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RSS FeedsRemote Sensing, Vol. 11, Pages 679: Prospects for Imaging Terrestrial Water Storage in South America Using Daily GPS Observations (Remote Sensing)

 
 

21 march 2019 12:05:00

 
Remote Sensing, Vol. 11, Pages 679: Prospects for Imaging Terrestrial Water Storage in South America Using Daily GPS Observations (Remote Sensing)
 




Few studies have used crustal displacements sensed by the Global Positioning System (GPS) to assess the terrestrial water storage (TWS), which causes loadings. Furthermore, no study has investigated the feasibility of using GPS to image TWS over South America (SA), which contains the world’s driest (Atacama Desert) and wettest (Amazon Basin) regions. This work presents a resolution analysis of an inversion of GPS data over SA. Firstly, synthetic experiments were used to verify the spatial resolutions of GPS-imaged TWS and examine the resolving accuracies of the inversion based on checkerboard tests and closed-loop simulations using “TWS” from the Noah-driven Global Land Data Assimilation System (GLDAS-Noah). Secondly, observed radial displacements were used to image daily TWS. The inverted results of TWS at a resolution of 300 km present negligible errors, as shown by synthetic experiments involving 397 GPS stations across SA. However, as a result of missing daily observations, the actual daily number of available stations varied from 60–353, and only 6% of the daily GPS-imaged TWS agree with GLDAS-Noah TWS, which indicates a root-mean-squared error (RMSE) of less than 100 kg/m 2 . Nevertheless, the inversion shows agreement that is better than 0.50 and 61.58 kg/m 2 in terms of the correlation coefficient (Pearson) and RMSE, respectively, albeit at each GPS site.


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24 viewsCategory: Geology, Physics
 
Remote Sensing, Vol. 11, Pages 678: An SRTM-Aided Epipolar Resampling Method for Multi-Source High-Resolution Satellite Stereo Observation (Remote Sensing)
Remote Sensing, Vol. 11, Pages 685: Shallow-Water Habitat Mapping using Underwater Hyperspectral Imaging from an Unmanned Surface Vehicle: A Pilot Study (Remote Sensing)
 
 
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