{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T06:54:53Z","timestamp":1780988093110,"version":"3.54.1"},"reference-count":46,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2020,1,18]],"date-time":"2020-01-18T00:00:00Z","timestamp":1579305600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004032","name":"Jilin University","doi-asserted-by":"publisher","award":["JLUSTIRT, 2017TD-26"],"award-info":[{"award-number":["JLUSTIRT, 2017TD-26"]}],"id":[{"id":"10.13039\/501100004032","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The selection of an appropriate global gravity field model and refinement method can effectively improve the accuracy of the refined regional geoid model in a certain research area. We analyzed the accuracy of Experimental Geopotential Model (XGM2016) based on the GPS-leveling data and the modification parameters of the global mean square errors in the KTH geoid refinement in Jilin Province, China. The regional geoid was refined based on Earth Gravitational Model (EGM2008) and XGM2016 using both the Helmert condensation method with an RCR procedure and the KTH method. A comparison of the original two gravity field models to the GPS-leveling benchmarks showed that the accuracies of XGM2016 and EGM2008 in the plain area of Jilin Province are similar with a standard deviation (STD) of 5.8 cm, whereas the accuracy of EGM2008 in the high mountainous area is 1.4 cm better than that of XGM2016, which may be attributed to its low resolution. The modification parameters between the two gravity field models showed that the coefficient error of XGM2016 model was lower than that of EGM2008 for the same degree of expansion. The different modification limits and integral radii may produce a centimeter level difference in global mean square error, while the influence of the truncation error caused by the integral was at the millimeter level. The terrestrial gravity data error accounted for the majority of the global mean square error. The optimal least squares modification obtained the minimum global mean square error, and the global mean square error calculated based on XGM2016 model was reduced by about 1~3 cm compared with EGM2008. The refined geoid based on the two gravity field models indicated that both KTH and RCR method can effectively improve the STD of the geoid model from about six to three centimeters. The refined accuracy of EGM2008 model using RCR and KTH methods is slightly better than that of XGM2016 model in the plain and high mountain areas after seven-parameter fitting. EGM2008 based on the KTH method was the most precise at \u00b1 2.0 cm in the plain area and \u00b1 2.4 cm in the mountainous area. Generally, for the refined geoid based on the two Earth gravity models, KTH produced results similar to RCR in the plain area, and had relatively better performance for the mountainous area where terrestrial gravity data is sparse and unevenly distributed.<\/jats:p>","DOI":"10.3390\/rs12020324","type":"journal-article","created":{"date-parts":[[2020,1,20]],"date-time":"2020-01-20T04:27:09Z","timestamp":1579494429000},"page":"324","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Performance Comparison of Geoid Refinement between XGM2016 and EGM2008 Based on the KTH and RCR Methods: Jilin Province, China"],"prefix":"10.3390","volume":"12","author":[{"given":"Qiong","family":"Wu","sequence":"first","affiliation":[{"name":"College of Geo-exploration Science and Technology, Jilin University, Changchun 130021, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongyao","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Geo-exploration Science and Technology, Jilin University, Changchun 130021, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bin","family":"Wang","sequence":"additional","affiliation":[{"name":"Geodetic Data Processing Centre, National Administration of Surveying, Mapping and Geoinformation, Xi\u2019an 710054, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shengbo","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Geo-exploration Science and Technology, Jilin University, Changchun 130021, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongqing","family":"Li","sequence":"additional","affiliation":[{"name":"College of Geo-exploration Science and Technology, Jilin University, Changchun 130021, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,1,18]]},"reference":[{"key":"ref_1","unstructured":"Molodenskii, M. 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