Results 141 to 150 of about 1,086,410 (154)

Global, Spatially Explicit Modelling of Zenith Wet Delay With XGBoost

Journal of Geodesy
Radio signals transmitted by Global Navigation Satellite System (GNSS) satellites experience tropospheric delays. While the hydrostatic part, referred to as zenith hydrostatic delay (ZHD) when mapped to the zenith direction, can be analytically modelled ...
Matthias Schartner, Florian Zus, Linda See   +2 more
exaly   +3 more sources

Modeling Tropospheric Zenith Wet Delays in the Chinese Mainland Based on Machine Learning

GPS Solutions, 2023
In this study, the tropospheric zenith wet delay (ZWD) modeling was realized based on the regression analysis of 7 years (2013–2019) of radiosonde data at 182 sites in the Chinese mainland and the surroundings through two machine learning (ML) approaches
Linguo Yuan, Qinzheng Li, Zhongshan Jiang   +2 more
exaly   +2 more sources

Forecasting Rainfall Events Based on Zenith Wet Delay Time Series Utilizing eXtreme Gradient Boosting (XGBoost)

Advances in Space Research
Accurate rainfall prediction is vital for mitigating flood and storm disasters as well as for planning agricultural activities and water resources management.
Saeed Farzaneh, Ehsan Forootan, Masoud Dehvari   +2 more
exaly   +2 more sources

Global Zenith Wet Delay Modeling With Surface Meteorological Data and Machine Learning

GPS Solutions
The tropospheric delay is a major error source for space geodetic techniques, and the performance of its modeling is significantly limited due to the high spatiotemporal variability of the moisture in the lower atmosphere.
Johannes Bohm, Robert Weber
exaly   +2 more sources

Impact of GPS Antenna Phase Center Models on Zenith Wet Delay and Tropospheric Gradients

GPS Solutions, 2019
peer reviewedWe demonstrate the potential for the Global Positioning System (GPS) to provide highly accurate tropospheric products for use in meteorological applications.
Addisu Hunegnaw, Félicia Norma Rebecca TEFERLE, Yohannes Getachew Ejigu   +2 more
exaly   +2 more sources

A Hybrid Deep Learning Algorithm for Tropospheric Zenith Wet Delay Modeling With the Spatiotemporal Variation Considered

Atmosphere
The tropospheric Zenith Wet Delay (ZWD) is one of the primary sources of error in Global Navigation Satellite Systems (GNSS). Precise ZWD modeling is essential for GNSS positioning and Precipitable Water Vapor (PWV) retrieval.
Lu Huang, Su Tian
exaly   +2 more sources

Statistical Significance of Trends in Zenith Wet Delay From Re-Processed GPS Solutions [PDF]

GPS Solutions, 2018
peer reviewedLong series of Zenith Wet Delay (ZWD) obtained as part of a homogeneous re-processing of Global Positioning System solutions constitute a reliable set of data to be assimilated into climate models. The correct stochastic properties, i.e. the
Anna Klos, Janusz Bogusz, Addisu Hunegnaw   +2 more
exaly   +2 more sources

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Establishing Zenith Wet Delay model (ZWD) and developing a framework for generating high resolution PWV for extreme weather monitoring using MT-InSAR and GNSS for Indian Himalayan region 

Precipitable water vapor (PWV), an essential climate variable enlisted by the Global Climate Observing System (GCOS), can be efficiently mapped using popular Earth Observation techniques like Global Navigation Satellite System (GNSS) and Interferometric Synthetic Aperture Radar (InSAR). When used in a combination, these techniques complement each other
shivika saxena, chandrakanta ojha, ramji dwivedi   +2 more
openaire   +1 more source

Developing a New Combined Model of Zenith Wet Delay by Using Neural Network

Advances in Space Research, 2022
Maohua Ding
exaly  

Tibetan Zenith Wet Delay Model With Refined Vertical Correction

Journal of Geodesy, 2023
Chaoqian Xu, Yibin Yao, Chen Liu
exaly