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Remote Sensing
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Field-Scale Monitoring for Water Resources and Ecosystems Management: From Drone...
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Field-Scale Monitoring for Water Resources and Ecosystems Management: From Drone to Satellite Imagery

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

Deadline for manuscript submissions: closed (20 July 2023) | Viewed by 2079

Special Issue Editors

Dr. Giuseppe Francesco Cesare Lama

E-Mail Website
Guest Editor
Department of Agricultural Sciences, University of Naples Federico II, 80055 Portici, Italy
Interests: ecohydraulics; vegetated flows; turbulence; CFD; experimental analysis; water resources management; remote sensing; river hydraulics
Special Issues, Collections and Topics in MDPI journals
Dr. Gianluigi Busico

E-Mail Website
Guest Editor
Department of Environmental, Biological and Pharmaceutical Sciences and Technologies, Campania University “Luigi Vanvitelli”, Caserta, Italy
Interests: hydrology; hydrogeology; groundwater flows; environmental science; water quality; geostatistical analysis; digital mapping; ecohydrology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Riparian and Riverine vegetation is amongst the most impacting ecohydraulical and ecohydrological key factors in the management of water resources and both aquatic and terrestrial ecosystems, considerably affecting vegetated water systems almost worldwide. Drone- and satellite-based imagery of vegetated open channels and watersheds allow for site-specific riparian and riverine vegetation management, which is a highly efficient methodology that is beneficial to the environment and ecosystem services in both constructed and natural territories. The most notable advantages of such methods are embodied by observing and then analyzing the main riparian plants’ traits in hardly accessible areas such as vegetated water bodies and basins massively covered by riparian biomass. Moreover, it is important to highlight that scientific and technical understanding of the specific research goals and available technology for obtaining the most accurate predictions of those traits is necessary to rapidly advance in this field. Drone-based images and post-processing are also extremely useful in obtaining digital terrain models (dtm) or land-cover characteristics to use as input for superficial water modeling to increase model resolution in data-scarce areas, aimed at reducing flood and erosion risk. In this Special Issue, we invite the authors to submit their articles focusing on a wide overview of the most suitable drone- and satellite-based image processing methodologies for the field-scale monitoring of both natural and urban water bodies and watersheds, pointing out their huge potential in the management of vegetated water systems and natural resources and to reducing disaster risk.

Dr. Giuseppe Francesco Cesare Lama
Dr. Gianluigi Busico
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

  • UAV
  • ecohydraulics
  • ecohydrology
  • water resources management
  • surface water modeling
  • satellites
  • vegetated waterways

Published Papers (1 paper)

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Research

16 pages, 3259 KiB  
Article
Snowfall Variation in Eastern Mediterranean Catchments
by Kalliopi Artemis Voudouri, Maria Margarita Ntona and Nerantzis Kazakis
Remote Sens. 2023, 15(6), 1596; https://doi.org/10.3390/rs15061596 - 15 Mar 2023
Cited by 2 | Viewed by 1469
Abstract
This study aims to present and analyze the time series of the snow parameters focusing on representative geographical areas of the Eastern Mediterranean (i.e., Greece and Italy) and to examine their seasonal variability, in terms of region and geography. The satellite retrievals were [...] Read more.
This study aims to present and analyze the time series of the snow parameters focusing on representative geographical areas of the Eastern Mediterranean (i.e., Greece and Italy) and to examine their seasonal variability, in terms of region and geography. The satellite retrievals were firstly validated against in-situ retrievals for 67 common days, with a mean bias equal to −0.018 cm, with a near-Gaussian distribution, showing the good performance of the satellite snow detection. The satellite-based analysis resulted in increasing trends of snow water equivalent, attributed to the enhanced values between 2000 and 2009; however, decreasing trends are found starting from 2010 until now of −1.79 × 10−17 and −2.31 × 10−18 over the two representative areas of Greece (e.g., Thessaloniki and Kozani). A similar pattern is found for the snow water equivalent in the Italian study area, with a decreasing trend of −4.45 × 10−18. The presented results contribute to a better understanding of the spatial snow distribution and the snow coverage seasonality that could be crucial for the long-term groundwater management, by combining snow data trends from in-situ data and satellite statistics. Full article
(This article belongs to the Special Issue Field-Scale Monitoring for Water Resources and Ecosystems Management: From Drone to Satellite Imagery)
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