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Remote Sensing for Forecasting and Monitoring Aquatic Systems

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".

Deadline for manuscript submissions: 30 June 2024 | Viewed by 7374

Special Issue Editors

Hydraulics and Environment Department, University of Lisbon, 1700-066 Lisbon, Portugal
Interests: real-time forecasting and monitoring of aquatic systems; high-performance modeling in aquatic systems; web platforms for risk and emergency analysis
Special Issues, Collections and Topics in MDPI journals
Hydraulics and Environment Department, National Civil Engineering Laboratory (LNEC), 1700-066 Lisbon, Portugal
Interests: numerical modeling applied to estuarine and coastal dynamics; oil spill transport and weathering modeling in oceans, coastal zones, and estuaries; remote sensing for coastal zones and estuaries monitoring, applied to the detection of internal waves, oil spills, bathymetry estimation, water bodies, and coastline evolution

Special Issue Information

Dear Colleagues,

Monitoring and forecasting water dynamics are fundamental tools for managing aquatic systems and improving our knowledge of their processes. In the last decade, the availability of data from remote sensing of satellites, such as the Copernicus constellation and the DIAS platforms, on-board plane cameras, and onsite low-cost cameras, has promoted the development of multiple monitoring and forecasting systems for water applications. Either as stand-alone data-based methodologies or integrated complex IT platforms that include numerical models and in-situ sensors, remote sensing in water environments is now an essential component of research and management initiatives. The availability of large-scale computational resources, such as PRACE, EOSC, and other cloud commercial infrastructures (e.g., AWS, Google Earth Engine, or Azure), and IT technologies for web availability of information, such as webGIS, has also contributed to significant advances in the use of remote sensing to address water problems, such as rapid inundation mapping, leak detection in large water mains, or water quality prediction in aquaculture facilities.

This Special Issue will bring together innovative works related to “Remote Sensing for Forecasting and Monitoring Aquatic Systems”, addressing several key issues that include but are not limited to the following:

  • Remote sensing from satellites, plane or UAVs, and onsite cameras for water systems dynamics
  • Integrated forecast tools using remote sensing
  • WebGIS platforms for remote sensing-based monitoring and forecasting
  • Data fusion for satellite, in-situ, and camera data
Dr. Anabela Oliveira
Dr. Alberto Carlos Azevedo
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. Sensors 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 2600 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

  • Remote sensing from satellites, plane or UAVs, and onsite cameras
  • Integrated forecast tools
  • WebGIS platforms for remote sensing data
  • Satellite data fusion
  • Remote sensing monitoring services

Published Papers (2 papers)

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Research

30 pages, 21703 KiB  
Article
Multispectral Optical Remote Sensing for Water-Leak Detection
by Jean-Claude Krapez, Javier Sanchis Muñoz, Christophe Mazel, Christian Chatelard, Philippe Déliot, Yves-Michel Frédéric, Philippe Barillot, Franck Hélias, Juan Barba Polo, Vincent Olichon, Guillaume Serra, Céline Brignolles, Alexandra Carvalho, Duarte Carreira, Anabela Oliveira, Elsa Alves, André B. Fortunato, Alberto Azevedo, Paolo Benetazzo, Alessandro Bertoni and Isabelle Le Goffadd Show full author list remove Hide full author list
Sensors 2022, 22(3), 1057; https://0-doi-org.brum.beds.ac.uk/10.3390/s22031057 - 29 Jan 2022
Cited by 5 | Viewed by 4306
Abstract
Water losses from water distribution means have a high environmental impact in terms of natural resource depletion (water, energy, ecosystems). This work aims to develop an optical airborne surveillance service for the detection of water leaks (WADI—Water-tightness Airborne Detection Implementation) to provide water [...] Read more.
Water losses from water distribution means have a high environmental impact in terms of natural resource depletion (water, energy, ecosystems). This work aims to develop an optical airborne surveillance service for the detection of water leaks (WADI—Water-tightness Airborne Detection Implementation) to provide water utilities with adequate and timely information on leaks in water transportation mains outside urban areas. Firstly, a series of measurement campaigns were performed with two hyperspectral cameras and a thermal infrared camera in order to select the most appropriate wavelengths and combinations thereof for best revealing high moisture areas, which are taken as a proxy for water leakage. The Temperature-Vegetation-Index method (T-VI, also known as Triangle/Trapezoid method) was found to provide the highest contrast-to-noise ratio. This preliminary work helped select the most appropriate onboard instrumentation for two types of aerial platforms, manned (MAV) and unmanned (UAV). Afterwards, a series of measurement campaigns were performed from 2017 to 2019 in an operational environment over two water distribution networks in France and Portugal. Artificial leaks were introduced and both remote sensing platforms successfully detected them when excluding the unfavorable situations of a recent rain event or high vegetation presence. With the most recent equipment configuration, known and unknown real leaks in the overflown part of a water transportation network in Portugal have been detected. A significant number of false alarms were also observed which were due either to natural water flows (groundwater exfiltration, irrigation runoff and ponds) or to vegetation-cover variability nearby water-distribution nodes. Close interaction with the water utilities, and ancillary information like topographic factors (e.g., slope orientation), are expected to reduce the false alarm rates and improve WADI’s methodology performance. Full article
(This article belongs to the Special Issue Remote Sensing for Forecasting and Monitoring Aquatic Systems)
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17 pages, 5354 KiB  
Article
Tracking Fluorescent Dye Dispersion from an Unmanned Aerial Vehicle
by Pawel Burdziakowski, Piotr Zima, Pawel Wielgat and Dominika Kalinowska
Sensors 2021, 21(11), 3905; https://0-doi-org.brum.beds.ac.uk/10.3390/s21113905 - 05 Jun 2021
Cited by 4 | Viewed by 2278
Abstract
Commercial unmanned aerial vehicles continue to gain popularity and their use for collecting image data and recording new phenomena is becoming more frequent. This study presents an effective method for measuring the concentration of fluorescent dyes (fluorescein and Rhodamine WT) for the purpose [...] Read more.
Commercial unmanned aerial vehicles continue to gain popularity and their use for collecting image data and recording new phenomena is becoming more frequent. This study presents an effective method for measuring the concentration of fluorescent dyes (fluorescein and Rhodamine WT) for the purpose of providing a mathematical dispersion model. Image data obtained using a typical visible-light camera was used to measure the concentration of the dye floating on water. The reference measurement was taken using a laboratory fluorometer. The article presents the details of three extensive measurement sessions and presents elements of a newly developed method for measuring fluorescent tracer concentrations. The said method provides tracer concentration maps presented on the example of an orthophoto within a 2 × 2 m discrete grid. Full article
(This article belongs to the Special Issue Remote Sensing for Forecasting and Monitoring Aquatic Systems)
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