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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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 |
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