{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T06:53:00Z","timestamp":1762325580572,"version":"build-2065373602"},"reference-count":37,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2023,4,23]],"date-time":"2023-04-23T00:00:00Z","timestamp":1682208000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["41876105","41371436"],"award-info":[{"award-number":["41876105","41371436"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2), launched in September 2018, has been widely used in forestry and surveying. A high-accuracy digital elevation model (DEM)\/digital surface model (DSM) for terrain matching can effectively evaluate the ICESat-2 design requirements and provide essential data support for further study. The conventional terrain-matching methods regard the laser ground track as a whole, ignoring the individual differences caused by the interaction of photons during flight. Therefore, a novel terrain-matching method using a two-dimensional affine transformation model was proposed to describe the deformation of laser tracks. The least-square optimizes the model parameters with the high-accuracy terrain data to obtain the best matching result. The results in McMurdo Dry Valley (MDV), Antarctica, and Zhengzhou (ZZ), China, demonstrate that the proposed method can verify geolocation accuracy and indicate that the average horizontal accuracy of ICESat-2 V5 data is about 3.86 m in MDV and 4.67 m in ZZ. It shows that ICESat-2 has good positioning accuracy, even in mountainous areas with complex terrain. Additionally, the random forest (RF) model was calculated to analyze the influence of four factors on geographic location accuracy. The slope and signal-to-noise ratio (SNR) are considered the crucial factors affecting the accuracy of ICESat-2 data.<\/jats:p>","DOI":"10.3390\/rs15092236","type":"journal-article","created":{"date-parts":[[2023,4,24]],"date-time":"2023-04-24T02:06:11Z","timestamp":1682301971000},"page":"2236","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Assessment of ICESat-2\u2019s Horizontal Accuracy Using an Iterative Matching Method Based on High-Accuracy Terrains"],"prefix":"10.3390","volume":"15","author":[{"given":"Ming","family":"Gao","sequence":"first","affiliation":[{"name":"Institute of Geospatial Information, Information Engineering University, Zhengzhou 450001, China"}]},{"given":"Shuai","family":"Xing","sequence":"additional","affiliation":[{"name":"Institute of Geospatial Information, Information Engineering University, Zhengzhou 450001, China"}]},{"given":"Guoping","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Geospatial Information, Information Engineering University, Zhengzhou 450001, China"},{"name":"Collaborative Innovation Center of Geo-Information Technology for Smart Central Plains, Zhengzhou 450001, China"},{"name":"Key Laboratory of Spatiotemporal Perception and Intelligent Processing, Ministry of Natural Resources, Zhengzhou 450001, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3361-5269","authenticated-orcid":false,"given":"Xinlei","family":"Zhang","sequence":"additional","affiliation":[{"name":"Xi\u2019an Research Institute of Surveying and Mapping, Xi\u2019an 710054, China"}]},{"given":"Pengcheng","family":"Li","sequence":"additional","affiliation":[{"name":"Institute of Geospatial Information, Information Engineering University, Zhengzhou 450001, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"557","DOI":"10.5194\/tc-9-557-2015","article-title":"Brief Communication: Contending Estimates of 2003\u20132008 Glacier Mass Balance over the Pamir\u2013Karakoram\u2013Himalaya","volume":"9","author":"Treichler","year":"2015","journal-title":"Cryosphere"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1016\/S0264-3707(02)00042-X","article-title":"ICESat\u2032s Laser Measurements of Polar Ice, Atmosphere, Ocean, and Land","volume":"34","author":"Zwally","year":"2002","journal-title":"J. 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