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Special Issue "Satellite Remotely Sensed Soil Moisture"

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

Deadline for manuscript submissions: 30 June 2019

Special Issue Editors

Guest Editor
Dr. José Darrozes

Géosciences Environnement Toulouse (GET), UMR 5563, CNRS/IRD/UPS, Observatoire Midi-Pyrénées (OMP), 14 Avenue Edouard Belin, 31400 Toulouse, France
Website | E-Mail
Interests: earth observation; river morphology; near surface geophysic; soil moisture; GNSS-R; water cycle
Guest Editor
Dr. Frédéric Frappart

Laboratoire d'Etudes en Géophysique et Océanographie Spatiales, UMR 5566, CNES/CNRS/IRD/UPS, Observatoire Midi-Pyrénées, 14 Avenue Edouard Belin, 31400 Toulouse, France
Website | E-Mail
Interests: earth observation; regional/global water cycle; land hydrology; surface water storage; terrestrial water storage
Guest Editor
Prof. Dr. Ernesto Lopez-Baeza

Climatology from Satellites Group, Faculty of Physics, Department of Earth Physics & Thermodynamics, University of Valencia, 46100 Valencia, Spain
Website | E-Mail
Interests: earth observation; soil moisture; vegetation biophysical parameetrs; GNSS-R; water cycle; water management

Special Issue Information

Dear Colleagues,

Soil moisture is a key component of the water cycle. It is also one of the main actor of the critical zone for conducting climate studies, weather predictions, flood monitoring and aquifer recharge. The different current measurement techniques have a wide range of characteristics in terms of spatial resolution, time resolution and precision. The optimization of one of these three parameters is unfortunately often to the detriment of the other two.

With the advent of remote sensing techniques, soil moisture is measured at a global scale, but to the detriment of temporal and spatial resolutions.

This Special Issue is dedicated to highlight the new downscaling/fusing researches (VNIS, SWIR, thermal IR, GNSS-R) and development of new sensors (from in situ to space-based sensors) for soil moisture retrieval.

Dr. José Darrozes
Dr. Frédéric Frappart
Dr. Ernesto Lopez-Baeza
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. 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 1800 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

  • GNSS-R
  • active and passive microwave remote sensing
  • thermal imagery
  • in situ gauge
  • fusing model
  • downscaling model
  • upscaling techniques
  • VNIR
  • SWIR
  • Multispectral/Hyperspectral imagery
  • GRACE
  • SMOS
  • SMAP
  • Sentinel-1

Published Papers (3 papers)

