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RSS FeedsRemote Sensing, Vol. 12, Pages 751: Analysis of the Potential Contributors to Common Mode Error in Chuandian Region of China (Remote Sensing)

 
 

25 february 2020 19:03:36

 
Remote Sensing, Vol. 12, Pages 751: Analysis of the Potential Contributors to Common Mode Error in Chuandian Region of China (Remote Sensing)
 


Common mode error (CME) in Chuandian region of China is derived from 6-year continuous GPS time series and is identified by principal component analysis (PCA) method. It is revealed that the temporal behavior of the CME is not purely random, and contains unmodeled signals such as nonseasonal mass loadings. Its spatial distribution is quite uniform for all GPS sites in the region, and the first principal component, uniformly distributed in the region, has a spatial response of more than 70%. To further explore the potential contributors of CME, daily atmospheric mass loading and soil moisture mass loading effects are evaluated. Our results show that ~15% of CME can be explained by these daily surface mass loadings. The power spectral analysis is used to assess the CME. After removing atmospheric and soil moisture loadings from the CME, the power of the CME reduces in a wide range of frequencies. We also investigate the contribution of CME in GPS filtered residuals time series and it shows the Root Mean Squares (RMSs) of GPS time series are reduced by applying of the mass loading corrections in CME. These comparison results demonstrate that daily atmosphere pressure and the soil moisture mass loadings are a part of contributors to the CME in Chuandian region of China.


 
172 viewsCategory: Geology, Physics
 
Remote Sensing, Vol. 12, Pages 752: Landslides Information Extraction Using Object-Oriented Image Analysis Paradigm Based on Deep Learning and Transfer Learning (Remote Sensing)
Remote Sensing, Vol. 12, Pages 750: Identifying the Contributions of Multi-Source Data for Winter Wheat Yield Prediction in China (Remote Sensing)
 
 
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