in the following aspects:

  • Characterization of vegetation type, height, and density
  • Monitoring animal activity (mussels, crabs, herbivores, etc.)
  • Estimation of marsh and creek ground elevation, with focus on vegetation removal techniques
  • Flow velocity estimation
  • Estimation of rates of change of marsh characteristics, such as marsh edge location, vegetation coverage, etc.
  • Sediment transport

Dr. Alberto Canestrelli
Dr. Sergio Marconi
Dr. Alvise Finotello
Dr. Guillaume Goodwin
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

  • Unmanned Aerial Vehicles (UAVs)
  • Marsh morphodynamics
  • Marsh vegetation
  • Marsh ecology
  • Hydrodynamics and sediment transport in creeks and salt marshes

Published Papers (3 papers)

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Research

14 pages, 3399 KiB  
Article
Quantifying the Importance of Ice-Rafted Debris to Salt Marsh Sedimentation Using High Resolution UAS Imagery
by Sarah Stopak, Giovanna Nordio and Sergio Fagherazzi
Remote Sens. 2022, 14(21), 5499; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14215499 - 31 Oct 2022
Cited by 2 | Viewed by 1712
Abstract
Salt marshes are vulnerable to sea-level rise, sediment deficits, and storm impacts. To remain vertically resilient, salt marshes must accrete sediment at rates greater or equal to sea-level rise. Ice-rafted debris (IRD), sediment that has been moved and deposited from ice sheets, is [...] Read more.
Salt marshes are vulnerable to sea-level rise, sediment deficits, and storm impacts. To remain vertically resilient, salt marshes must accrete sediment at rates greater or equal to sea-level rise. Ice-rafted debris (IRD), sediment that has been moved and deposited from ice sheets, is one of many processes that contribute to salt marsh sediment accretion in northern latitudes. On 4 January 2018, a winter storm caused major ice mobilization in the Plum Island Estuary (PIE), Massachusetts, USA, which led to large deposits of ice-rafted sediment. We aimed to quantify the volume and mass of deposited sediment, and evaluate the significance of IRD to sediment supply in Plum Island using pixel-based land-cover classification of aerial imagery collected by an Unmanned Aircraft System (UAS) and a Digital Elevation Model. Field measurements of patch thickness, and the area of IRD determined from the classification were used to estimate annual sediment accretion from IRD. Results show that IRD deposits are localized in three areas, and estimates show that IRD contributes an annual sediment accretion rate of 0.57 ± 0.14 mm/y to the study site. New England salt marsh accretion rates typically vary between 2–10 mm/y, and the average PIE sediment accretion rate is 2.5–2.7 mm/y. Therefore, this event contributed on average 20% of the annual volume of material accreted by salt marshes, although locally the deposit thickness was 8–14 times the annual accretion rate. We show that pixel-based classification can be a useful tool for identifying sediment deposits from remote sensing. Additionally, we suggest that IRD has the potential to bring a significant supply of sediment to salt marshes in northern latitudes and contribute to sediment accretion. As remotely sensed aerial imagery from UASs becomes more readily available, this method can be used to efficiently identify and quantify deposited sediment. Full article
(This article belongs to the Special Issue UAV for High-Resolution Salt Marsh Monitoring)
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30 pages, 4071 KiB  
Article
Estimating Ground Elevation and Vegetation Characteristics in Coastal Salt Marshes Using UAV-Based LiDAR and Digital Aerial Photogrammetry
by Daniele Pinton, Alberto Canestrelli, Benjamin Wilkinson, Peter Ifju and Andrew Ortega
Remote Sens. 2021, 13(22), 4506; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13224506 - 09 Nov 2021
Cited by 18 | Viewed by 3597
Abstract
This study evaluates the skills of two types of drone-based point clouds, derived from LiDAR and photogrammetric techniques, in estimating ground elevation, vegetation height, and vegetation density on a highly vegetated salt marsh. The proposed formulation is calibrated and tested using data measured [...] Read more.
