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Advances in Remote Sensing of the Inland and Coastal Water Zones

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

Deadline for manuscript submissions: closed (30 April 2022) | Viewed by 43023

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Special Issue Editors

Dr. Jacek Lubczonek

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Guest Editor

Institute of Geoinformatics, Maritime University of Szczecin, 70-500 Szczecin, Poland
Interests: image processing; shoreline extraction; spatial analyses; digital terrain modeling; sea bottom modeling; big data set reduction; neural networks
Special Issues, Collections and Topics in MDPI journals

Dr. Paweł Terefenko

E-Mail Website
Guest Editor

Institute of Marine and Environmental Sciences, University of Szczecin, 70-500 Szczecin, Poland
Interests: terrestrial laser scanner; remote sensing modeling of coastal environment; shoreline erosion; coastal geomorphology; coastal hazards; flood risk
Special Issues, Collections and Topics in MDPI journals

Dr. Katarzyna Bradtke

E-Mail Website
Guest Editor

Institute of Oceanography, University of Gdańsk, 80-309 Gdańsk, Poland
Interests: physical oceanography; satellite remote sensing; sea color; sea surface temperature; object based image analysis
Special Issues, Collections and Topics in MDPI journals

Dr. Marta Wlodarczyk-Sielicka

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Guest Editor

Department of Navigation, Maritime University of Szczecin, Waly Chrobrego 1-2, 70-500 Szczecin, Poland
Interests: spatial big data; spatial analysis; artificial neural networks; deep learning; data fusion; processing of bathymetric data; sea bottom modeling; data reduction
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The contact areas between water and land are an important element of the environment that is constantly changing. It is related to the influence of marine and inland water masses on land and the influence of various anthropogenic factors. One of the effects of the impact may be coastal erosion, changes in the coastline, the occurrence of floods, algal blooms, pollution or changes in the functioning of ecosystems. The balanced coexistence of these two environments requires constant monitoring. Taking into account the extent of inland and coastal water areas, such monitoring can be carried out with the use of remote sensing sensors on a scale covering local analyses or covering larger sections of banks, rivers or water reservoirs. More and more detailed and diversified remote sensing data of the aquatic environment and adjacent areas make it possible to conduct comprehensive studies, which is often related to their increasing resolution, completeness, availability or development of measuring instruments.

We dedicate a special edition to publications related to research on the environment of coastal and inland water zones, undertaking comprehensive and up-to-date solutions to scientific problems. Research may also be related to new applications of remote sensing data, the development of new methods of their processing or geospatial modelling. Taking into account the constant development of remote sensing, satellite, hydrographic, UAV and mobile sensors, in this special issue we wanted to focus on their use in various environmental aspects. Research may include, among others detection of changes taking place in coastal zones, analysis of water parameters, processing of data, creation of numerical terrain and bottom models, ecosystem analysis and other thematically related to a special edition.

Dr. Jacek Lubczonek
Dr. Paweł Terefenko
Dr. Katarzyna Bradtke
Dr. Marta Wlodarczyk-Sielicka
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

coastal zone
coastal geomorphology
inland waters
Shoreline change/ erosion
ecosystem
water parameters
water level
bathymetry
digital Elevation Models
data processing
data fusion
LIDAR
spatial big data
satellite remote sensing
algal blooms

Published Papers (13 papers)

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Editorial

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5 pages, 188 KiB

Open AccessEditorial

Advances in Remote Sensing of the Inland and Coastal Water Zones

by Jacek Lubczonek, Paweł Terefenko, Katarzyna Bradtke and Marta Wlodarczyk-Sielicka

Remote Sens. 2022, 14(21), 5346; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14215346 - 25 Oct 2022

Viewed by 896

Abstract

Coastal zone areas are important parts of the environment, very often subject to constant change [...] Full article

(This article belongs to the Special Issue Advances in Remote Sensing of the Inland and Coastal Water Zones)

Research

Jump to: Editorial, Other

19 pages, 6918 KiB

Open AccessArticle

Monitoring Sand Spit Variability Using Sentinel-2 and Google Earth Engine in a Mediterranean Estuary

by Mar Roca, Gabriel Navarro, Javier García-Sanabria and Isabel Caballero

Remote Sens. 2022, 14(10), 2345; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14102345 - 12 May 2022

