{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T06:34:31Z","timestamp":1773815671541,"version":"3.50.1"},"reference-count":61,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,1,23]],"date-time":"2022-01-23T00:00:00Z","timestamp":1642896000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41774014"],"award-info":[{"award-number":["41774014"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41574014"],"award-info":[{"award-number":["41574014"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the Liaoning Revitalization Talents Program under Grant","award":["XLYC2002082"],"award-info":[{"award-number":["XLYC2002082"]}]},{"name":"the Liaoning Revitalization Talents Program under Grant","award":["XLYC2002101"],"award-info":[{"award-number":["XLYC2002101"]}]},{"name":"the Liaoning Revitalization Talents Program under Grant","award":["XLYC2008034"],"award-info":[{"award-number":["XLYC2008034"]}]},{"name":"the Innovation Workstation Project of Science and Technology Commission of the Central Military Commission under Grant","award":["085015"],"award-info":[{"award-number":["085015"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Densely distributed Global Navigation Satellite System (GNSS) stations can invert the terrestrial water storage anomaly (TWSA) with high precision. However, the uneven distribution of GNSS stations greatly limits the application of TWSA inversion. The purpose of this study was to compensate for the spatial coverage of GNSS stations by simulating the vertical deformation in unobserved grids. First, a new deep learning weight loading inversion model (DWLIM) was constructed by combining the long short-term memory (LSTM) algorithm, inverse distance weight, and the crustal load model. DWLIM is beneficial for improving the inversion accuracy of TWSA based on the GNSS vertical displacement. Second, the DWLIM-based and traditional GNSS-derived TWSA methods were utilized to derive TWSA over mainland China. Furthermore, the TWSA results were compared with the TWSA solutions of the Gravity Recovery and Climate Experiment (GRACE) and Global Land Data Assimilation System (GLDAS) model. The results indicate that the maximum Pearson\u2019s correlation coefficient (PCC), Nash\u2013Sutcliffe efficiency (NSE) coefficient, and root mean square error (RMSE) equal 0.81, 0.61, and 2.18 cm, respectively. The accuracy of DWLIM was higher than that of the traditional GNSS inversion method according to PCC, NSE, and RMSE, which were increased by 67.11, 128.15, and 22.75%. The inversion strategy of DWLIM can effectively improve the accuracy of TWSA inversion in regions with unevenly distributed GNSS stations. Third, this study investigated the variation characteristics of TWSA based on DWLIM in 10 river basins over mainland China. The analysis shows that the TWSA amplitudes of Songhua and Liaohe River basins are significantly higher than those of the other basins. Moreover, TWSA sequences in each river basin contain annual seasonal signals, and the wave peaks of TWSA estimates emerge between June and July. Overall, DWLIM provides a useful measure to derive TWSA in regions where GNSS stations are uneven or sparse.<\/jats:p>","DOI":"10.3390\/rs14030535","type":"journal-article","created":{"date-parts":[[2022,1,23]],"date-time":"2022-01-23T20:34:40Z","timestamp":1642970080000},"page":"535","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Improving the Inversion Accuracy of Terrestrial Water Storage Anomaly by Combining GNSS and LSTM Algorithm and Its Application in Mainland China"],"prefix":"10.3390","volume":"14","author":[{"given":"Yifan","family":"Shen","sequence":"first","affiliation":[{"name":"School of Geomatics, Liaoning Technical University, Fuxin 123000, China"},{"name":"Qian Xuesen Laboratory of Technology, China Academy of Space Technology, Beijing 100094, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Geomatics, Liaoning Technical University, Fuxin 123000, China"},{"name":"Qian Xuesen Laboratory of Technology, China Academy of Space Technology, Beijing 100094, China"},{"name":"School of Aeronautics and Astronautics, Taiyuan University of Technology, Jinzhong 030600, China"},{"name":"School of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China"},{"name":"School of Aerospace Science and Technology, Xidian University, Xi\u2019an 710126, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenjie","family":"Yin","sequence":"additional","affiliation":[{"name":"Qian Xuesen Laboratory of Technology, China Academy of Space Technology, Beijing 