{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:49:52Z","timestamp":1760237392636,"version":"build-2065373602"},"reference-count":36,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2020,4,8]],"date-time":"2020-04-08T00:00:00Z","timestamp":1586304000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The ionosphere is one of the largest error sources in GNSS (Global Navigation Satellite Systems) applications and can cause up to several meters of error in positioning. Especially for single-frequency users, who cannot correct the ionospheric delay, the information about the state of the ionosphere is mandatory. Dual- and multi-frequency GNSS users, on the other hand, can correct the ionospheric effect on their observations by linear combination. However, real-time applications such as autonomous driving or precision farming, require external high accuracy corrections for fast convergence. Mostly, this external information is given in terms of grids or coefficients of the vertical total electron content (VTEC). Globally distributed GNSS stations of different networks, such as the network of the International GNSS Services (IGS), provide a large number of multi-frequency observations which can be used to determine the state of the ionosphere. These data are used to generate Global Ionosphere Maps (GIM). Due to the inhomogeneous global distribution of GNSS real-time stations and especially due to the large data gaps over oceanic areas, the global VTEC models are usually limited in their spatial and spectral resolution. Most of the GIMs are mathematically based on globally defined radial basis functions, i.e., spherical harmonics (SH), with a maximum degree of 15 and provided with a spatial resolution of      2.5 \u00b0  \u00d7  5 \u00b0      in latitude and longitude, respectively. Regional GNSS networks, however, offer dense clusters of observations, which can be used to generate regional VTEC solutions with a higher spectral resolution. In this study, we introduce a two-step model (TSM) comprising a global model as the first step and a regional model as the second step. We apply polynomial and trigonometric B-spline functions to represent the global VTEC. Polynomial B-splines are used for modelling the finer structures of VTEC within selected regions, i.e., the densification areas. The TSM provides both, a global and a regional VTEC map at the same time. In order to study the performance, we apply the developed approach to hourly data of the global IGS network as well as the EUREF network of the European region for St. Patrick storm in March 2015. For the assessment of the generated maps, we use the dSTEC analysis and compare both maps with different global and regional products from the IGS Ionosphere Associated Analysis Centers, e.g., the global product from CODE (Berne, Switzerland) and from UPC (Barcelona, Spain), as well as the regional maps from ROB (Brussels, Belgium). The assessment shows a significant improvement of the regional VTEC representation in the form of the generated TSM maps. Among all other products used for comparison, the developed regional one is of the highest accuracy within the selected time span. Since the numerical tests are performed using hourly data with a latency of one to two hours, the presented procedure is seen as an intermediate step for the generation of high precision regional real-time corrections for modern applications.<\/jats:p>","DOI":"10.3390\/rs12071198","type":"journal-article","created":{"date-parts":[[2020,4,9]],"date-time":"2020-04-09T03:40:19Z","timestamp":1586403619000},"page":"1198","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Global and Regional High-Resolution VTEC Modelling Using a Two-Step B-Spline Approach"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6780-268X","authenticated-orcid":false,"given":"Andreas","family":"Goss","sequence":"first","affiliation":[{"name":"Deutsches Geod\u00e4tisches Forschungsinstitut der Technischen Universit\u00e4t M\u00fcnchen, Arcisstra\u00dfe 21, 80333 Munich, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael","family":"Schmidt","sequence":"additional","affiliation":[{"name":"Deutsches Geod\u00e4tisches Forschungsinstitut der Technischen Universit\u00e4t M\u00fcnchen, Arcisstra\u00dfe 21, 80333 Munich, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7468-0617","authenticated-orcid":false,"given":"Eren","family":"Erdogan","sequence":"additional","affiliation":[{"name":"Deutsches Geod\u00e4tisches Forschungsinstitut der Technischen Universit\u00e4t M\u00fcnchen, Arcisstra\u00dfe 21, 80333 Munich, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0718-6069","authenticated-orcid":false,"given":"Florian","family":"Seitz","sequence":"additional","affiliation":[{"name":"Deutsches Geod\u00e4tisches Forschungsinstitut der Technischen Universit\u00e4t M\u00fcnchen, Arcisstra\u00dfe 21, 80333 Munich, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,4,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Teunissen, P.J.G., and Kleusberg, A. 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