Cited by 12 | Viewed by 3247

Abstract

Estuarine degradation is a major concern worldwide, and is rapidly increasing due to anthropogenic pressures. The Mediterranean Guadiaro estuary, located in San Roque (Cadiz, Spain), is an example of a highly modified estuary, showing severe negative effects of eutrophication episodes and beach erosion. The migration of its river mouth sand spit causes the closure of the estuary, resulting in serious water quality issues and flora and fauna mortality due to the lack of water renewal. With the aim of studying the Guadiaro estuary throughout a 4-year period (2017–2020), the Sentinel-2 A/B twin satellites of the Copernicus programme were used thanks to their 5-day and 10 m temporal and spatial resolution, respectively. Sea–land mapping was performed using the Normalized Difference Water Index (NDWI) in the Google Earth Engine (GEE) platform, selecting cloud-free Sentinel-2 Level 2A images and computing statistics. Results show a closure trend of the Guadiaro river mouth and no clear sand spit seasonal patterns. The study also reveals the potential of both Sentinel-2 and GEE for estuarine monitoring by means of an optimized processing workflow. This improvement will be useful for coastal management to ensure a continuous and detailed monitoring in the area, contributing to the development of early-warning tools, which can be helpful for supporting an ecosystem-based approach to coastal areas. Full article

(This article belongs to the Special Issue Advances in Remote Sensing of the Inland and Coastal Water Zones)

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21 pages, 9716 KiB

Open AccessArticle

Vertical Ground Displacements and Its Impact on Erosion along the Karachi Coastline, Pakistan

by Shamsa Kanwal, Xiaoli Ding, Songbo Wu and Muhammad Sajjad

Remote Sens. 2022, 14(9), 2054; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14092054 - 25 Apr 2022

Cited by 6 | Viewed by 3356

Abstract

This study employed remote sensing (optical and synthetic aperture radar) and data analysis techniques to quantify vertical ground displacements and assess their contribution to coastline erosion. To provide evidence from Pakistan, we selected the coast of Karachi—a mega-city located along the dynamic coastline of the Indus River Delta—which has been experiencing severe coastal erosion during the last few decades. Observations from the C-band Envisat/ASAR and Sentinel-1A sensors over the 2004–2010 and 2014–2016 periods, respectively, enabled us to study vertical ground displacements in the study area, providing a long-term assessment during 2004–2016. Results suggest that some areas along the Karachi coastline are subsiding at comparable rates to or even much higher than the relative sea-level rise (SLR, ~1.9 mm/yr), which may amplify the rates of relative SLR in coming years, along with accelerating coastal erosion. Various parts of the study area along the coast are unstable and undergoing displacement. Landsat images from 1989 to 2018 (10-year temporal resolution) were further used to examine the state of coastline erosion using three statistical approaches (i.e., End Point Rate (EPR), Linear Regression Rate (LRR), and Least Median of Squares (LMS)). While the erosion underlaid the majority of the eastern sections of the study area, the ground displacements were spatially heterogeneous across the study area and along the coastline. Erosion rates of ~2.4 m/yr spatially corresponded with ground displacement rates of up to ~−1.4 cm/yr, but not all the coastline segments with high annual mean erosion rates were associated with local mean subsidence. The causes of ground displacements and coastline erosion were analyzed, and results were interpreted by integrating spatial ancillary information. Results indicate that rapid urbanization, construction on reclaimed land, coastline erosion favoring seawater intrusion, failed drainage/sewerage networks, and soil liquefaction are contributing to the site-specific variations in the land displacement in Karachi. Full article

(This article belongs to the Special Issue Advances in Remote Sensing of the Inland and Coastal Water Zones)

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30 pages, 6667 KiB

Open AccessArticle

Assessment of Adjacency Correction over Inland Waters Using Sentinel-2 MSI Images

by Rejane S. Paulino, Vitor S. Martins, Evlyn M. L. M. Novo, Claudio C. F. Barbosa, Lino A. S. de Carvalho and Felipe N. Begliomini

