{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,31]],"date-time":"2024-08-31T12:48:13Z","timestamp":1725108493039},"reference-count":32,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2021,6,12]],"date-time":"2021-06-12T00:00:00Z","timestamp":1623456000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2017YFA0603104"],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"State Key Program of National Natural Science Foundation of China","award":["42074006"]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"The global positioning system (GPS) can provide the daily coordinate time series to help geodesy and geophysical studies. However, due to logistics and malfunctioning, missing values are often \u201cseen\u201d in GPS time series, especially in polar regions. Acquiring a consistent and complete time series is the prerequisite for accurate and reliable statical analysis. Previous imputation studies focused on the temporal relationship of time series, and only a few studies used spatial relationships and\/or were based on machine learning methods. In this study, we impute 20 Greenland GPS time series using missForest, which is a new machine learning method for data imputation. The imputation performance of missForest and that of four traditional methods are assessed, and the methods\u2019 impacts on principal component analysis (PCA) are investigated. Results show that missForest can impute more than a 30-day gap, and its imputed time series has the least influence on PCA. When the gap size is 30 days, the mean absolute value of the imputed and true values for missForest is 2.71 mm. The normalized root mean squared error is 0.065, and the distance of the first principal component is 0.013. missForest outperforms the other compared methods. missForest can effectively restore the information of GPS time series and improve the results of related statistical processes, such as PCA analysis.<\/jats:p>","DOI":"10.3390\/rs13122312","type":"journal-article","created":{"date-parts":[[2021,6,15]],"date-time":"2021-06-15T02:25:46Z","timestamp":1623723946000},"page":"2312","source":"Crossref","is-referenced-by-count":15,"title":["Imputation of GPS Coordinate Time Series Using missForest"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"http:\/\/orcid.org\/0000-0001-7436-2504","authenticated-orcid":false,"given":"Shengkai","family":"Zhang","sequence":"first","affiliation":[{"name":"Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan 430079, China"}]},{"ORCID":"http:\/\/orcid.org\/0000-0003-2105-0528","authenticated-orcid":false,"given":"Li","family":"Gong","sequence":"additional","affiliation":[{"name":"Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan 430079, China"}]},{"given":"Qi","family":"Zeng","sequence":"additional","affiliation":[{"name":"Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan 430079, China"}]},{"given":"Wenhao","family":"Li","sequence":"additional","affiliation":[{"name":"School of Geomatics Science and Technology, Nanjing Tech University, Nanjing 211800, China"}]},{"ORCID":"http:\/\/orcid.org\/0000-0003-3742-9380","authenticated-orcid":false,"given":"Feng","family":"Xiao","sequence":"additional","affiliation":[{"name":"Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan 430079, China"}]},{"given":"Jintao","family":"Lei","sequence":"additional","affiliation":[{"name":"Department of Land Surveying and Geo-Informatics, Hong Kong Polytechnic University, Kowloon, Hong Kong"}]}],"member":"1968","published-online":{"date-parts":[[2021,6,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1007\/s10291-017-0689-3","article-title":"A MATLAB-Based Kriged Kalman Filter Software for Interpolating Missing Data in GNSS Coordinate Time Series","volume":"22","author":"Liu","year":"2017","journal-title":"GPS Solut."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.epsl.2013.06.011","article-title":"Aseismic Deformation across the Hilina Fault System, Hawaii, Revealed by Wavelet Analysis of InSAR and GPS Time Series","volume":"376","author":"Shirzaei","year":"2013","journal-title":"Earth Planet. 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