Evaluation of Satellite-Based Soil Moisture Products over Four Different Continental In-Situ Measurements

Global, near-real-time satellite-based soil moisture (SM) datasets have been developed over recent decades. However, there has been a lack of comparison among different passing times, retrieving algorithms, and sensors between SM products over various regions. In this study, we assessed seven types...

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Main Authors: Yangxiaoyue Liu, Yaping Yang, Xiafang Yue
Format: Article
Language:English
Published: MDPI AG 2018-07-01
Series:Remote Sensing
Subjects:
ECV
Online Access:http://www.mdpi.com/2072-4292/10/7/1161
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spelling doaj-ccd94523e8714ae3990570b8abefd3ad2020-11-25T00:04:12ZengMDPI AGRemote Sensing2072-42922018-07-01107116110.3390/rs10071161rs10071161Evaluation of Satellite-Based Soil Moisture Products over Four Different Continental In-Situ MeasurementsYangxiaoyue Liu0Yaping Yang1Xiafang Yue2State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaGlobal, near-real-time satellite-based soil moisture (SM) datasets have been developed over recent decades. However, there has been a lack of comparison among different passing times, retrieving algorithms, and sensors between SM products over various regions. In this study, we assessed seven types of SM products (AMSR_A, AMSR_D, ECV_A, ECV_C, ECV_P, SMOS_A, and SMOS_D) over four different continental in-situ networks in North America, the Tibetan Plateau, Western Europe, and Southeastern Australia. Bias, R, root mean square error (RMSE), unbiased root mean square difference (ubRMSD), anomalies, and anomalies R were calculated to explore the agreement between satellite-based SM and in-situ measurements. Taylor diagrams were drawn for an inter-comparison. The results showed that (1) ECV_C was superior both in characterizing the SM temporal variation tendency and absolute value, while ECV_A produced numerous abnormal values over all validation regions. ECV_P was able to basically express the SM variation tendency, except for a few overestimations and underestimations. (2) The ascending data (AMSR_A, SMOS_A) generally outperformed the corresponding descending data (AMSR_D, SMOS_D). (3) AMSR exceeded SMOS in terms of the coefficient of correlation. (4) The validation result of SMOS_D over the NAN and OZN networks was unsatisfactory, with a rather poor correlation for both original data and anomalies.http://www.mdpi.com/2072-4292/10/7/1161satellite-based soil moisturein-situ measurementsAMSRSMOSECVevaluation
collection DOAJ
language English
format Article
sources DOAJ
author Yangxiaoyue Liu
Yaping Yang
Xiafang Yue
spellingShingle Yangxiaoyue Liu
Yaping Yang
Xiafang Yue
Evaluation of Satellite-Based Soil Moisture Products over Four Different Continental In-Situ Measurements
Remote Sensing
satellite-based soil moisture
in-situ measurements
AMSR
SMOS
ECV
evaluation
author_facet Yangxiaoyue Liu
Yaping Yang
Xiafang Yue
author_sort Yangxiaoyue Liu
title Evaluation of Satellite-Based Soil Moisture Products over Four Different Continental In-Situ Measurements
title_short Evaluation of Satellite-Based Soil Moisture Products over Four Different Continental In-Situ Measurements
title_full Evaluation of Satellite-Based Soil Moisture Products over Four Different Continental In-Situ Measurements
title_fullStr Evaluation of Satellite-Based Soil Moisture Products over Four Different Continental In-Situ Measurements
title_full_unstemmed Evaluation of Satellite-Based Soil Moisture Products over Four Different Continental In-Situ Measurements
title_sort evaluation of satellite-based soil moisture products over four different continental in-situ measurements
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2018-07-01
description Global, near-real-time satellite-based soil moisture (SM) datasets have been developed over recent decades. However, there has been a lack of comparison among different passing times, retrieving algorithms, and sensors between SM products over various regions. In this study, we assessed seven types of SM products (AMSR_A, AMSR_D, ECV_A, ECV_C, ECV_P, SMOS_A, and SMOS_D) over four different continental in-situ networks in North America, the Tibetan Plateau, Western Europe, and Southeastern Australia. Bias, R, root mean square error (RMSE), unbiased root mean square difference (ubRMSD), anomalies, and anomalies R were calculated to explore the agreement between satellite-based SM and in-situ measurements. Taylor diagrams were drawn for an inter-comparison. The results showed that (1) ECV_C was superior both in characterizing the SM temporal variation tendency and absolute value, while ECV_A produced numerous abnormal values over all validation regions. ECV_P was able to basically express the SM variation tendency, except for a few overestimations and underestimations. (2) The ascending data (AMSR_A, SMOS_A) generally outperformed the corresponding descending data (AMSR_D, SMOS_D). (3) AMSR exceeded SMOS in terms of the coefficient of correlation. (4) The validation result of SMOS_D over the NAN and OZN networks was unsatisfactory, with a rather poor correlation for both original data and anomalies.
topic satellite-based soil moisture
in-situ measurements
AMSR
SMOS
ECV
evaluation
url http://www.mdpi.com/2072-4292/10/7/1161
work_keys_str_mv AT yangxiaoyueliu evaluationofsatellitebasedsoilmoistureproductsoverfourdifferentcontinentalinsitumeasurements
AT yapingyang evaluationofsatellitebasedsoilmoistureproductsoverfourdifferentcontinentalinsitumeasurements
AT xiafangyue evaluationofsatellitebasedsoilmoistureproductsoverfourdifferentcontinentalinsitumeasurements
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