Remote Sens. 2022, 14(8), 1829; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14081829 - 11 Apr 2022

Cited by 9 | Viewed by 3888

Abstract

Satellite remote sensing data have been used for water quality mapping, but accurate water reflectance retrieval is dependent on multiple procedures, such as atmospheric and adjacency corrections. For the latter, physical-based methods are used to minimize the adjacency effects caused by neighboring land targets close to water pixels, and implementation requires atmospheric and environmental parameters, such as aerosol optical depth and horizontal range (i.e., distance in meters) of the adjacency effect (

H_{Adj}

). Generally, the

H_{Adj}

is empirically defined by users and can lead to substantial errors in water reflectance when incorrectly used. In this research, a physical-based approach with three empirical methods to determine the

H_{Adj}

(fixed, SIMilarity Environment Correction—SIMEC, and Adaptative Window by Proportion—AWP-Inland Water) were used to correct and characterize the adjacency effects in Sentinel-2 images over Brazilian inland waters. An interactive inversion method of the deep blue waveband estimated the aerosol loading for the atmospheric correction procedure. The results of atmospheric and adjacency corrections were validated against in-situ reflectance data. The inverted aerosol loading achieved a good agreement with in-situ measurements, especially at visible wavelengths (Mean Absolute Percentage Error—MAPE for eutrophic (~56%), bright (~80%), and dark (~288%) waters). The adjacency correction performance was near similar between the SIMEC and AWP-Inland Water methods in eutrophic and bright waters (MAPE difference < 3%). However, only the AWP-Inland Water method provided a smaller error (MAPE ~53%) for dark waters compared to the fixed (~108%) and SIMEC (~289%) methods, which shows how critical

H_{Adj}

parametrization is for low water reflectance values. Simulations of different atmospheric and adjacency effects were performed, and they highlighted the importance of adjacency correction under aerosol loading higher 0.1, which is a typical aerosol loading in a dry climate season, and over extremely dark, low-reflectance waters. This paper contributes to further understanding adjacency effects in medium spatial resolution imagery of inland waters using a physical-based approach including the uncertainties in

H_{Adj}

determination. Full article

(This article belongs to the Special Issue Advances in Remote Sensing of the Inland and Coastal Water Zones)

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23 pages, 7549 KiB

Open AccessArticle

Using Augmented and Virtual Reality (AR/VR) to Support Safe Navigation on Inland and Coastal Water Zones

by Tomasz Templin, Dariusz Popielarczyk and Marcin Gryszko

Remote Sens. 2022, 14(6), 1520; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14061520 - 21 Mar 2022

Cited by 14 | Viewed by 5433

Abstract

The aim of this research is to propose a new solution to assist sailors in safe navigation on inland shallow waters by using Augmented and Virtual Reality. Despite continuous progress in the methodology of displaying bathymetric data and 3D models of the bottoms, there is still a lack of solutions promoting these data and their widespread use. Most existing products present navigation content on 2D/3D maps onscreen. Augmented Reality (AR) technology revolutionises the way digital content is displayed. This paper presents the solution for the use of AR on inland and coastal waterways to increase the safety of sailing and other activities on the water (diving, fishing, etc.). The real-time capability of AR in the proposed mobile application also allows other users to be observed on the water in limited visibility and even at night. The architecture and the prototype Mobile Augmented Reality (MAR) applications are presented. The required AR, including the preparation methodology supported by the Virtual Reality Geographic Information System (VRGIS), is also shown. The prototype’s performance has been validated in water navigation, specifically for exemplary lakes of Warmia and Mazury in Poland. The performed tests showed the great usefulness of AR in the field of content presentation during the navigation process. Full article

(This article belongs to the Special Issue Advances in Remote Sensing of the Inland and Coastal Water Zones)

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17 pages, 71919 KiB

Open AccessArticle

Multi-Temporal Analysis of Changes of the Southern Part of the Baltic Sea Coast Using Aerial Remote Sensing Data

by Krystyna Michałowska and Ewa Głowienka

Remote Sens. 2022, 14(5), 1212; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14051212 - 01 Mar 2022

