Special Issue "Remote Sensing in Aquatic Vegetation 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: 31 October 2021.

Special Issue Editors

Dr. Thomas Schneider
E-Mail Website
Guest Editor
Technical University Munich (TUM), Chair for Aquatic System Biology, Limnological Station, Arcisstrasse 21, 80333 Munich, Germany
Interests: remote sensing of submersed macrophytes; aquatic reed inventory and monitoring; catchment area impact; climate change impact; field spectroscopy and goniometry
Prof. Dr. Natascha Oppelt
E-Mail Website
Guest Editor
Christian-Albrechts-University Kiel (CAU), Department for Geography, Remote Sensing & Environmental Modelling, 24118 Kiel, Germany
Interests: remote sensing of deep and shallow water; monitoring of shallow benthis coverage; coupling of earth observation data and modelling approaches; time series nalysis and sensor fusion
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Special Issue Information

Aquatic plants, or macrophytes, are primary producers that grow in water (salt- or freshwater) and are either emergent, submergent, or floating. Macrophytes provide habitats for fish and aquatic invertebrates, produce oxygen, and act as food for fish and wildlife. Macrophytes are sessile, react on changes in the environment, and are therefore indicators for changing environmental conditions; the macrophyte index, for instance, is an integral part of the European Water Framework Directive (EU-WFD) and is understood as a long-term trophy status indicator. The growth of macrophytes is influenced by global change effects like the increase in water temperatures, more frequent extreme events (such as heavy rain, storm, drought periods), as well as changes in land use within the catchment of tributaries. These phenomena affect population composition, growth dynamics and promote endemic or alien invasive species. Ship-, air- and space-borne remote sensing (RS) approaches can support inventory and monitoring of macrophytes. At present, mainly optical systems are in use to analyse spatial, spectral, or temporal changes and to deliver information on bathymetry. Sonar and Green Lidar techniques complement the spectral information-based approaches of optical systems by bathymetric information and, to some extent, height information of macrophyte populations, expected to improve biomass estimation in contribution to methane emissions by lakes and rivers.

Manuscripts handed in for publication may cover the following aspects:

  • Measurement frequency: across the daytime, mono-temporal, multi-seasonal (x-times per vegetation period), multi-temporal (successive years, same phenological phase)
  • Measurement level: ‘in-situ’/’ex-situ’, ship, drone, airplane, satellite
  • Instrumentation: broadband (e.g. PAR sensors, fluorescence), multi- to hyperspectral, sonar, Lidar
  • Environmental setups/frame conditions:
    • lake type, size, water contents, bathymethry effects (depth, slope, aspect, bottom type), atmosphere, daytime, etc.
    • phenology changes (identification, growth competition)
    • catchment effects (land use changes, connectivity of lakes)
  • Criteria for identification and status assessment
  • Analytical methods: growth modelling, supporting datasets, joint approaches (environmental DNA (eDNA), citizen science approaches, interaction freshwater body management/trophy status, interaction macrophytes/fishery, etc.)
  • Analytical goals:
    • Emersed aquatic populations and status indicators (frontline structure, vitality, density, height, species mixture)
    • Submersed (including floating) species composition for EU-WFD, invasive species identification, growth depth and biomass, especially with regard to methane greenhouse gas emissions
Dr. Thomas Schneider
Prof. Dr. Natascha Oppelt
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 papers will be 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 2400 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

  • Identification of aquatic vegetation communities
  • Phenology and detectability of submersed macrophytes
  • Invasive species
  • Influence of periphyton on lake bottom signal
  • Water contents and detectability
  • Climate change effects
  • Water level changes
  • Status assessment of submerged and emerged aquatic vegetation
  • Bathymetry related issues
  • Fish/macrophyte interactions
  • Catchment area influences
  • Sensor fusion
  • Time series analysis

Published Papers (2 papers)

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Research

Article
Spotting Green Tides over Brittany from Space: Three Decades of Monitoring with Landsat Imagery
Remote Sens. 2021, 13(8), 1408; https://doi.org/10.3390/rs13081408 - 07 Apr 2021
Cited by 3 | Viewed by 973
Abstract
Green tides of macroalgae have been negatively affecting the coasts of Brittany, France, for at least five decades, caused by excessive nitrogen inputs from the farming sector. Regular areal estimates of green tide surfaces are publicly available but only from 2002 onwards. Using [...] Read more.
Green tides of macroalgae have been negatively affecting the coasts of Brittany, France, for at least five decades, caused by excessive nitrogen inputs from the farming sector. Regular areal estimates of green tide surfaces are publicly available but only from 2002 onwards. Using free and openly accessible Landsat satellite imagery archives over 35 years (1984–2019), this study explores the potential of remote sensing for detection and long-term monitoring of green macroalgae blooms. By using a Google Earth Engine (GEE) script, we were able to detect and quantify green tide surfaces using the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) at four highly affected beaches in Northern Brittany. Mean green tide coverage was derived and analyzed from 1984 to 2019, at both monthly and annual scales. Our results show important interannual and seasonal fluctuations in estimated macroalgae cover. In terms of trends over time, green tide events did not show a decrease in extent at three out of four studied sites. The observed decrease in nitrogen concentrations for the rivers draining the study sites has not resulted in a reduction of green tide extents. Full article
(This article belongs to the Special Issue Remote Sensing in Aquatic Vegetation Monitoring)
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Article
Monitoring the Efficacy of Crested Floatingheart (Nymphoides cristata) Management with Object-Based Image Analysis of UAS Imagery
Remote Sens. 2021, 13(4), 830; https://doi.org/10.3390/rs13040830 - 23 Feb 2021
Cited by 1 | Viewed by 758
Abstract
This study investigates the use of unmanned aerial systems (UAS) mapping for monitoring the efficacy of invasive aquatic vegetation (AV) management on a floating-leaved AV species, Nymphoides cristata (CFH). The study site consists of 48 treatment plots (TPs). Based on six unique flights [...] Read more.
This study investigates the use of unmanned aerial systems (UAS) mapping for monitoring the efficacy of invasive aquatic vegetation (AV) management on a floating-leaved AV species, Nymphoides cristata (CFH). The study site consists of 48 treatment plots (TPs). Based on six unique flights over two days at three different flight altitudes while using both a multispectral and RGB sensor, accuracy assessment of the final object-based image analysis (OBIA)-derived classified images yielded overall accuracies ranging from 89.6% to 95.4%. The multispectral sensor was significantly more accurate than the RGB sensor at measuring CFH areal coverage within each TP only with the highest multispectral, spatial resolution (2.7 cm/pix at 40 m altitude). When measuring response in the AV community area between the day of treatment and two weeks after treatment, there was no significant difference between the temporal area change from the reference datasets and the area changes derived from either the RGB or multispectral sensor. Thus, water resource managers need to weigh small gains in accuracy from using multispectral sensors against other operational considerations such as the additional processing time due to increased file sizes, higher financial costs for equipment procurements, and longer flight durations in the field when operating multispectral sensors. Full article
(This article belongs to the Special Issue Remote Sensing in Aquatic Vegetation Monitoring)
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