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Soil Moisture Retrieval Using GNSS-IR Based on Empirical Modal Decomposition and Cross-Correlation Satellite Selection.

Authors :
Ding, Qin
Liang, Yueji
Liang, Xingyong
Ren, Chao
Yan, Hongbo
Liu, Yintao
Zhang, Yan
Lu, Xianjian
Lai, Jianmin
Hu, Xinmiao
Source :
Remote Sensing; Jul2023, Vol. 15 Issue 13, p3218, 20p
Publication Year :
2023

Abstract

Global Navigation Satellite System interferometric reflectometry (GNSS-IR), as a new remote sensing detection technology, can retrieve surface soil moisture (SM) by separating the modulation terms from the effective signal-to-noise ratio (SNR) data. However, traditional low-order polynomials are prone to over-fitting when separating modulation terms. Moreover, the existing research mainly relies on prior information to select satellites for SM retrieval. Accordingly, this study proposes a method based on empirical modal decomposition (EMD) and cross-correlation satellite selection (CCSS) for SM retrieval. This method intended to adaptively separate the modulation terms of SNR through the combination of EMD and an intrinsic mode functions (IMF) discriminant method, then construct a CCSS method to select available satellites, and finally establish a multisatellite robust estimation regression (MRER) model to retrieve SM. The results indicated that with EMD, the different feature components implied in the SNR data of different satellites could be adaptively decomposed, and the trend and modulation terms of the SNR could more accurately be acquired by the IMF discriminant method. The available satellites could be efficiently selected through CCSS, and the SNR quality of different satellites could also be classified at different accuracy levels. Furthermore, MRER could fuse the multisatellite phases well, which enhanced the accuracy of SM retrieval and further verified the feasibility and effectiveness of combining EMD and CCSS. When r m = 0.600 and r n = 0.700 , the correlation coefficient (r) of the multisatellite combination reached 0.918, an improvement of at least 40% relative to the correlation coefficient of a single satellite. Therefore, this method can improve the adaptive ability of SNR decomposition, and the selection of satellites has high flexibility, which is helpful for the application and popularization of the GNSS-IR technology. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20724292
Volume :
15
Issue :
13
Database :
Complementary Index
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
164922131
Full Text :
https://doi.org/10.3390/rs15133218