Special Issue "New Outstanding Results over Land from the SMOS Mission"

A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: 30 June 2020.

Special Issue Editors

Dr. Amen Al-Yaari
E-Mail Website
Guest Editor
INRA Bordeaux-Aquitaine, Villenave-d'Ornon, France
Interests: soil moisture; microwave remote sensing; hydrology; vegetation water content; climate; agriculture
Dr. Arnaud Mialon
E-Mail Website
Guest Editor
CESBIO, CNES/CNRS/IRD/UPS, UMR 5126, 31401 Toulouse CEDEX 9, France
Interests: surface soil moisture; SMOS; L-VOD; passive microwave
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Surface soil moisture (the water content in the first centimeters of soil) is an essential climate variable that plays an important role in land–atmosphere interactions. Soil moisture is widely used in improving climate model predictions/projections, weather forecasting, drought monitoring, rainfall estimations, etc.

Monitoring surface soil moisture at a global scale has recently become possible thanks to microwave remote sensing. SMOS (Soil Moisture and Ocean Salinity) was the first dedicated soil moisture mission that has been in orbit for eight years. The SMOS satellite was launched by the European Space Agency (ESA) in 2009, carrying on board a radiometer in the L-band frequency with a spatial resolution of ~43 km. Since then, soil moisture and vegetation optical depth (VOD) have been retrieved from multi-angular brightness temperature observations relying mainly on a radiative transfer model. 

This is a dedicated Special Issue on SMOS. We welcome studies on all subjects that are related to the SMOS satellite and its products.

Potential topics include, but are not limited to, the following:

  • the improvements in the soil moisture/VOD retrieval algorithms;
  • the evaluation/validation of the SMOS soil moisture and VOD products;
  • SMOS synergy with other remote sensing observations or models simulations;
  • SMOS soil moisture/VOD applications for agriculture, hydrology, etc.

Dr. Amen Al-Yaari
Dr. Arnaud Mialon
Guest Editors

Manuscript Submission Information

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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 2000 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

  • SMOS
  • Soil moisture
  • Validation
  • Application
  • Synergy

Published Papers (3 papers)

