Refinement of global gridded ray-traced Zenith tropospheric delay over Nigeria based on local GNSS network observations

Recent studies on the application of Zenith Tropospheric Delay (ZTD) in meteorology and geodesy have shown improved accuracy with the use of locally estimated ZTD compared to Global ZTD. This paper focuses on the refinement of global gridded ray-traced Vienna Mapping Functions 1 (VMF1) ZTD over Nige...

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Main Authors: Ifechukwu Ugochukwu Nzelibe, Timothy Oluwadare Idowu
Format: Article
Language:English
Published: Elsevier 2023-02-01
Series:Geosystems and Geoenvironment
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2772883822001121
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author Ifechukwu Ugochukwu Nzelibe
Timothy Oluwadare Idowu
author_facet Ifechukwu Ugochukwu Nzelibe
Timothy Oluwadare Idowu
author_sort Ifechukwu Ugochukwu Nzelibe
collection DOAJ
description Recent studies on the application of Zenith Tropospheric Delay (ZTD) in meteorology and geodesy have shown improved accuracy with the use of locally estimated ZTD compared to Global ZTD. This paper focuses on the refinement of global gridded ray-traced Vienna Mapping Functions 1 (VMF1) ZTD over Nigeria, using ZTD estimates derived from local GNSS Continuously Operating Reference Stations (CORS) observations. Three (3) years of GNSS observations collected at 13 CORS located within the study area were post-processed using GNSS Analysis and Processing Software (GAPS) to derive the local GNSS-ZTD estimates. The global VMF1-ZTD were interpolated at the locations of the local GNSS-CORS. An optimal deep structured supervised Neural Network (NN) was derived by training feedforward networks using the Levenberg-Marquardt backpropagation algorithm, with spatiotemporal variables and VMF1-ZTD as inputs and the GNSS-ZTD as the target. The outputs from the NN model were assessed using internal and external data. Results from internal data evaluations indicated a robust and accurate model output with optimum network performances indicating MSE of ∼7.22 × 10−6 m and ∼4.56 × 10−4 m for hydrostatic and wet ZTD networks respectively. The external data evaluations performed using the International GNSS Services (IGS) Zenith Path Delay (ZPD), indicated an RMSE range of ∼0.041 m to 0.095 m for global-VMF1 and ∼0.030 m to 0.037 m for the Local Refine (LR)-VMF1. The results suggest that the application of ZTD estimates derived from local GNSS observations in the refinement of global gridded VMF1-ZTD yields an improved accuracy over Nigeria. Consequently, the LR-VMF1 ZTD estimates are recommended for improved accuracy, required for geodetic and meteorological applications in and around Nigeria
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spelling doaj.art-0c7ee240823b4cd29f60982c2c9f79bd2023-01-07T04:17:54ZengElsevierGeosystems and Geoenvironment2772-88382023-02-0121100137Refinement of global gridded ray-traced Zenith tropospheric delay over Nigeria based on local GNSS network observationsIfechukwu Ugochukwu Nzelibe0Timothy Oluwadare Idowu1Corresponding author.; Department of Surveying and Geoinformatics, Federal University of Technology Akure, Ondo State, NigeriaDepartment of Surveying and Geoinformatics, Federal University of Technology Akure, Ondo State, NigeriaRecent studies on the application of Zenith Tropospheric Delay (ZTD) in meteorology and geodesy have shown improved accuracy with the use of locally estimated ZTD compared to Global ZTD. This paper focuses on the refinement of global gridded ray-traced Vienna Mapping Functions 1 (VMF1) ZTD over Nigeria, using ZTD estimates derived from local GNSS Continuously Operating Reference Stations (CORS) observations. Three (3) years of GNSS observations collected at 13 CORS located within the study area were post-processed using GNSS Analysis and Processing Software (GAPS) to derive the local GNSS-ZTD estimates. The global VMF1-ZTD were interpolated at the locations of the local GNSS-CORS. An optimal deep structured supervised Neural Network (NN) was derived by training feedforward networks using the Levenberg-Marquardt backpropagation algorithm, with spatiotemporal variables and VMF1-ZTD as inputs and the GNSS-ZTD as the target. The outputs from the NN model were assessed using internal and external data. Results from internal data evaluations indicated a robust and accurate model output with optimum network performances indicating MSE of ∼7.22 × 10−6 m and ∼4.56 × 10−4 m for hydrostatic and wet ZTD networks respectively. The external data evaluations performed using the International GNSS Services (IGS) Zenith Path Delay (ZPD), indicated an RMSE range of ∼0.041 m to 0.095 m for global-VMF1 and ∼0.030 m to 0.037 m for the Local Refine (LR)-VMF1. The results suggest that the application of ZTD estimates derived from local GNSS observations in the refinement of global gridded VMF1-ZTD yields an improved accuracy over Nigeria. Consequently, the LR-VMF1 ZTD estimates are recommended for improved accuracy, required for geodetic and meteorological applications in and around Nigeriahttp://www.sciencedirect.com/science/article/pii/S2772883822001121Artificial Neural Network (ANN)Global Navigation Satellite Systems (GNSS)ModellingNigeria GNSS Network (NIGNET)RefinementZenith Tropospheric Delay (ZTD)
spellingShingle Ifechukwu Ugochukwu Nzelibe
Timothy Oluwadare Idowu
Refinement of global gridded ray-traced Zenith tropospheric delay over Nigeria based on local GNSS network observations
Geosystems and Geoenvironment
Artificial Neural Network (ANN)
Global Navigation Satellite Systems (GNSS)
Modelling
Nigeria GNSS Network (NIGNET)
Refinement
Zenith Tropospheric Delay (ZTD)
title Refinement of global gridded ray-traced Zenith tropospheric delay over Nigeria based on local GNSS network observations
title_full Refinement of global gridded ray-traced Zenith tropospheric delay over Nigeria based on local GNSS network observations
title_fullStr Refinement of global gridded ray-traced Zenith tropospheric delay over Nigeria based on local GNSS network observations
title_full_unstemmed Refinement of global gridded ray-traced Zenith tropospheric delay over Nigeria based on local GNSS network observations
title_short Refinement of global gridded ray-traced Zenith tropospheric delay over Nigeria based on local GNSS network observations
title_sort refinement of global gridded ray traced zenith tropospheric delay over nigeria based on local gnss network observations
topic Artificial Neural Network (ANN)
Global Navigation Satellite Systems (GNSS)
Modelling
Nigeria GNSS Network (NIGNET)
Refinement
Zenith Tropospheric Delay (ZTD)
url http://www.sciencedirect.com/science/article/pii/S2772883822001121
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