This study evaluates the skills of two types of drone-based point clouds, derived from LiDAR and photogrammetric techniques, in estimating ground elevation, vegetation height, and vegetation density on a highly vegetated salt marsh. The proposed formulation is calibrated and tested using data measured on a Spartina alterniflora-dominated salt marsh in Little Sapelo Island, USA. The method produces high-resolution (ground sampling distance = 0.40 m) maps of ground elevation and vegetation characteristics and captures the large gradients in the proximity of tidal creeks. Our results show that LiDAR-based techniques provide more accurate reconstructions of marsh vegetation (height: MAEVH = 12.6 cm and RMSEVH = 17.5 cm; density: MAEVD = 6.9 stems m−2 and RMSEVD = 9.4 stems m−2) and morphology (MAEM = 4.2 cm; RMSEM = 5.9 cm) than Digital Aerial Photogrammetry (DAP) (MAEVH = 31.1 cm; RMSEVH = 38.1 cm; MAEVD = 12.7 stems m−2; RMSEVD = 16.6 stems m−2; MAEM = 11.3 cm; RMSEM = 17.2 cm). The accuracy of the classification procedure for vegetation calculation negligibly improves when RGB images are used as input parameters together with the LiDAR-UAV point cloud (MAEVH = 6.9 cm; RMSEVH = 9.4 cm; MAEVD = 10.0 stems m−2; RMSEVD = 14.0 stems m−2). However, it improves when used together with the DAP-UAV point cloud (MAEVH = 21.7 cm; RMSEVH = 25.8 cm; MAEVD = 15.2 stems m−2; RMSEVD = 18.7 stems m−2). Thus, we discourage using DAP-UAV-derived point clouds for high-resolution vegetation mapping of coastal areas, if not coupled with other data sources. Full article
(This article belongs to the Special Issue UAV for High-Resolution Salt Marsh Monitoring)
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20 pages, 18295 KiB  
Article
High-Resolution Monitoring of Tidal Systems Using UAV: A Case Study on Poplar Island, MD (USA)
by Yuri Taddia, Alberto Pellegrinelli, Corinne Corbau, Giulia Franchi, Lorie W. Staver, John Court Stevenson and William Nardin
Remote Sens. 2021, 13(7), 1364; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13071364 - 02 Apr 2021
Cited by 20 | Viewed by 2798
Abstract
Tidal processes regulating sediment accretion rates and vegetated platform erosion in tidal systems strongly affect salt marsh evolution. A balance between erosion and deposition in a restored salt marsh is crucial for analyzing restoration strategies to be adopted within a natural context. Marsh [...] Read more.
Tidal processes regulating sediment accretion rates and vegetated platform erosion in tidal systems strongly affect salt marsh evolution. A balance between erosion and deposition in a restored salt marsh is crucial for analyzing restoration strategies to be adopted within a natural context. Marsh morphology is also coupled with tidal mudflats and channel networks and this makes micro-tidal systems crucial for a detailed assessment of restoration interventions. Here, we present a methodological approach for monitoring channel morphodynamics and vegetation variations over a time frame of six years in a low tidal energy salt marsh of the Paul S. Sarbanes Ecosystem Restoration Project at Poplar Island (Maryland, USA). The project is a restoration site where sediment dredged from the shipping channels in the upper Chesapeake Bay is used to restore a tidal marsh habitat in mid-Chesapeake Bay. Aerial surveys with an Unmanned Aerial Vehicle (UAV) have been performed for the high-resolution mapping of a small tidal system. Flight missions were planned to obtain a Ground Sample Distance (GSD) of 2 cm. Structure-from-Motion (SfM) and Multi-View-Stereo (MVS) algorithms have been used to reconstruct the 3D geometry of the site. The mapping of channel morphology and an elevation assessment on the mudflat were performed using orthomosaics, Digital Terrain Models (DTMs) and GNSS survey. The results highlight that the workflow adopted in this pilot work is suitable to assess the geomorphological evolution over time in a micro-tidal system. However, issues were encountered for salt marsh due to the presence of dense vegetation. The UAV-based photogrammetry approach with GNSS RTK ground surveys can hence be replicated in similar sites all over the world to evaluate restoration interventions and to develop new strategies for a better management of existing shorelines. Full article
(This article belongs to the Special Issue UAV for High-Resolution Salt Marsh Monitoring)
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