Evaluation of gridded soil moisture products over varied land covers, climates, and soil textures using in situ measurements: A case study of Lake Urmia Basin

Saeedi, Mohammad; Sharafati, Ahmad; Tavakol, Ameneh

doi:10.1007/s00704-021-03678-x

Cited by 9 publications

(2 citation statements)

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“…Within the scope of the CYGNSS constellation and to meet the requirement of data quality control, a total of 1824 stations are quali ed and used for evalidation. Since the collected raw data set was not experience the quality control processing, the measured SSM time series may include some outlies caused by the instrument abnormality, the preprocessing approach in (Saeedi et al 2021) is utilized using the median absolute deviation (MAD) to remove the outliers to improve the quality of in-situ measurements:…”

Section: Soil Sparse Networkmentioning

confidence: 99%

“…Continuous collection of large-scale and long-term soil moisture data is essential for geoscience research and agricultural production (Vreugdenhil et al 2022). Geoscientists are particularly interested in soil moisture remote sensing using active and passive microwave sensors since theoretical and validation experiments have demonstrated that L-band microwaves, which are sensitive to soil moisture changes, less vulnerable to vegetation, and unaffected by clouds and rain, are optimal for land surface soil moisture (SSM) remote sensing (Saeedi et al 2021).…”

Section: Introductionmentioning

confidence: 99%

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Validation of CYGNSS soil moisture products using in-situ measurments: A case study of Southern China

Dong

Jin

et al. 2023

Preprint

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In terrestrial remote sensing applications, the spaceborne Global Navigation Satellite System-Reflectometry (GNSS-R) has demonstrated its worth. The application to land surface soil moisture (SSM) detection is particularly intriguing since it has the ability to provide fine-scale results to supplement traditional satellite-based active and passive missions. To date, many retrieval algorithms for spaceborne GNSS-R have been developed in order to produce SSM products. However, detailed product reliability and robustness evaluations are still absent. In this study, the satellite-based microwave radiometry product, the model-base product, and in-situ measurements from the Chinese soil moisture monitoring network with over 1800 ground stations during the year 2018 were used to evaluate the CYclone Global Navigation Satellite System (CYGNSS) mission Level-3 SSM products released by the University Corporation for Atmospheric Research (UCAR) and the University of Colorado at Boulder (CU). Typical relative skill metrics and triple collocation-based metrics, along with corresponding confidence intervals, are given to analyze the performance. According to the pixel-by-pixel validation and overall statistical findings, the results reveal that the current CYGNSS-based SSM exhibits low performance in southern China when compared to the radiometry-based data with a low R2 (median R2=0.09) and the ubRMSD 0.055 cm3cm-3, which is poorer than the results from SMAP against in-situ measurements (median R2=0.25, ubRMSD=0.046 cm3cm-3). To acquire better results to support the related operational applications in the future, the new enhanced retrieval algorithms and high-accuracy calibration referenced data must be used.

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Section: Soil Sparse Networkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%