{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T03:10:52Z","timestamp":1769829052301,"version":"3.49.0"},"reference-count":53,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2022,7,13]],"date-time":"2022-07-13T00:00:00Z","timestamp":1657670400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"VEGA Project","award":["ANR11-LBX-0023-01"],"award-info":[{"award-number":["ANR11-LBX-0023-01"]}]},{"name":"VEGA Project","award":["CNRS FR 2036"],"award-info":[{"award-number":["CNRS FR 2036"]}]},{"name":"CNRS Program LEFE\/INSU","award":["ANR11-LBX-0023-01"],"award-info":[{"award-number":["ANR11-LBX-0023-01"]}]},{"name":"CNRS Program LEFE\/INSU","award":["CNRS FR 2036"],"award-info":[{"award-number":["CNRS FR 2036"]}]},{"name":"Project Labex MME-DII","award":["ANR11-LBX-0023-01"],"award-info":[{"award-number":["ANR11-LBX-0023-01"]}]},{"name":"Project Labex MME-DII","award":["CNRS FR 2036"],"award-info":[{"award-number":["CNRS FR 2036"]}]},{"name":"FP2M Federation","award":["ANR11-LBX-0023-01"],"award-info":[{"award-number":["ANR11-LBX-0023-01"]}]},{"name":"FP2M Federation","award":["CNRS FR 2036"],"award-info":[{"award-number":["CNRS FR 2036"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Homogenization is an important and crucial step to improve the usage of observational data for climate analysis. This work is motivated by the analysis of long series of GNSS Integrated Water Vapour (IWV) data, which have not yet been used in this context. This paper proposes a novel segmentation method called segfunc that integrates a periodic bias and a heterogeneous, monthly varying, variance. The method consists in estimating first the variance using a robust estimator and then estimating the segmentation and periodic bias iteratively. This strategy allows for the use of the dynamic programming algorithm, which is the most efficient exact algorithm to estimate the change point positions. The performance of the method is assessed through numerical simulation experiments. It is implemented in the R package GNSSseg, which is available on the CRAN. This paper presents the application of the method to a real data set from a global network of 120 GNSS stations. A hit rate of 32% is achieved with respect to available metadata. The final segmentation is made in a semi-automatic way, where the change points detected by three different penalty criteria are manually selected. In this case, the hit rate reaches 60% with respect to the metadata.<\/jats:p>","DOI":"10.3390\/rs14143379","type":"journal-article","created":{"date-parts":[[2022,7,14]],"date-time":"2022-07-14T00:12:40Z","timestamp":1657757560000},"page":"3379","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["GNSSseg, a Statistical Method for the Segmentation of Daily GNSS IWV Time Series"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1218-1657","authenticated-orcid":false,"given":"Annarosa","family":"Quarello","sequence":"first","affiliation":[{"name":"Capgemini Engineering, 75016 Paris, France"},{"name":"Institut de Physique du Globe de Paris, Universit\u00e9 Paris Cit\u00e9, CNRS, IGN, 75005 Paris, France"},{"name":"ENSG-G\u00e9omatique, IGN, 77455 Marne-la-Vall\u00e9e, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5980-938X","authenticated-orcid":false,"given":"Olivier","family":"Bock","sequence":"additional","affiliation":[{"name":"Institut de Physique du Globe de Paris, Universit\u00e9 Paris Cit\u00e9, CNRS, IGN, 75005 Paris, France"},{"name":"ENSG-G\u00e9omatique, IGN, 77455 Marne-la-Vall\u00e9e, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9170-5836","authenticated-orcid":false,"given":"Emilie","family":"Lebarbier","sequence":"additional","affiliation":[{"name":"Laboratoire Modal\u2019X, UPL, Universit\u00e9 Paris Nanterre, 92000 Nanterre, France"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,13]]},"reference":[{"key":"ref_1","unstructured":"Trenberth, K.E., Jones, P.D., Ambenje, P., Bojariu, R., Easterling, D., Klein Tank, A., Parker, D., Rahimzadeh, F., Renwick, J.A., and Rusticucci, M. 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