100094, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aigong","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Geomatics, Liaoning Technical University, Fuxin 123000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huizhong","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Geomatics, Liaoning Technical University, Fuxin 123000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4216-804X","authenticated-orcid":false,"given":"Qingqing","family":"Wang","sequence":"additional","affiliation":[{"name":"Qian Xuesen Laboratory of Technology, China Academy of Space Technology, Beijing 100094, China"},{"name":"School of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiwei","family":"Chen","sequence":"additional","affiliation":[{"name":"Qian Xuesen Laboratory of Technology, China Academy of Space Technology, Beijing 100094, China"},{"name":"School of Aerospace Science and Technology, Xidian University, Xi\u2019an 710126, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,1,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.rse.2014.08.006","article-title":"Drought and flood monitoring for a large karst plateau in southwest China using extended GRACE data","volume":"155","author":"Long","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1007\/s40328-021-00338-4","article-title":"Long-term temporal prediction of terrestrial water storage changes over global basins using GRACE and limited GRACE-FO data","volume":"56","author":"Ahi","year":"2021","journal-title":"Acta Geod. Geophys."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Shen, Y., Zheng, W., Yin, W., Xu, A., Zhu, H., Yang, S., and Su, K. (2021). Inverted algorithm of terrestrial water-storage anomalies based on machine learning combined with load model and its application in southwest China. Remote Sens., 13.","DOI":"10.3390\/rs13173358"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"3874742","DOI":"10.1155\/2019\/3874742","article-title":"Reconstructing terrestrial water storage variations from 1980 to 2015 in the Beishan area of China","volume":"2019","author":"Yin","year":"2019","journal-title":"Geofluids"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Li, W., Wang, D., Liu, S., Zhu, Y., and Yan, Z. (2020). Reclamation of Cultivated Land Reserves in Northeast China: Indigenous Ecological Insecurity Underlying National Food Security. Int. J. Environ. Res. Public Health, 17.","DOI":"10.3390\/ijerph17041211"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"L24605","DOI":"10.1029\/2004GL021435","article-title":"Climate-driven deformation of the solid Earth from GRACE and GPS","volume":"31","author":"Davis","year":"2004","journal-title":"Geophys. Res. Lett."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Li, W., Wang, W., Zhang, C., Wen, H., Zhong, Y., Zhu, Y., and Li, Z. (2019). Bridging terrestrial water storage anomaly during GRACE\/GRACE-FO gap using SSA method: A case study in China. Sensors, 19.","DOI":"10.3390\/s19194144"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"126349","DOI":"10.1016\/j.jhydrol.2021.126349","article-title":"Estimation of daily hydrological mass changes using continuous GNSS measurements in mainland China","volume":"598","author":"Jiang","year":"2021","journal-title":"J. Hydrol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1139","DOI":"10.1007\/s10712-016-9385-z","article-title":"Terrestrial water storage anomalies associated with drought in southwestern USA from GPS observations","volume":"37","author":"Jin","year":"2016","journal-title":"Surv. Geophys."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"5973","DOI":"10.1029\/2017JD027468","article-title":"Statistical downscaling of GRACE-derived groundwater storage using ET data in the North China Plain","volume":"123","author":"Yin","year":"2018","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Tangdamrongsub, N., and \u0160prl\u00e1k, M. (2021). The assessment of hydrologic- and flood-induced land deformation in data-sparse regions using GRACE\/GRACE-FO data assimilation. Remote Sens., 13.","DOI":"10.3390\/rs13020235"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"112249","DOI":"10.1016\/j.rse.2020.112249","article-title":"Monitoring time-varying terrestrial water storage changes using daily GNSS measurements in Yunnan, southwest China","volume":"254","author":"Jiang","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1007\/s10712-008-9033-3","article-title":"Hydrological signals observed by the GRACE satellites","volume":"29","author":"Schmidt","year":"2008","journal-title":"Surv. Geophys."