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Remote Sensing
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Advances in Remote Sensing for Regional Soil Moisture Monitoring
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Advances in Remote Sensing for Regional Soil Moisture 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: 14 September 2024 | Viewed by 677

Special Issue Editors

Dr. Qi Gao

E-Mail Website
Guest Editor
Remote Sensing Department, Division of Geomatics, Centre Tecnològic de Telecomunicacions de Catalunya (CTTC), Av. Gauss, 7 E-08860 Castelldefels, Barcelona, Spain
Interests: SAR and SAR data processing; SAR interferometry; land deformation; hydrology; water management; hazard monitoring
Special Issues, Collections and Topics in MDPI journals
Dr. Mehrez Zribi

E-Mail Website
Guest Editor
CESBIO, University of Toulouse, CNRS/UT3/IRD/CNES/INRAE, 31400 Toulouse, France
Interests: remote sensing; synthetic aperture radar; GNSS-R; airborne microwave instrumentation; soil moisture; vegetation; hydrology; water resources
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Massimo Menenti

E-Mail Website
Guest Editor
1. State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
2. Department of Geoscience and Remote Sensing, Faculty of Civil Engineering and Geosciences, Delft University of Technology, 2628 Delft, The Netherlands
Interests: land surface processes; terrestrial water cycle; water management; optical remote sensing
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Jian Peng

E-Mail Website
Guest Editor
Helmholtz Centre for Environmental Research—UFZ, Permoserstraße 15, 04318 Leipzig, Germany
Interests: quantitative retrieval of land surface parameters from remote sensing data; radiative transfer in soil–vegetation–atmosphere systems; process-based modeling and data-driven methods; hydroclimatic extremes
Special Issues, Collections and Topics in MDPI journals
Dr. Tianjie Zhao

E-Mail Website
Guest Editor
Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
Interests: soil moisture; passive microwave; hydrology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Remote sensing technologies have revolutionized our ability to monitor soil moisture dynamics at a regional scale, facilitating effective water resource management and sustainable agriculture practices. By leveraging multi-sensor remote sensing observations, in situ measurements, geographical data from multiple thematic scales, and model-data fusion techniques, researchers can capture the spatiotemporal variations of soil moisture and provide valuable insights for decision-making.

This Special Issue focuses on advances in remote sensing for regional soil moisture monitoring. It aims to bring together cutting-edge research in the field, highlighting innovative approaches, case studies, and review discussions that enhance our ability to retrieve and understand soil moisture dynamics and their applications. We welcome submissions that explore the forefront of remote sensing techniques and methodologies specifically tailored to regional soil moisture monitoring.

Topics of interest include, but are not limited to, the following:

  • Unmanned aerial vehicle remote sensing for the high-resolution and near-real-time monitoring of soil moisture
  • Innovative remote sensing techniques for the retrieval of soil moisture
  • Analysis of recently available and near future satellite data products for regional soil moisture monitoring
  • Airborne calibration and validation experiments to showcase potential innovations for future remote sensing technologies
  • Case studies demonstrating the application of remote sensing in regional-scale soil moisture assessment
  • Approaches for integrating remote sensing and in situ observations to improve soil moisture monitoring accuracy
  • The impacts of soil moisture variability on hydrological processes, agricultural productivity, and climate dynamics
  • Uncertainty quantification and error propagation in remote-sensing-based soil moisture retrieval

Dr. Qi Gao
Dr. Mehrez Zribi
Prof. Dr. Massimo Menenti
Prof. Dr. Jian Peng
Dr. Tianjie Zhao
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

  • remote sensing
  • soil moisture
  • water resources management
  • regional scale
  • hydrological processes
  • data integration and interpretation
  • multi-sensor remote sensing observations

Published Papers (1 paper)

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Research

16 pages, 6217 KiB  
Article
Medium-Scale Soil Moisture Retrievals Using an ELBARA L-Band Radiometer Using Time-Dependent Parameters for Wetland-Meadow-Cropland Site
by Kamil Szewczak and Mateusz Łukowski
Remote Sens. 2024, 16(12), 2200; https://0-doi-org.brum.beds.ac.uk/10.3390/rs16122200 - 17 Jun 2024
Viewed by 216
Abstract
The soil moisture at the medium spatial scale is strongly desired in the context of satellite remote sensing data validation. The use of a ground-installed passive L-band radiometer ELBARA at the Bubnów-Sęków test site in the east of Poland gave a possibility to [...] Read more.
The soil moisture at the medium spatial scale is strongly desired in the context of satellite remote sensing data validation. The use of a ground-installed passive L-band radiometer ELBARA at the Bubnów-Sęków test site in the east of Poland gave a possibility to provide reference soil moisture data from the area with a radius of 100 m. In addition, the test site comprised three different land cover types that could be investigated continuously with one day resolution. The studies were focused on the evaluation of the ω-τ model coefficients for three types of land cover, including meadow, wetland, and cropland, to allow for the assessment of the soil moisture retrievals at a medium scale. Consequently, a set of reference time-dependent coefficients of effective scattering albedo, optical depth, and constant-in-time roughness parameters were estimated. The mean annual values of the effective scattering albedo including two polarisations were 0.45, 0.26, 0.14, and 0.54 for the meadow with lower organic matter, the meadow with higher organic matter, the wetland, and the cropland, respectively. The values of optical depth were in the range from 0.30 to 0.80 for the cropland, from 0.40 to 0.52 for the meadows (including the two investigated meadows), and from 0.60 to 0.70 for the wetland. Time-constant values of roughness parameters at the level of 0.45 were obtained. Full article
(This article belongs to the Special Issue Advances in Remote Sensing for Regional Soil Moisture Monitoring)
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