Updated GNSS velocity solution in the Nordic and Baltic countries with a semi-automatic offset detection method

Sonja Lahtinen*, Lotti Jivall, Pasi Häkli, Maaria Nordman

*Tämän työn vastaava kirjoittaja

Tutkimustuotos: LehtiartikkeliArticleScientificvertaisarvioitu

6 Lataukset (Pure)

Abstrakti

In Fennoscandia, the Glacial Isostatic Adjustment (GIA) causes intraplate deformations that affect the national static reference frames. The GNSS-determined velocities are important data for constraining the GIA models, which are necessary for maintaining the national reference frames. The Nordic Geodetic Commission (NKG) has published a dense and consistent GNSS station velocity solution in 2019, and we present now an update of the solution covering additional 3.5 years of data. Undetected positional offsets are the main factor decreasing the accuracy of the velocity estimates. We developed a method for the semi-automatic offset detection to improve the quality of our solution. The results show that we could correctly detect 74% of the manually determined offsets, and the undetected offsets would have caused a median 0.1 mm/y bias in trend. The method pointed out some otherwise unnoticed offsets and will decrease the need for manual analysis in the future. The updated velocity solution especially improves the velocity estimates of the newly established stations and the quality of the velocity estimates in Baltic countries. The formal uncertainties estimated using the power-law plus white noise model were at a median of 0.06 and 0.15 mm/y for horizontal and vertical velocities, respectively. However, we concluded that the systematic velocity uncertainties due to the reference frame alignment were approximately at the same level.

AlkuperäiskieliEnglanti
Artikkeli9
Sivumäärä12
JulkaisuGPS SOLUTIONS
Vuosikerta26
Numero1
DOI - pysyväislinkit
TilaJulkaistu - tammikuuta 2022
OKM-julkaisutyyppiA1 Julkaistu artikkeli, soviteltu

Sormenjälki

Sukella tutkimusaiheisiin 'Updated GNSS velocity solution in the Nordic and Baltic countries with a semi-automatic offset detection method'. Ne muodostavat yhdessä ainutlaatuisen sormenjäljen.

Siteeraa tätä