Next Article in Journal
Preliminary Results from a Wildfire Detection System Using Deep Learning on Remote Camera Images
Previous Article in Journal
Analysis of Ice Storm Impact on and Post-Disaster Recovery of Typical Subtropical Forests in Southeast China
Open AccessArticle

SHAtropE—A Regional Gridded ZTD Model for China and the Surrounding Areas

1
Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai 200030, China
2
School of Astronomy and Space Science, University of Chinese Academy of Sciences, Beijing 100049, China
3
Shanghai Key Laboratory of Space Navigation and Positioning Techniques, Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai 200030, China
4
College of Surveying and Geo-Informatics, Tong Ji University, Shanghai 200092, China
5
College of Marine Technology, Tokyo University of Marine Science and Technology, Tokyo 1358533, Japan
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(1), 165; https://doi.org/10.3390/rs12010165
Received: 20 November 2019 / Revised: 24 December 2019 / Accepted: 30 December 2019 / Published: 2 January 2020
A regional zenith tropospheric delay (ZTD) empirical model, referred to as SHAtropE (SHanghai Astronomical observatory tropospheric delay model—Extended), is developed and provides tropospheric propagation delay corrections for users in China and the surrounding areas with improved accuracy. The SHAtropE model was developed based on the ZTD time series of the continuous GNSS sites from the Crustal Movement Observation Network of China (CMONOC) and GNSS sites of surrounding areas. It combines the exponential and periodical functions and is provided as regional grids with a resolution of 2.5° × 2.0° in longitude and latitude. At each grid point, the exponential function converts the ZTD from the site height to the ellipsoid, and the periodical terms, including both annual and semi-annual periods, describe ZTD’s temporal variation. Moreover, SHAtropE also provides the predicted ZTD uncertainty, which is valuable in Precise Point Positioning (PPP) with ZTD being constrained for faster convergence. The data of 310 GNSS sites over 7 years were used to validate the new model. Results show that the SHAtropE ZTD has an accuracy of 3.5 cm in root mean square (RMS) quantity, which has a mean improvement of 35.2% and 5.4% over the UNB3m (5.4 cm) and GPT3 (3.7 cm) models, respectively. The predicted uncertainty of SHAtropE ZTD shows seasonal variations, where the values are larger in summer than in winter. By applying the SHAtropE model in the static PPP, the convergence time of GPS-only and BDS-only solutions are reduced by 8.1% and 14.5% respectively compared to the UNB3m model, and the reductions are 6.9% and 11.2% respectively for the GPT3 model. As no meteorological data are required for the implementation of the model, the SHAtropE could thus be a refined tropospheric model for GNSS users in mainland China and the surrounding areas. The method of modeling the ZTD uncertainty can also be used in further global tropospheric delay modeling. View Full-Text
Keywords: GNSS; tropospheric modeling; SHAtropE; precise point positioning GNSS; tropospheric modeling; SHAtropE; precise point positioning
Show Figures

Graphical abstract

MDPI and ACS Style

Chen, J.; Wang, J.; Wang, A.; Ding, J.; Zhang, Y. SHAtropE—A Regional Gridded ZTD Model for China and the Surrounding Areas. Remote Sens. 2020, 12, 165.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop