Sensitivity of satellite microwave and infrared observations to soil moisture at a global scale: Relationship of satellite observations to in situ soil moisture measurements

2005 ◽  
Vol 110 (D7) ◽  
Author(s):  
Catherine Prigent
Keyword(s):  
Soil Moisture ◽  
Global Scale ◽  
Satellite Observations ◽  
Infrared Observations ◽  
Satellite Microwave ◽  
Relationship Of

scholarly journals Quality Improvement of Satellite Soil Moisture Products by Fusing with In-Situ Measurements and GNSS-R Estimates in the Western Continental U.S.

2018 ◽  
Vol 10 (9) ◽  
pp. 1351 ◽  
Author(s):  
Hongzhang Xu ◽  
Qiangqiang Yuan ◽  
Tongwen Li ◽  
Huanfeng Shen ◽  
Liangpei Zhang ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Water Cycle ◽  
Satellite System ◽  
Global Scale ◽  
Generalized Regression Neural Network ◽  
Level 3 ◽  
Global Navigation Satellite ◽  
Microwave Sensors ◽  
Surface Fusion

Soil moisture is a key component of the water cycle budget. Sensing soil moisture using microwave sensors onboard satellites is an effective way to retrieve surface soil moisture (SSM) at a global scale, but the retrieval accuracy in some regions is inadequate due to the complicated factors influencing the general retrieval process. On the other hand, monitoring soil moisture directly through in-situ devices is capable of providing high-accuracy SSM measurements, but the distribution of such stations is sparse. Recently, the Global Navigation Satellite System interferometric Reflectometry (GNSS-R) method was used to derive field-scale SSM, which can serve as a supplement to contemporary sparse in-situ soil moisture networks. On this basis, it is of great research significance to explore the fusion of these different kinds of SSM data, so as to improve the present satellite SSM products with regard to their data accuracy. In this paper, a multi-source point-surface fusion method based on the generalized regression neural network (GRNN) model is applied to fuse the Soil Moisture Active Passive (SMAP) Level 3 radiometer SSM daily product with in-situ measured and GNSS-R estimated SSM data from five soil moisture networks in the western continental U.S. The results show that the GRNN model obtains a fairly good performance, with a cross-validation R value of approximately 0.9 and a ubRMSE of 0.044 cm3 cm−3. Furthermore, the fused SSM product agrees well with the site-specific SSM data in terms of time and space, which demonstrates that the proposed GRNN model is able to construct the non-linear relationship between the point- and surface-scale SSM.

scholarly journals Intercomparison of Salinity Products in the Beaufort Gyre and Arctic Ocean

2021 ◽  
Vol 14 (1) ◽  
pp. 71
Author(s):  
Sarah B. Hall ◽  
Bulusu Subrahmanyam ◽  
James H. Morison
Keyword(s):  
Soil Moisture ◽  
Arctic Ocean ◽  
Satellite Observations ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
The Arctic ◽  
Surface Salinity ◽  
Beaufort Gyre ◽  
The Arctic Ocean

Salinity is the primary determinant of the Arctic Ocean’s density structure. Freshwater accumulation and distribution in the Arctic Ocean have varied significantly in recent decades and certainly in the Beaufort Gyre (BG). In this study, we analyze salinity variations in the BG region between 2012 and 2017. We use in situ salinity observations from the Seasonal Ice Zone Reconnaissance Surveys (SIZRS), CTD casts from the Beaufort Gyre Exploration Project (BGP), and the EN4 data to validate and compare with satellite observations from Soil Moisture Active Passive (SMAP), Soil Moisture and Ocean Salinity (SMOS), and Aquarius Optimally Interpolated Sea Surface Salinity (OISSS), and Arctic Ocean models: ECCO, MIZMAS, HYCOM, ORAS5, and GLORYS12. Overall, satellite observations are restricted to ice-free regions in the BG area, and models tend to overestimate sea surface salinity (SSS). Freshwater Content (FWC), an important component of the BG, is computed for EN4 and most models. ORAS5 provides the strongest positive SSS correlation coefficient (0.612) and lowest bias to in situ observations compared to the other products. ORAS5 subsurface salinity and FWC compare well with the EN4 data. Discrepancies between models and SIZRS data are highest in GLORYS12 and ECCO. These comparisons identify dissimilarities between salinity products and extend challenges to observations applicable to other areas of the Arctic Ocean.

scholarly journals The AQUI Soil Moisture Network for Satellite Microwave Remote Sensing Validation in South-Western France

