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Open AccessArticle

Evaluation of Remotely-Sensed and Model-Based Soil Moisture Products According to Different Soil Type, Vegetation Cover and Climate Regime Using Station-Based Observations over Turkey

1
Department of Civil Engineering, Middle East Technical University, Ankara 06800, Turkey
2
Hydrology and Remote Sensing Laboratory, USDA Agricultural Research Service, Beltsville Agricultural Research Center, Beltsville, MD 20705, USA
3
Turkish Directorate General of Meteorology, 6th Regional Directorate, Adana 01220, Turkey
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(16), 1875; https://doi.org/10.3390/rs11161875
Received: 1 July 2019 / Revised: 5 August 2019 / Accepted: 8 August 2019 / Published: 10 August 2019
This study evaluates the performance of widely-used remotely sensed- and model-based soil moisture products, including: The Advanced Scatterometer (ASCAT), the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E), the European Space Agency Climate Change Initiative (ESA-CCI), the Antecedent Precipitation Index (API), and the Global Land Data Assimilation System (GLDAS-NOAH). Evaluations are performed between 2008 and 2011 against the calibrated station-based soil moisture observations collected by the General Directorate of Meteorology of Turkey. The calibration of soil moisture observing sensors with respect to the soil type, correction of the soil moisture for the soil temperature, and the quality control of the collected measurements are performed prior to the evaluation of the products. Evaluation of remotely sensed- and model-based soil moisture products is performed considering different characteristics of the time series (i.e., seasonality and anomaly components) and the study region (i.e., soil type, vegetation cover, soil wetness and climate regime). The systematic bias between soil moisture products and in situ measurements is eliminated by using a linear rescaling method. Correlations between the soil moisture products and the in situ observations vary between 0.57 and 0.87, while the root mean square errors of the products versus the in situ observations vary between 0.028 and 0.043 m3 m−3. Overall, according to the correlation and root mean square error values obtained in all evaluation categories, NOAH and ESA-CCI soil moisture products perform better than all the other model- and remotely sensed-based soil moisture products. These results are valid for the entire study time period and all of the sub-categories under soil type, vegetation cover, soil wetness and climate regime. View Full-Text
Keywords: soil moisture; station-based measurements; sensor calibration; validation; inter-comparison soil moisture; station-based measurements; sensor calibration; validation; inter-comparison
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Bulut, B.; Yilmaz, M.T.; Afshar, M.H.; Şorman, A.Ü.; Yücel, İ.; Cosh, M.H.; Şimşek, O. Evaluation of Remotely-Sensed and Model-Based Soil Moisture Products According to Different Soil Type, Vegetation Cover and Climate Regime Using Station-Based Observations over Turkey. Remote Sens. 2019, 11, 1875.

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