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one of the important error sources in the Global Navigation Satellite System (GNSS) data processing. With the rapid construction and development of GNSS, the abundant satellite resources have brought new opportunities for ionospheric monitoring. To further investigate the performances and abilities of Galileo and BDS in ionosphere modeling, we study the ionosphere modeling based on the 15th order spherical harmonic function, and 364 stations around the world are selected for global ionospheric modeling of GPS, GLONASS, Galileo and BDS systems under ionospheric quiet and active conditions, respectively. The results show that the average biases of the ionospheric models built by GPS, GLONASS and Galileo are relatively small, which are within 2 Total Electron Content Unit (TECU) as compared to the Center for Orbit Determination in Europe (CODE) global ionospheric map (GIM), while the average biases of the models built by BDS are between 6 and 8 TECU during the ionospheric quiet and active days, respectively. In addition, in order to analyze the modeling performances before and after using BDS geostationary earth orbit (GEO) satellites, BDS is divided into two groups, in which one group contains medium earth orbit (MEO), inclined geosynchronous orbit (IGSO) and GEO satellites; and the other group contains only MEO and IGSO satellites. The results show that the influence of GEO satellites on ionospheric modeling is less than 1 TECU. Due to the distribution of the stations, the 0-value region in the ionospheric model is mainly distributed in the mid and high-latitude regions of the southern hemisphere. Since the ionospheric parameters are lumped with the Differential Code Bias (DCB), we also estimate the DCB parameters and analyze their performances. The DCB estimated in ionosphere modeling shows strong stability, with the average biases of GPS, GLONASS, Galileo and BDS under 0.25 ns, 0.25 ns, 0.2 ns and 0.42 ns, respectively. We also estimate other DCB types of the four GNSS systems. The results show that the DCB is stable and shows consistency with Chinese Academy of Sciences (CAS) DCB products.<\/jats:p>","DOI":"10.3390\/rs14215479","type":"journal-article","created":{"date-parts":[[2022,11,1]],"date-time":"2022-11-01T06:01:28Z","timestamp":1667282488000},"page":"5479","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["BDS and Galileo: Global Ionosphere Modeling and the Comparison to GPS and GLONASS"],"prefix":"10.3390","volume":"14","author":[{"given":"Yafeng","family":"Wang","sequence":"first","affiliation":[{"name":"Chinese Academy of Surveying and Mapping, Beijing 100036, China"},{"name":"College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hu","family":"Wang","sequence":"additional","affiliation":[{"name":"Chinese Academy of Surveying and Mapping, Beijing 100036, China"},{"name":"Key Laboratory of Surveying and Mapping Science and Geospatial Information Technology of MNR, Chinese Academy of Surveying and Mapping, Beijing 100036, China"},{"name":"Beijing Fangshan Human Satellite Laser National Field Scientific Observation and Research Station, Beijing 102406, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yamin","family":"Dang","sequence":"additional","affiliation":[{"name":"Chinese Academy of Surveying and Mapping, Beijing 100036, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3772-1966","authenticated-orcid":false,"given":"Hongyang","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Geomatics Science and Technology, Nanjing Tech University, Nanjing 210037, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Changhui","family":"Xu","sequence":"additional","affiliation":[{"name":"Chinese Academy of Surveying and Mapping, Beijing 100036, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiang","family":"Yang","sequence":"additional","affiliation":[{"name":"Chinese Academy of Surveying and Mapping, Beijing 100036, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yingying","family":"Ren","sequence":"additional","affiliation":[{"name":"College of Surveying and Geo-Informatics, Tongji University, Shanghai 200092, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shushan","family":"Fang","sequence":"additional","affiliation":[{"name":"Chinese Academy of Surveying and Mapping, Beijing 100036, China"},{"name":"Key Laboratory of Surveying and Mapping Science and Geospatial Information Technology of MNR, Chinese Academy of Surveying and Mapping, Beijing 100036, China"},{"name":"Beijing Fangshan Human Satellite Laser National Field Scientific Observation and Research Station, Beijing 102406, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,10,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Haddad, R., Kovach, K., and Slattery, R. 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