2018 ◽  
Vol 10 (11) ◽  
pp. 1839 ◽  
Author(s):  
A. Al-Yaari ◽  
S. Dayau ◽  
C. Chipeaux ◽  
C. Aluome ◽  
A. Kruszewski ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Agricultural Research ◽  
Pearson Correlation ◽  
European Space Agency ◽  
Microwave Remote Sensing ◽  
Climate Conditions ◽  
Space Agency ◽  
Satellite Microwave

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.

scholarly journals Linking Remote Sensing and Geodiversity and Their Traits Relevant to Biodiversity—Part I: Soil Characteristics

2019 ◽  
Vol 11 (20) ◽  
pp. 2356 ◽  
Author(s):  
Angela Lausch ◽  
Jussi Baade ◽  
Lutz Bannehr ◽  
Erik Borg ◽  
Jan Bumberger ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Cost Effective ◽  
Global Scale ◽  
Soil Characteristics ◽  
Monitoring Methods ◽  
In Situ Techniques ◽  
The Face ◽  
Remote Sensing Techniques

In the face of rapid global change it is imperative to preserve geodiversity for the overall conservation of biodiversity. Geodiversity is important for understanding complex biogeochemical and physical processes and is directly and indirectly linked to biodiversity on all scales of ecosystem organization. Despite the great importance of geodiversity, there is a lack of suitable monitoring methods. Compared to conventional in-situ techniques, remote sensing (RS) techniques provide a pathway towards cost-effective, increasingly more available, comprehensive, and repeatable, as well as standardized monitoring of continuous geodiversity on the local to global scale. This paper gives an overview of the state-of-the-art approaches for monitoring soil characteristics and soil moisture with unmanned aerial vehicles (UAV) and air- and spaceborne remote sensing techniques. Initially, the definitions for geodiversity along with its five essential characteristics are provided, with an explanation for the latter. Then, the approaches of spectral traits (ST) and spectral trait variations (STV) to record geodiversity using RS are defined. LiDAR (light detection and ranging), thermal and microwave sensors, multispectral, and hyperspectral RS technologies to monitor soil characteristics and soil moisture are also presented. Furthermore, the paper discusses current and future satellite-borne sensors and missions as well as existing data products. Due to the prospects and limitations of the characteristics of different RS sensors, only specific geotraits and geodiversity characteristics can be recorded. The paper provides an overview of those geotraits.

Linking tree rings with satellite observations of soil moisture: toward the reconstruction of water availability in the Mediterranean Andes region

2020 ◽  
Author(s):  
Alvaro Gonzalez-Reyes ◽  
Duncan Christie ◽  
Carlos LeQuesne ◽  
Moises Rojas-Badilla ◽  
Tomas Muñoz ◽  
...  
Keyword(s):  
Soil Moisture ◽  
South America ◽  
Tree Growth ◽  
Surface Soil ◽  
Satellite Observations ◽  
Last Millennium ◽  
Surface Soil Moisture ◽  
The Mediterranean ◽  
Soil Moisture Variability

&lt;p&gt;Soil moisture is a key variable into the earth surface dynamics, however long-term in situ measurements are globally scarce. In the Mediterranean Andes of Chile (30&amp;#176; - 37&amp;#176;S) grow the long-lived conifer &amp;#8220;Cipr&amp;#233;s de la Cordillera&amp;#8221; (Austrocedrus chilensis), which is a demonstrated hydroclimatic proxy capable to cover the last millennium. Previous paleoclimatic studies have documented a high sensitivity between tree species and several&amp;#160;hydroclimatic variables such as precipitation, streamflow, snowpack and aridity indexes, but the lack of in situ soil moisture observations has precluded an assessment of the spatial growth responses to high-resolution soil moisture variability. Here, we use three A. chilensis&amp;#160;chronologies to determine linkages with the satellite-based surface soil moisture product v04.5 generated by ESA. We found significant relationships between tree-growth an a soil moisture field across the 32&amp;#176; - 34&amp;#176;S spatial domain of western South America from January to September during 1985 &amp;#8211; 2013 period (r = 0.65; P &lt; 0.001).&amp;#160;Temporal relationships between tree-growth and soil moisture satellite observations exhibit a significant spectral coherence associated to cycles around 7 years (P &lt; 0.10) and a clear decadal variability. Based on our preliminary results and the present extensive network of A.&amp;#160;chilensis&amp;#160;tree-ring chronologies, this species appears as a promising proxy to reconstruct surface soil moisture variability derived from remote sensing over the last millennium in a topographically complex Andean region of South America.&lt;/p&gt;&lt;p&gt;Acknowledgements&lt;/p&gt;&lt;p&gt;Alvaro&amp;#160;Gonzalez-Reyes wish&amp;#160;to&amp;#160;thank: CONICYT+PAI+CONVOCATORIA NACIONAL SUBVENCI&amp;#211;N A INSTALACI&amp;#211;N EN LA ACADEMIA CONVOCATORIA A&amp;#209;O 2019 + PAI77190101&lt;/p&gt;

scholarly journals Evaluation of MERRA Land Surface Estimates in Preparation for the Soil Moisture Active Passive Mission

