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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Series: | Advances in Meteorology |
Online Access: | http://dx.doi.org/10.1155/2018/7914581 |
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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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