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"5051","DOI":"10.1007\/s00024-019-02251-y","article-title":"Characterizing the seasonal hydrological loading over the asian continent using GPS, GRACE, and hydrological model","volume":"176","author":"Xiang","year":"2019","journal-title":"Pure Appl. Geophys."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2433","DOI":"10.1029\/2006WR005779","article-title":"Analysis of terrestrial water storage changes from GRACE and GLDAS","volume":"44","author":"Syed","year":"2008","journal-title":"Water Resour. Res."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"685","DOI":"10.1007\/s11269-019-02468-5","article-title":"Assessment of water storage changes using GRACE and GLDAS","volume":"34","author":"Moghim","year":"2020","journal-title":"Water Resour. Manag."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.jog.2011.07.003","article-title":"Efficient accuracy improvement of GRACE global gravitational field recovery using a new inter-satellite range interpolation method","volume":"53","author":"Zheng","year":"2012","journal-title":"J. Geodyn."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2110","DOI":"10.1002\/wrcr.20192","article-title":"Evaluation of groundwater depletion in North China using the Gravity Recovery and Climate Experiment (GRACE) data and ground-based measurements","volume":"49","author":"Feng","year":"2013","journal-title":"Water Resour. Res."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Fok, H.S., and Liu, Y. (2019). An improved GPS-inferred seasonal terrestrial water storage using terrain-corrected vertical crustal displacements constrained by GRACE. Remote Sens., 11.","DOI":"10.3390\/rs11121433"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"6048","DOI":"10.1002\/2013GL058093","article-title":"Horizontal motion in elastic response to seasonal loading of rain water in the Amazon Basin and monsoon water in Southeast Asia observed by GPS and inferred from GRACE","volume":"40","author":"Fu","year":"2013","journal-title":"Geophys. Res. Lett."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"L19503","DOI":"10.1029\/2009GL040222","article-title":"Increasing rates of ice mass loss from the Greenland and Antarctic ice sheets revealed by GRACE","volume":"36","author":"Velicogna","year":"2009","journal-title":"Geophys. Res. Lett."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"259","DOI":"10.3390\/rs10020259","article-title":"Vertical displacements driven by groundwater storage changes in the North China Plain detected by GPS observations","volume":"10","author":"Liu","year":"2018","journal-title":"Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1835","DOI":"10.3390\/rs12111835","article-title":"Surface mass variations from GPS and GRACE\/GFO: A case study in southwest China","volume":"12","author":"Zhong","year":"2020","journal-title":"Remote Sens."},{"key":"ref_24","unstructured":"Pan, Y., Zhang, C., Gong, H.L., Yeh, P.J.F., Shen, Y., Guo, Y., Huang, Z., and Li, X. (2017, January 23\u201328). Detection of human-induced evapotranspiration using GRACE satellite observations in the Haihe River Basin of China. Proceedings of the Egu General Assembly Conference, Vienna, Austria."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1038\/s41597-021-00862-6","article-title":"Downscaling GRACE total water storage change using partial least squares regression","volume":"8","author":"Vishwakarma","year":"2021","journal-title":"Sci. Data"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"533","DOI":"10.1007\/s42452-021-04525-4","article-title":"A time series assessment of terrestrial water storage and its relationship with hydro-meteorological factors in Gilgit-Baltistan region using GRACE observation and GLDAS-Noah model","volume":"3","author":"Hussain","year":"2021","journal-title":"SN Appl. Sci."},{"key":"ref_27","first-page":"669","article-title":"Vertical deformation of seasonal hydrological loading in southern tibet detected by joint analysis of GPS and GRACE","volume":"43","author":"Chen","year":"2018","journal-title":"Geomat. Inf. Sci. Wuhan Univ."},{"key":"ref_28","first-page":"671","article-title":"Solute transport in heterogeneous porous formations","volume":"55","author":"Dagan","year":"2004","journal-title":"Water Resour. Res."