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Research

Open AccessArticle
Estimating Root Zone Soil Moisture Across the Eastern United States with Passive Microwave Satellite Data and a Simple Hydrologic Model
Remote Sens. 2019, 11(17), 2013; https://doi.org/10.3390/rs11172013 - 27 Aug 2019
Abstract
Root zone soil moisture (RZSM) affects many natural processes and is an important component of environmental modeling, but it is expensive and challenging to monitor for relatively small spatial extents. Satellite datasets offer ample spatial coverage of near-surface soil moisture content at up [...] Read more.
Root zone soil moisture (RZSM) affects many natural processes and is an important component of environmental modeling, but it is expensive and challenging to monitor for relatively small spatial extents. Satellite datasets offer ample spatial coverage of near-surface soil moisture content at up to a daily time-step, but satellite-derived data products are currently too coarse in spatial resolution to use directly for many environmental applications, such as those for small catchments. This study investigated the use of passive microwave satellite soil moisture data products in a simple hydrologic model to provide root zone soil moisture estimates across a small catchment over a two year time period and the Eastern U.S. (EUS) at a 1 km resolution over a decadal time-scale. The physically based soil moisture analytical relationship (SMAR) was calibrated and tested with the Advanced Microwave Scanning Radiometer (AMSRE), Soil Moisture Ocean Salinity (SMOS), and Soil Moisture Active Passive (SMAP) data products. The SMAR spatial model relies on maps of soil physical properties and was first tested at the Shale Hills experimental catchment in central Pennsylvania. The model met a root mean square error (RMSE) benchmark of 0.06 cm3 cm−3 at 66% of the locations throughout the catchment. Then, the SMAR spatial model was calibrated at up to 68 sites (SCAN and AMERIFLUX network sites) that monitor soil moisture across the EUS region, and maps of SMAR parameters were generated for each satellite data product. The average RMSE for RZSM estimates from each satellite data product is <0.06 cm3 cm−3. Lastly, the 1 km EUS regional RZSM maps were tested with data from the Shale Hills, which was set aside for validating the regional SMAR, and the RMSE between the RZSM predictions and the catchment average is 0.042 cm3 cm−3. This study offers a promising approach for generating long time-series of regional RZSM maps with the same spatial resolution of soil property maps. Full article
(This article belongs to the Special Issue New Outstanding Results over Land from the SMOS Mission)
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Open AccessArticle
Evaluation of Soil Moisture Variability in Poland from SMOS Satellite Observations
Remote Sens. 2019, 11(11), 1280; https://doi.org/10.3390/rs11111280 - 29 May 2019
Cited by 1
Abstract
Soil moisture (SM) data play an important role in agriculture, hydrology, and climate sciences. In this study, we examined the spatial-temporal variability of soil moisture using Soil Moisture Ocean Salinity (SMOS) satellite measurements for Poland from a five-year period (2010–2014). SMOS L2 v. [...] Read more.
Soil moisture (SM) data play an important role in agriculture, hydrology, and climate sciences. In this study, we examined the spatial-temporal variability of soil moisture using Soil Moisture Ocean Salinity (SMOS) satellite measurements for Poland from a five-year period (2010–2014). SMOS L2 v. 551 datasets (latitudinal rectangle 1600 × 840 km, centered in Poland) averaged for quarterly (three months corresponding to winter, spring, summer, and autumn) and yearly values were used. The results were analysed with the use of classical statistics and geostatistics (using semivariograms) to acquire information about the nature of anisotropy and the lengths and directions of spatial dependences. The minimum (close to zero) and maximum soil moisture values covered the 0.5 m3 m−3 range. In particular quarters, average soil moisture did not exceed 0.2 m3 m−3 and did not drop below 0.12 m3 m−3; the corresponding values in the study years were 0.171 m3 m−3 and 0.128 m3 m−3. The highest variability of SM occurred generally in winter (coefficient of variation, CV, up to 40%) and the lowest value was recorded in spring (around 23%). The average CV for all years was 32%. The quarterly maximum (max) soil moisture contents were well positively correlated with the average soil moisture contents (R2 = 0.63). Most of the soil moisture distributions (histograms) were close to normal distribution and asymmetric data were transformed with the square root to facilitate geostatistical analysis. Isotropic and anisotropic empirical semivariograms were constructed and the theoretical exponential models were well fitted (R2 > 0.9). In general, the structural dependence of the semivariance was strong and moderate. The nugget (C0) values slightly deceased with increasing soil moisture while the sills (C0 + C) increased. The effective ranges of spatial dependence (A) were between 1° and 4° (110–440 km of linear distance). Generally, the ranges were greater for drier than moist soils. Anisotropy of the SM distribution exhibited different orientation with predominance from north-west to south-east in winter and spring and changed for from north-east to south-west or from north to south in the other seasons. The fractal dimension values showed that the distribution of the soil moisture pattern was less diverse (smoother) in the winter and spring, compared to that in the summer and autumn. The soil moisture maps showed occurrence of wet areas (soil moisture > 0.25 m3 m−3) in the north-eastern, south-eastern and western parts and dry areas (soil moisture < 0.05 m3 m−3) mainly in the central part (oriented towards the south) of Poland. The spatial distribution of SM was attributed to soil texture patterns and associated with water holding capacity and permeability. The results will help undertake appropriate steps to minimize susceptibility to drought and flooding in different regions of Poland. Full article
(This article belongs to the Special Issue New Outstanding Results over Land from the SMOS Mission)
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Open AccessFeature PaperArticle
The AQUI Soil Moisture Network for Satellite Microwave Remote Sensing Validation in South-Western France
Remote Sens. 2018, 10(11), 1839; https://doi.org/10.3390/rs10111839 - 20 Nov 2018
Cited by 2
Abstract
Global soil moisture (SM) products are currently available thanks to microwave remote sensing techniques. Validation of these satellite-based SM products over different vegetation and climate conditions is a crucial step. INRA (National Institute of Agricultural Research) has set up the AQUI SM and [...] Read more.
Global soil moisture (SM) products are currently available thanks to microwave remote sensing techniques. Validation of these satellite-based SM products over different vegetation and climate conditions is a crucial step. INRA (National Institute of Agricultural Research) has set up the AQUI SM and soil temperature in situ network (composed of three main sites Bouron, Bilos, and Hermitage), over a flat area of dense pine forests, in South-Western France (the Bordeaux–Aquitaine region) to validate the Soil Moisture and Ocean salinity (SMOS) satellite SM products. SMOS was launched in 2009 by the European Space Agency (ESA). The aims of this study are to present the AQUI network and to evaluate the SMOS SM product (in the new SMOS-IC version) along with other microwave SM products such as the active ASCAT (Advanced Scatterometer) and the ESA combined (passive and active) CCI (Climate Change Initiative) SM retrievals. A first comparison, using Pearson correlation, Bias, RMSE (Root Mean Square Error), and Un biased RMSE (ubRMSE) scores, between the 0–5 cm AQUI network and ASCAT, CCI, and SMOS SM products was conducted. In general all the three products were able to reproduce the annual cycle of the AQUI in situ observations. CCI and ASCAT had best and similar correlations (R~0.72) over the Bouron and Bilos sites. All had comparable correlations over the Hermitage sites with overall average values of 0.74, 0.68, and 0.69 for CCI, SMOS-IC, and ASCAT, respectively. Considering anomalies, correlation values decreased for all products with best ability to capture day to day variations obtained by ASCAT. CCI (followed by SMOS-IC) had the best ubRMSE values (mostly < 0.04 m3/m3) over most of the stations. Although the region is highly impacted by radio frequency interferences, SMOS-IC followed correctly the in situ SM dynamics. All the three remotely-sensed SM products (except SMOS-IC over some stations) overestimated the AQUI in situ SM observations. These results demonstrate that the AQUI network is likely to be well-suited for satellite microwave remote sensing evaluations/validations. Full article
(This article belongs to the Special Issue New Outstanding Results over Land from the SMOS Mission)
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