Multitemporal Soil Moisture Retrieval over Bare Agricultural Areas by Means of Alpha Model with Multisensor SAR Data

The objective of this research is to optimize the Alpha approximation model for soil moisture retrieval using multitemporal SAR data. The Alpha model requires prior knowledge of soil moisture range to constrain soil moisture estimation. The solution of the Alpha model is an undetermined problem due...

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Main Authors: Xiang Zhang, Xinming Tang, Xiaoming Gao, Hui Zhao
Format: Article
Language:English
Published: Hindawi Limited 2018-01-01
Series:Advances in Meteorology
Online Access:http://dx.doi.org/10.1155/2018/7914581
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spelling doaj-2763f712b1084c5bab887a6a7404d6b92020-11-25T00:59:18ZengHindawi LimitedAdvances in Meteorology1687-93091687-93172018-01-01201810.1155/2018/79145817914581Multitemporal Soil Moisture Retrieval over Bare Agricultural Areas by Means of Alpha Model with Multisensor SAR DataXiang Zhang0Xinming Tang1Xiaoming Gao2Hui Zhao3Satellite Surveying and Mapping Application Center, National Administration of Surveying, Mapping and Geo-information, Beijing 100048, ChinaSatellite Surveying and Mapping Application Center, National Administration of Surveying, Mapping and Geo-information, Beijing 100048, ChinaSatellite Surveying and Mapping Application Center, National Administration of Surveying, Mapping and Geo-information, Beijing 100048, ChinaNational Geomatics Center of China, Beijing 100080, ChinaThe objective of this research is to optimize the Alpha approximation model for soil moisture retrieval using multitemporal SAR data. The Alpha model requires prior knowledge of soil moisture range to constrain soil moisture estimation. The solution of the Alpha model is an undetermined problem due to the fact that the number of observation equations is less than the number of unknown parameters. This research primarily focused on the optimization of Alpha model by employing multisensor and multitemporal SAR data. The disadvantage of the Alpha model can be eliminated by the combination of multisensor SAR data. The optimized Alpha model was evaluated on the basis of a comprehensive campaign for soil moisture retrieval, which acquired multisensor time series SAR data and coincident field measurements. The agreement between the estimated and measured soil moisture was within a root mean square error of 0.08 cm3/cm3 for both methods. The optimized Alpha model shows an obvious improvement for soil moisture retrieval. The results demonstrated that multisensor and multitemporal SAR data are favorable for time series soil moisture retrieval over bare agricultural areas.http://dx.doi.org/10.1155/2018/7914581
collection DOAJ
language English
format Article
sources DOAJ
author Xiang Zhang
Xinming Tang
Xiaoming Gao
Hui Zhao
spellingShingle Xiang Zhang
Xinming Tang
Xiaoming Gao
Hui Zhao
Multitemporal Soil Moisture Retrieval over Bare Agricultural Areas by Means of Alpha Model with Multisensor SAR Data
Advances in Meteorology
author_facet Xiang Zhang
Xinming Tang
Xiaoming Gao
Hui Zhao
author_sort Xiang Zhang
title Multitemporal Soil Moisture Retrieval over Bare Agricultural Areas by Means of Alpha Model with Multisensor SAR Data
title_short Multitemporal Soil Moisture Retrieval over Bare Agricultural Areas by Means of Alpha Model with Multisensor SAR Data
title_full Multitemporal Soil Moisture Retrieval over Bare Agricultural Areas by Means of Alpha Model with Multisensor SAR Data
title_fullStr Multitemporal Soil Moisture Retrieval over Bare Agricultural Areas by Means of Alpha Model with Multisensor SAR Data
title_full_unstemmed Multitemporal Soil Moisture Retrieval over Bare Agricultural Areas by Means of Alpha Model with Multisensor SAR Data
title_sort multitemporal soil moisture retrieval over bare agricultural areas by means of alpha model with multisensor sar data
publisher Hindawi Limited
series Advances in Meteorology
issn 1687-9309
1687-9317
publishDate 2018-01-01
description The objective of this research is to optimize the Alpha approximation model for soil moisture retrieval using multitemporal SAR data. The Alpha model requires prior knowledge of soil moisture range to constrain soil moisture estimation. The solution of the Alpha model is an undetermined problem due to the fact that the number of observation equations is less than the number of unknown parameters. This research primarily focused on the optimization of Alpha model by employing multisensor and multitemporal SAR data. The disadvantage of the Alpha model can be eliminated by the combination of multisensor SAR data. The optimized Alpha model was evaluated on the basis of a comprehensive campaign for soil moisture retrieval, which acquired multisensor time series SAR data and coincident field measurements. The agreement between the estimated and measured soil moisture was within a root mean square error of 0.08 cm3/cm3 for both methods. The optimized Alpha model shows an obvious improvement for soil moisture retrieval. The results demonstrated that multisensor and multitemporal SAR data are favorable for time series soil moisture retrieval over bare agricultural areas.
url http://dx.doi.org/10.1155/2018/7914581
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AT xinmingtang multitemporalsoilmoistureretrievaloverbareagriculturalareasbymeansofalphamodelwithmultisensorsardata
AT xiaominggao multitemporalsoilmoistureretrievaloverbareagriculturalareasbymeansofalphamodelwithmultisensorsardata
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