{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,28]],"date-time":"2025-11-28T12:33:39Z","timestamp":1764333219383,"version":"build-2065373602"},"reference-count":52,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2022,10,13]],"date-time":"2022-10-13T00:00:00Z","timestamp":1665619200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Equipment Development Project of Aerospace System Department","award":["JHZ2021-0071-YZ(ZD)","42074041","TJ20203C040257","SKLGIE2022-ZZ-01","SKLGIE2019-Z-2-1","300102260301","300102262401"],"award-info":[{"award-number":["JHZ2021-0071-YZ(ZD)","42074041","TJ20203C040257","SKLGIE2022-ZZ-01","SKLGIE2019-Z-2-1","300102260301","300102262401"]}]},{"name":"National Natural Science Foundation of China Projects","award":["JHZ2021-0071-YZ(ZD)","42074041","TJ20203C040257","SKLGIE2022-ZZ-01","SKLGIE2019-Z-2-1","300102260301","300102262401"],"award-info":[{"award-number":["JHZ2021-0071-YZ(ZD)","42074041","TJ20203C040257","SKLGIE2022-ZZ-01","SKLGIE2019-Z-2-1","300102260301","300102262401"]}]},{"name":"Comprehensive Research Project of Aerospace System Department","award":["JHZ2021-0071-YZ(ZD)","42074041","TJ20203C040257","SKLGIE2022-ZZ-01","SKLGIE2019-Z-2-1","300102260301","300102262401"],"award-info":[{"award-number":["JHZ2021-0071-YZ(ZD)","42074041","TJ20203C040257","SKLGIE2022-ZZ-01","SKLGIE2019-Z-2-1","300102260301","300102262401"]}]},{"name":"Independent project of State Key Laboratory of Geographic Information Engineering","award":["JHZ2021-0071-YZ(ZD)","42074041","TJ20203C040257","SKLGIE2022-ZZ-01","SKLGIE2019-Z-2-1","300102260301","300102262401"],"award-info":[{"award-number":["JHZ2021-0071-YZ(ZD)","42074041","TJ20203C040257","SKLGIE2022-ZZ-01","SKLGIE2019-Z-2-1","300102260301","300102262401"]}]},{"name":"Fundamental Research Funds for the Central Universities, Chang\u2019an University","award":["JHZ2021-0071-YZ(ZD)","42074041","TJ20203C040257","SKLGIE2022-ZZ-01","SKLGIE2019-Z-2-1","300102260301","300102262401"],"award-info":[{"award-number":["JHZ2021-0071-YZ(ZD)","42074041","TJ20203C040257","SKLGIE2022-ZZ-01","SKLGIE2019-Z-2-1","300102260301","300102262401"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The new-generation photon-counting laser altimeter aboard the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) has acquired unprecedented high-density laser data on the global surface. The continuous analysis and calibration of potential systematic biases in laser data are important for generating highly accurate data products. Current studies mainly calibrate the absolute systematic bias of laser altimeters based on external reference data. There are few studies that focus on the analysis and calibration of relative systematic biases in long-term laser data. This paper explores a method for systematic biases analysis and calibration of ICESat-2 laser data based on track crossovers for the first time. In the experiment, the simulated data and ICESat-2 data were used to verify the algorithm. The results show that, during the three-year period in orbit, the standard deviation (STD) and bias of the crossover differences of the ICESat-2 terrain data were 0.82 m and \u22120.03 m, respectively. The simulation validation well demonstrate that the crossover adjustment can calibrate the relative bias between different beams. For ICESat-2 data, the STD of the estimated systematic bias after crossover adjustment was 0.09 m, and the mean absolute error (MAE) was 0.07 m. Compared with airborne lidar data, the bias and root mean square error (RMSE) of the ICESat-2 data remained basically unchanged after adjustment, i.e., \u22120.04 m and 0.38 m, respectively. This shows that the current ICESat-2 data products possess excellent internal and external accuracy. This study shows the potential of crossover for evaluating and calibrating the accuracy of spaceborne photon-counting laser altimeter data products, in terms of providing a technical approach to generate global\/regional high-accuracy point cloud data with consistent accuracy.<\/jats:p>","DOI":"10.3390\/rs14205125","type":"journal-article","created":{"date-parts":[[2022,10,14]],"date-time":"2022-10-14T01:44:13Z","timestamp":1665711853000},"page":"5125","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Biases Analysis and Calibration of ICESat-2\/ATLAS Data Based on Crossover Adjustment Method"],"prefix":"10.3390","volume":"14","author":[{"given":"Tao","family":"Wang","sequence":"first","affiliation":[{"name":"School of Geology Engineering and Geomatics, Chang\u2019an University, Xi\u2019an 710054, China"}]},{"given":"Yong","family":"Fang","sequence":"additional","affiliation":[{"name":"Xi\u2019an Research Institute of Surveying and Mapping, Xi\u2019an 710054, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0357-5312","authenticated-orcid":false,"given":"Shuangcheng","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Geology Engineering and Geomatics, Chang\u2019an University, Xi\u2019an 710054, China"}]},{"given":"Bincai","family":"Cao","sequence":"additional","affiliation":[{"name":"Xi\u2019an Research Institute of Surveying and Mapping, Xi\u2019an 710054, China"}]},{"given":"Zhenlei","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Geology Engineering and Geomatics, Chang\u2019an University, Xi\u2019an 710054, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,10,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2783","DOI":"10.1080\/01431161.2020.1862441","article-title":"An active-passive fusion strategy and accuracy evaluation for shallow water bathymetry based on ICESat-2 ATLAS laser point cloud and satellite remote sensing imagery","volume":"42","author":"Cao","year":"2021","journal-title":"Int. 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