Cited by 6 | Viewed by 2077

Abstract

Understanding processes that affect changes in the coastal zone and the ability to predict these processes in the future depends on the period for which detailed monitoring is carried out and on the type of coast. This paper analyzes a southern fragment of the Baltic coast (30 km), where there has been no anthropogenic impact (Slowinski National Park). The study was carried out covering a time interval of 65 years. Historic and current aerial photographs (orthophotomaps) from the following years: 1951, 1964, 1975, 1984, 1995, 2004, and 2016 were used. Changes in the position of the foredune toe line (FTL) in each years’ images were used. For each time interval (1951–1964, 1964–1975, 1975–1984, 1984–1995, 1995–2004, 2004–2016), the coastal area over which morphodynamic processes (erosion and accumulation) took place was calculated. The calculated RL (reference line)—FTL positions allowed us to determine differences in the shoreline course in subsequent years and to determine the extent of shifts/changes of the coastline in each time period. The study results showed an equilibrium between the processes of accumulation and erosion, proving that the development of the studied natural coastline is balanced. There was only a change in the trend of the characteristics of changes from erosive into accumulative ones and vice versa. Moreover, along the studied coast section, a certain periodicity in the coastline changes can be observed. The intervals where predominant erosion occurs alternate with those when accumulation prevails, and then the cycle repeats. The analysis of historic/current aerial images and orthophotomaps from 1951–2016 indicated that strong storms have a significant impact on the magnitude of change (accumulation/erosion) and the formation of the studied coastline. Full article

(This article belongs to the Special Issue Advances in Remote Sensing of the Inland and Coastal Water Zones)

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20 pages, 7257 KiB

Open AccessArticle

Simplified Method of Determination of the Sound Speed in Water on the Basis of Temperature Measurements and Salinity Prediction for Shallow Water Bathymetry

by Artur Makar

Remote Sens. 2022, 14(3), 636; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14030636 - 28 Jan 2022

Cited by 4 | Viewed by 4552

Abstract

The aim of this paper is to present a method of determining sound speed in water, based on temperature measurements executed by means of a laboratory low-cost thermometer with a probe provided with a long cable. It has been assumed that the salinity variation in respect to depth, found in a shallow water area, has insignificant impact on the sound velocity distribution determined by the temperature changes. The salinity data were obtained via the Internet service from the closest measuring station that registers surface water parameters. The sound speed in water was determined based on the formulas widely adopted in hydroacoustics and compared with the results obtained from the measurements executed by means of a Conductivity/Salinity Temperature Depth (CTD/STD) probe. The impact of inaccuracy in determining the sound speed in respect to the SingleBeam EchoSounder (SBES) immersion depth, i.e., a method commonly used by unmanned surface vessels in seaport measurements, was estimated. The measurements were taken in water areas of the Baltic Sea of low salinity and then verified with measurements in the Mediterranean Sea representing quite high salinity. The method is an alternative for calibrating the SBES the bar check way and has the capacity to meet the requirements in respect to its application in hydrographic surveys. Full article

(This article belongs to the Special Issue Advances in Remote Sensing of the Inland and Coastal Water Zones)

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18 pages, 9015 KiB

Open AccessArticle

Application of Unmanned Aerial Vehicles and Image Processing Techniques in Monitoring Underwater Coastal Protection Measures

by Jakub Śledziowski, Paweł Terefenko, Andrzej Giza, Paweł Forczmański, Andrzej Łysko, Witold Maćków, Grzegorz Stępień, Arkadiusz Tomczak and Apoloniusz Kurylczyk

Remote Sens. 2022, 14(3), 458; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14030458 - 19 Jan 2022

Cited by 9 | Viewed by 2606

Abstract

A prerequisite for solving issues associated with surf zone variability, which affect human activity in coastal zones, is an accurate estimation of the effects of coastal protection methods. Therefore, performing frequent monitoring activities, especially when applying new nature-friendly coastal defense methods, is a major challenge. In this manuscript, we propose a pipeline for performing low-cost monitoring using RGB images, accessed by an unmanned aerial vehicle (UAV) and a four-level analysis architecture of an underwater object detection methodology. First, several color-based pre-processing activities were applied. Second, contrast-limited adaptive histogram equalization and the Hough transform methodology were used to automatically detect the underwater, circle-shaped elements of a hybrid coastal defense construction. An alternative pipeline was used to detect holes in the circle-shaped elements with an adaptive thresholding method; this pipeline was subsequently applied to the normalized images. Finally, the concatenation of the results from both the methods and the validation processes were performed. The results indicate that our automated monitoring tool works for RGB images captured by a low-cost consumer UAV. The experimental results showed that our pipeline achieved an average error of four pixels in the test set. Full article