2011 ◽  
Vol 24 (15) ◽  
pp. 3797-3816 ◽  
Author(s):  
Yonghong Yi ◽  
John S. Kimball ◽  
Lucas A. Jones ◽  
Rolf H. Reichle ◽  
Kyle C. McDonald
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Surface Soil ◽  
Middle Latitude ◽  
Surface Soil Moisture ◽  
Freeze Thaw ◽  
Earth Observing System ◽  
In Situ Observations ◽  
Satellite Microwave

Abstract The authors evaluated several land surface variables from the Modern-Era Retrospective Analysis for Research and Applications (MERRA) product that are important for global ecological and hydrological studies, including daily maximum (Tmax) and minimum (Tmin) surface air temperatures, atmosphere vapor pressure deficit (VPD), incident solar radiation (SWrad), and surface soil moisture. The MERRA results were evaluated against in situ measurements, similar global products derived from satellite microwave [the Advanced Microwave Scanning Radiometer for Earth Observing System (EOS) (AMSR-E)] remote sensing and earlier generation atmospheric analysis [Goddard Earth Observing System version 4 (GEOS-4)] products. Relative to GEOS-4, MERRA is generally warmer (~0.5°C for Tmin and Tmax) and drier (~50 Pa for VPD) for low- and middle-latitude regions (&lt;50°N) associated with reduced cloudiness and increased SWrad. MERRA and AMSR-E temperatures show relatively large differences (&gt;3°C) in mountainous areas, tropical forest, and desert regions. Surface soil moisture estimates from MERRA (0–2-cm depth) and two AMSR-E products (~0–1-cm depth) are moderately correlated (R ~ 0.4) for middle-latitude regions with low to moderate vegetation biomass. The MERRA derived surface soil moisture also corresponds favorably with in situ observations (R = 0.53 ± 0.01, p &lt; 0.001) in the midlatitudes, where its accuracy is directly proportional to the quality of MERRA precipitation. In the high latitudes, MERRA shows inconsistent soil moisture seasonal dynamics relative to in situ observations. The study’s results suggest that satellite microwave remote sensing may contribute to improved reanalysis accuracy where surface meteorological observations are sparse and in cold land regions subject to seasonal freeze–thaw transitions. The upcoming NASA Soil Moisture Active Passive (SMAP) mission is expected to improve MERRA-type reanalysis accuracy by providing accurate global mapping of freeze–thaw state and surface soil moisture with 2–3-day temporal fidelity and enhanced (≤9 km) spatial resolution.

scholarly journals Assessment of the Temperature Effects in SMAP Satellite Soil Moisture Products in Oklahoma

2021 ◽  
Vol 13 (20) ◽  
pp. 4104
Author(s):  
Kim Oanh Hoang ◽  
Minjiao Lu
Keyword(s):  
Dielectric Constant ◽  
Soil Moisture ◽  
Brightness Temperature ◽  
Temperature Effects ◽  
The United States ◽  
Satellite Observations ◽  
Soil Moisture Data ◽  
Spatial Coverage ◽  
The Impact

Soil moisture is a notably important component in various studies in water sciences, including hydrology, agriculture, and water management. To achieve extensive or global spatial coverage, satellites focusing on soil moisture observation have been launched, and many satellite products, such as SMAP and SMOS soil moisture products, have been provided. Most of these satellite observations are based on the dielectric properties of wet soil, and most soil moisture retrieval algorithms are calibrated or evaluated using in situ soil moisture. While the in situ data observed by dielectric sensors, which are the most widely used, are reported to include errors caused by the so-called “temperature effects” of these sensors, the temperature dependency of bulk soil dielectric constant has rarely been discussed on satellite data. Since both in situ dielectric measurements and satellite observations are based on the same physical variable, the dielectric constant and the dielectrically measured in situ soil moisture data are also used as ground truth, it is necessary to assess the impact of temperature effects on satellite products. In this work, we attempted to identify the existence of the temperature effects and evaluate the consequences of removing these effects on in situ and satellite soil moisture and the relationships between the brightness temperature at the soil surface and the brightness temperature provided by satellite observation. To achieve the goals of this study, we analyzed the temperature effects on surface soil moisture data provided by a SMAP mission in Oklahoma, the United States. The results show that temperature effects exist in SMAP soil moisture products in Oklahoma, and the removal of these effects will potentially improve the accuracy of these products.

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