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"B03407","DOI":"10.1029\/2011JB008925","article-title":"Seasonal and long-term vertical deformation in the Nepal Himalaya constrained by GPS and GRACE measurements","volume":"117","author":"Fu","year":"2012","journal-title":"J. Geophys. Res. Solid Earth"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1795","DOI":"10.1002\/jgrb.50104","article-title":"The use of GPS horizontals for loading studies, with applications to northern California and southeast Greenland","volume":"118","author":"Wahr","year":"2013","journal-title":"J. Geophys. Res. Solid Earth"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1016\/j.quaint.2017.05.043","article-title":"Continuous GPS measurements of crustal deformation in Garhwal-Kumaun Himalaya","volume":"462","author":"Gautam","year":"2017","journal-title":"Quat. Int."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1971","DOI":"10.1002\/2014GL059570","article-title":"Seasonal variation in total water storage in California inferred from GPS observations of vertical land motion","volume":"41","author":"Argus","year":"2014","journal-title":"Geophys. Res. Lett."},{"key":"ref_33","unstructured":"Argus, D. (2015, January 14\u201318). Sustained water changes in California during drought and heavy precipitation inferred from GPS, InSAR, and GRACE. Proceedings of the Agu Fall Meeting, San Francisco, CA, USA."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1587","DOI":"10.1126\/science.1260279","article-title":"Ongoing drought-induced uplift in the western United States","volume":"345","author":"Borsa","year":"2014","journal-title":"Science"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"581","DOI":"10.1002\/2017WR021521","article-title":"Accuracy of snow water equivalent estimated from GPS vertical displacements: A synthetic loading case study for western U.S. mountains","volume":"54","author":"Enzminger","year":"2018","journal-title":"Water Resour. Res."},{"key":"ref_36","first-page":"177","article-title":"Dense gps array as a new sensor of seasonal changes of surface loads","volume":"Volume 150","author":"Heki","year":"2004","journal-title":"The State of the Planet: Frontiers and Challenges in Geophysics"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"13006","DOI":"10.1029\/2019GL085370","article-title":"A decade of water storage changes across the contiguous united states from GPS and satellite gravity","volume":"46","author":"Adusumilli","year":"2019","journal-title":"Geophys. Res. Lett."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"19861","DOI":"10.3390\/s141019861","article-title":"Earth surface deformation in the North China Plain detected by joint analysis of GRACE and GPS data","volume":"14","author":"Liu","year":"2014","journal-title":"Sensors"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"26096","DOI":"10.3390\/s151026096","article-title":"The quasi-biennial vertical oscillations at global GPS stations: Identification by ensemble empirical mode decomposition","volume":"15","author":"Pan","year":"2015","journal-title":"Sensors"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"9290","DOI":"10.1002\/2017JB014465","article-title":"Crustal deformation in the India-Eurasia collision zone from 25 years of GPS measurements: Crustal deformation in Asia from GPS","volume":"122","author":"Zheng","year":"2017","journal-title":"J. Geophys. Res. Solid Earth"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"17507","DOI":"10.1109\/ACCESS.2021.3049118","article-title":"Feature extraction algorithm using a correlation coefficient combined with the VMD and its application to the GPS and GRACE","volume":"9","author":"Shen","year":"2021","journal-title":"IEEE Access"},{"key":"ref_42","unstructured":"Herring, T.A., King, R.W., and Mcclusky, S.C. (2010). GAMIT Reference Manual."},{"key":"ref_43","unstructured":"Xue, K. (2017). Combined GRACE and GPS to Study Terrestrial Water Storage, Chang\u2019an University."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"150731131106004","DOI":"10.1175\/JHM-D-14-0230.1","article-title":"Evaluation of the global land data assimilation system (GLDAS) air temperature data products","volume":"16","author":"Ji","year":"2015","journal-title":"J. Hydrometeorol."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1007\/s13351-021-0107-1","article-title":"The Asian subtropical westerly jet stream in CRA-40, ERA5, and CFSR reanalysis data: Comparative assessment","volume":"35","author":"Yu","year":"2021","journal-title":"J. Meteorol. Res."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","article-title":"Long Short-Term Memory","volume":"9","author":"Hochreiter","year":"1997","journal-title":"Neural Comput."