(This article belongs to the Special Issue Advances in Remote Sensing of the Inland and Coastal Water Zones)

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22 pages, 19242 KiB

Open AccessEditor’s ChoiceArticle

Open-Source Analysis of Submerged Aquatic Vegetation Cover in Complex Waters Using High-Resolution Satellite Remote Sensing: An Adaptable Framework

by Arthur de Grandpré, Christophe Kinnard and Andrea Bertolo

Remote Sens. 2022, 14(2), 267; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14020267 - 07 Jan 2022

Cited by 9 | Viewed by 3061

Abstract

Despite being recognized as a key component of shallow-water ecosystems, submerged aquatic vegetation (SAV) remains difficult to monitor over large spatial scales. Because of SAV’s structuring capabilities, high-resolution monitoring of submerged landscapes could generate highly valuable ecological data. Until now, high-resolution remote sensing of SAV has been largely limited to applications within costly image analysis software. In this paper, we propose an example of an adaptable open-sourced object-based image analysis (OBIA) workflow to generate SAV cover maps in complex aquatic environments. Using the R software, QGIS and Orfeo Toolbox, we apply radiometric calibration, atmospheric correction, a de-striping correction, and a hierarchical iterative OBIA random forest classification to generate SAV cover maps based on raw DigitalGlobe multispectral imagery. The workflow is applied to images taken over two spatially complex fluvial lakes in Quebec, Canada, using Quickbird-02 and Worldview-03 satellites. Classification performance based on training sets reveals conservative SAV cover estimates with less than 10% error across all classes except for lower SAV growth forms in the most turbid waters. In light of these results, we conclude that it is possible to monitor SAV distribution using high-resolution remote sensing within an open-sourced environment with a flexible and functional workflow. Full article

(This article belongs to the Special Issue Advances in Remote Sensing of the Inland and Coastal Water Zones)

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29 pages, 13306 KiB

Open AccessArticle

Methodology for Combining Data Acquired by Unmanned Surface and Aerial Vehicles to Create Digital Bathymetric Models in Shallow and Ultra-Shallow Waters

by Jacek Lubczonek, Witold Kazimierski, Grzegorz Zaniewicz and Malgorzata Lacka

Remote Sens. 2022, 14(1), 105; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14010105 - 27 Dec 2021

Cited by 19 | Viewed by 3887

Abstract

This paper presents a method for integrating data acquired by unmanned surface vehicles and unmanned aerial vehicles. The aim of this work was to create a uniform bathymetric surface extending to the shoreline. Such a body of water is usually characterized by ultra-shallow depths, which makes measurement impossible even with hydrographic autonomous vessels. Bathymetric data acquired by the photogrammetric method are, however, characterized by large errors with increasing depth. The presented method is based on processing of two data sets using a bathymetric reference surface and selection of points on the basis of generated masks. Numerical bathymetric models created by interpolation methods confirmed the usefulness of the concept adopted. Full article

(This article belongs to the Special Issue Advances in Remote Sensing of the Inland and Coastal Water Zones)

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17 pages, 5327 KiB

Open AccessCommunication

Atmospheric Correction of Airborne Hyperspectral CASI Data Using Polymer, 6S and FLAASH

by Mengmeng Yang, Yong Hu, Hongzhen Tian, Faisal Ahmed Khan, Qinping Liu, Joaquim I. Goes, Helga do R. Gomes and Wonkook Kim

Remote Sens. 2021, 13(24), 5062; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13245062 - 13 Dec 2021