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Research

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Open AccessArticle Soil Moisture Retrieval by Integrating TASI-600 Airborne Thermal Data, WorldView 2 Satellite Data and Field Measurements: Petacciato Case Study
Sensors 2019, 19(7), 1515; https://doi.org/10.3390/s19071515
Received: 28 January 2019 / Revised: 19 March 2019 / Accepted: 25 March 2019 / Published: 28 March 2019
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Abstract
Soil moisture (SM) plays a fundamental role in the terrestrial water cycle and in agriculture, with key applications such as the monitoring of crop growing and hydrogeological management. In this study, a calibration procedure was applied to estimate SM based on the integration [...] Read more.
Soil moisture (SM) plays a fundamental role in the terrestrial water cycle and in agriculture, with key applications such as the monitoring of crop growing and hydrogeological management. In this study, a calibration procedure was applied to estimate SM based on the integration of in situ and airborne thermal remote sensing data. To this aim, on April 2018, two airborne campaigns were carried out with the TASI-600 multispectral thermal sensor on the Petacciato (Molise, Italy) area. Simultaneously, soil samples were collected in different agricultural fields of the study area to determine their moisture content and the granulometric composition. A WorldView 2 high-resolution visible-near infrared (VNIR) multispectral satellite image was acquired to calculate the albedo of the study area to be used together with the TASI images for the estimation of the apparent thermal inertia (ATI). Results show a good correlation (R2 = 0.62) between the estimated ATI and the SM of the soil samples measured in the laboratory. The proposed methodology has allowed us to obtain a SM map for bare and scarcely vegetated soils in a wide agricultural area in Italy which concerns cyclical hydrogeological instability phenomena. Full article
(This article belongs to the Special Issue Satellite Remotely Sensed Soil Moisture)
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Open AccessArticle Spatial Evaluation of Soil Moisture (SM), Land Surface Temperature (LST), and LST-Derived SM Indexes Dynamics during SMAPVEX12
Sensors 2019, 19(5), 1247; https://doi.org/10.3390/s19051247
Received: 11 February 2019 / Revised: 4 March 2019 / Accepted: 8 March 2019 / Published: 12 March 2019
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Abstract
Downscaling microwave soil moisture (SM) with optical/thermal remote sensing data has considerable application potential. Spatial correlations between SM and land surface temperature (LST) or LST-derived SM indexes (SMIs) are vital to the current optical/thermal and microwave fusion downscaling methods. In this study, the [...] Read more.
Downscaling microwave soil moisture (SM) with optical/thermal remote sensing data has considerable application potential. Spatial correlations between SM and land surface temperature (LST) or LST-derived SM indexes (SMIs) are vital to the current optical/thermal and microwave fusion downscaling methods. In this study, the spatial correlations were evaluated at the same spatial scale using SMAPVEX12 SM data and MODIS day/night LST products. LST-derived SMIs was calculated using NLDAS-2 gridded meteorological data with conventional trapezoid and two-stage trapezoid models. Results indicated that (1) SM agrees better with daytime LST than the nighttime or the day-night differential LST; (2) the daytime LSTs on Aqua and Terra present very similar spatial agreement with SM and they have very similar performances as downscaling factors in simulating SM; (3) decoupling effect among SM, LST, and LST-derived SMIs occurs not only in very wet but also in very dry condition; and (4) the decoupling effect degrades the performance of LST as a downscaling factor. The future downscaling algorithms should consider net surface radiation and soil type to tackle the decoupling effect. Full article
(This article belongs to the Special Issue Satellite Remotely Sensed Soil Moisture)
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Other

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Open AccessLetter Potential of Sentinel-1 Surface Soil Moisture Product for Detecting Heavy Rainfall in the South of France
Sensors 2019, 19(4), 802; https://doi.org/10.3390/s19040802
Received: 7 January 2019 / Revised: 31 January 2019 / Accepted: 14 February 2019 / Published: 16 February 2019
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Abstract
The objective of this paper is to present an analysis of Sentinel-1 derived surface soil moisture maps (S1-SSM) produced with high spatial resolution (at plot scale) and a revisit time of six days for the Occitanie region located in the South of France [...] Read more.
The objective of this paper is to present an analysis of Sentinel-1 derived surface soil moisture maps (S1-SSM) produced with high spatial resolution (at plot scale) and a revisit time of six days for the Occitanie region located in the South of France as a function of precipitation data, in order to investigate the potential of S1-SSM maps for detecting heavy rainfalls. First, the correlation between S1-SSM maps and rainfall maps provided by the Global Precipitation Mission (GPM) was investigated. Then, we analyzed the effect of the S1-SSM temporal resolution on detecting heavy rainfall events and the impact of these events on S1-SSM values as a function of the number of days that separated the heavy rainfall and the S1 acquisition date (cumulative rainfall more than 60 mm in 24 hours or 80 mm in 48 hours). The results showed that the six-day temporal resolution of the S1-SSM map doesn’t always permit the detection of an extreme rainfall event, because confusion will appear between high S1-SSM values due to extreme rainfall events occurring six days before the acquisition of S1-SSM, and high S1-SSM values due to light rain a few hours before the acquisition of Sentinel-1 images. Moreover, the monitoring of extreme rain events using only soil moisture maps remains difficult, since many environmental parameters could affect the value of SSM, and synthetic aperture radar (SAR) doesn’t allow the estimation of very high soil moistures (higher than 35 vol.%). Full article
(This article belongs to the Special Issue Satellite Remotely Sensed Soil Moisture)
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