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1841","DOI":"10.1007\/s10973-016-6082-6","article-title":"The multi-dimensional ensemble empirical mode decomposition (MEEMD)","volume":"128","author":"Yao","year":"2017","journal-title":"J. Therm. Anal. Calorim."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1016\/j.cageo.2012.06.022","article-title":"Load love numbers and Green\u2019s functions for elastic earth models PREM, iasp91, ak135, and modified models with refined crustal structure from Crust 2.0","volume":"49","author":"Wang","year":"2012","journal-title":"Comput. Geosci."},{"key":"ref_49","first-page":"235","article-title":"Determining the ridge parameter in a ridge estimation using L-curve method","volume":"29","author":"Wang","year":"2004","journal-title":"Geomat. Inf. Sci. Wuhan Univ."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"450","DOI":"10.1038\/384450a0","article-title":"Relatively recent construction of the Tien Shan inferred from GPS measurements of present-day crustal deformation rates","volume":"384","author":"Abdrakhmatov","year":"1996","journal-title":"Nature"},{"key":"ref_51","first-page":"404","article-title":"A comparison of annual vertical crustal displacements from GPS and Gravity Recovery and Climate Experiment (GRACE) over Europe","volume":"112","author":"Dam","year":"2007","journal-title":"J. Geophys. Res. Solid Earth"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1945","DOI":"10.1016\/j.dsp.2013.06.014","article-title":"Research on the stability analysis of GNSS reference stations network by time series analysis","volume":"23","year":"2013","journal-title":"Digit. Signal. Process."},{"key":"ref_53","first-page":"4777","article-title":"Determination of vertical surface displacements in Sichuan using GPS and GRACE measurements","volume":"061","author":"Ding","year":"2018","journal-title":"Chin. J. Geophys."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"He, M., Shen, W., Pan, Y., Chen, R., and Guo, G. (2017). Temporal\u2013Spatial surface seasonal mass changes and vertical crustal deformation in south china block from GPS and GRACE measurements. Sensors, 18.","DOI":"10.3390\/s18010099"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"552","DOI":"10.1002\/2014JB011415","article-title":"GPS as an independent measurement to estimate terrestrial water storage variations in Washington and Oregon","volume":"120","author":"Fu","year":"2015","journal-title":"J. Geophys. Res. Solid Earth"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"5008","DOI":"10.1002\/jgrb.50353","article-title":"Numerical simulations of global-scale high-resolution hydrological crustal deformations","volume":"118","author":"Dill","year":"2013","journal-title":"J. Geophys. Res. Solid Earth"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"1247","DOI":"10.5194\/gmd-7-1247-2014","article-title":"Root mean square error (RMSE) or mean absolute error (MAE) aguments against avoiding RMSE in the literature","volume":"7","author":"Chai","year":"2014","journal-title":"Geosci. Model. Dev."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1016\/S0167-9473(03)00062-8","article-title":"Pseudo R-squared measures for poisson regression models with over- or underdispersion","volume":"44","author":"Heinzl","year":"2003","journal-title":"Comput. Stat. Data Anal."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.jhydrol.2009.08.003","article-title":"Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling","volume":"377","author":"Gupta","year":"2009","journal-title":"J. Hydrol."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1023\/A:1007586507433","article-title":"An Experimental Comparison of Ordinary and Universal Kriging and Inverse Distance Weighting","volume":"31","author":"Zimmerman","year":"1999","journal-title":"Math. Geol."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"627","DOI":"10.1109\/LGRS.2020.2983045","article-title":"Quantifying noise in daily GPS height time series: Harmonic function versus GRACE-assimilating modeling approaches","volume":"18","author":"Klos","year":"2020","journal-title":"IEEE Geosci. Remote Sens. Lett."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/3\/535\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:06:18Z","timestamp":1760133978000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/3\/535"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,23]]},"references-count":61,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2022,2]]}},"alternative-id":["rs14030535"],"URL":"https:\/\/doi.org\/10.3390\/rs14030535","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,23]]}}}