Cited by 5 | Viewed by 2898

Abstract

Airborne hyperspectral data play an important role in remote sensing of coastal waters. However, before their application, atmospheric correction is required to remove or reduce the atmospheric effects caused by molecular and aerosol scattering and absorption. In this study, we first processed airborne hyperspectral CASI-1500 data acquired on 4 May 2019 over the Uljin coast of Korea with Polymer and then compared the performance with the other two widely used atmospheric correction approaches, i.e., 6S and FLAASH, to determine the most appropriate correction technique for CASI-1500 data in coastal waters. Our results show the superiority of Polymer over 6S and FLAASH in deriving the R_rs spectral shape and magnitude. The performance of Polymer was further evaluated by comparing CASI-1500 R_rs data with those obtained from the MODIS-Aqua sensor on 3 May 2019 and processed using Polymer. The spectral shapes of the derived R_rs from CASI-1500 and MODIS-Aqua matched well, but the magnitude of CASI-1500 R_rs was approximately 0.8 times lower than MODIS R_rs. The possible reasons for this difference were time difference (1 day) between CASI-1500 and MODIS data, higher land adjacency effect for MODIS-Aqua than for CASI-1500, and possible errors in MODIS R_rs from Polymer. Full article

(This article belongs to the Special Issue Advances in Remote Sensing of the Inland and Coastal Water Zones)

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26 pages, 21629 KiB

Open AccessArticle

Methodology for Developing a Combined Bathymetric and Topographic Surface Model Using Interpolation and Geodata Reduction Techniques

by Jacek Lubczonek, Marta Wlodarczyk-Sielicka, Malgorzata Lacka and Grzegorz Zaniewicz

Remote Sens. 2021, 13(21), 4427; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13214427 - 03 Nov 2021

Cited by 9 | Viewed by 2260

Abstract

The research in this paper is concerned with the development of a continuous elevation model in the coastal zones of inland waters. The source data for the creation of numerical terrain models were data acquired by contemporary sensors, such as such as a single-beam echosounder and an unmanned aircraft system. Different interpolation methods were tested in the study. A new approach in the research field is an interpolation method based on the processing of datasets with different degrees of spatial data reduction. The authors call it the Spatial Interpolation Method based on Data Reduction (SIMDR). The choice of method is based on quantitative and qualitative analysis, taking into account the type of interpolation and the method of geodata reduction. A proposal for the practical implementation of the method involves script processing, which automates the processes of modeling and error calculation. Full article

(This article belongs to the Special Issue Advances in Remote Sensing of the Inland and Coastal Water Zones)

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Other

Jump to: Editorial, Research

14 pages, 3518 KiB

Open AccessTechnical Note

Classification of Wetland Vegetation Based on NDVI Time Series from the HLS Dataset

by Yang Ju and Gil Bohrer

Remote Sens. 2022, 14(9), 2107; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14092107 - 27 Apr 2022

Cited by 17 | Viewed by 3180

Abstract

Natural wetlands are intrinsically heterogeneous and typically composed of a mosaic of ecosystem patches with different vegetation types. Hydrological and biogeochemical processes in wetlands vary strongly among these ecosystem patches. To date, most remote sensing classification approaches for wetland vegetation either rely on coarse images that cannot capture the spatial variability of wetland vegetation or rely on very-high-resolution multi-spectral images that are detailed but very sporadic in time (less than once per year). This study aimed to use NDVI time series, generated from NASA’s HLS dataset, to classify vegetation patches. We demonstrate our approach at a temperate, coastal lake, estuarine marsh. To classify vegetation patches, a standard time series library of the four land-cover patch types was built from referencing specific locations that were identified as “pure” pixels. These were identified using a single-time high-resolution image. We calculated the distance between the HLS-NDVI time series at each pixel and the “pure”-pixel standards for each land-cover type. The resulting true-positive classified rate was >73% for all patch types other than water lily. The classification accuracy was higher in pixels of a more uniform composition. A set of vegetation maps was created for the years 2016 to 2020 at our research site to identify the vegetation changes at the site as it is affected by rapid water elevation increases in Lake Erie. Our results reveal how changes in water elevation have changed the patch distribution in significant ways, leading to the local extinction of cattail by 2019 and a continuous increase in the area cover of water lily patches. Full article

(This article belongs to the Special Issue Advances in Remote Sensing of the Inland and Coastal Water Zones)

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