{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T17:09:04Z","timestamp":1770916144788,"version":"3.50.1"},"reference-count":59,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2021,2,25]],"date-time":"2021-02-25T00:00:00Z","timestamp":1614211200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41801261"],"award-info":[{"award-number":["41801261"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100018537","name":"National Science and Technology Major Project","doi-asserted-by":"publisher","award":["11-Y20A12-9001-17\/18; 42-Y20A11-9001-17\/18"],"award-info":[{"award-number":["11-Y20A12-9001-17\/18; 42-Y20A11-9001-17\/18"]}],"id":[{"id":"10.13039\/501100018537","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2020T130148"],"award-info":[{"award-number":["2020T130148"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100011354","name":"State Key Laboratory of Geo-Information Engineering","doi-asserted-by":"publisher","award":["SKLGIE2018-Z-3-1"],"award-info":[{"award-number":["SKLGIE2018-Z-3-1"]}],"id":[{"id":"10.13039\/501100011354","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["2042020kf1050"],"award-info":[{"award-number":["2042020kf1050"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) can measure the elevations of the Earth\u2019s surface using a sampling strategy with unprecedented spatial detail. In the daytime of mountainous areas where the signal\u2013noise ratio (SNR) of weak beam data is very low, current algorithms do not always perform well on extracting signal photons from weak beam data (i.e., many signal photons were missed). This paper proposes an effective algorithm to extract signal photons from the weak beam data of ICESat-2 in mountainous areas. First, a theoretical equation of SNR for ICESat-2 measured photons in mountainous areas was derived to prove that the available information provided by strong beam data can be used to assist the signal extraction of weak beam data (that may have very low SNR in mountainous areas). Then, the relationship between the along-track slope and the noise level was used as the bridge to connect the strong and weak beam data. To be specific, the along-track slope of the weak beam was inversed by the slope\u2013noise relationship obtained from strong beam data, and then was used to rotate the direction of the searching neighborhood in the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm. With the help of this process, the number of signal photons included in the searching neighborhood will significantly increase in mountainous areas and will be easily detected from the measured noisy photons. The proposed algorithm was tested in the Tibetan Plateau, the Altun Mountains, and the Tianshan Mountains in different seasons, and the extraction results were compared with the results from the ATL03 datasets, the ATL08 datasets, and the classical DBSCAN algorithm. Based on the ground-truth signal photons obtained by visual inspection, the parameters of the classification precision, recall, and F-score of our algorithm and three other algorithms were calculated. The modified DBSCAN could achieve a good balance between the classification precision (93.49% averaged) and recall (89.34% averaged), and its F-score (more than 0.91) was higher than that of the other three methods, which successfully obtained a continuous surface profile from weak beam data with very low SNRs. In the future, the detected signal photons from weak beam data are promising to assess the elevation accuracy achieved by ICESat-2, estimate the along-track and cross-track slope, and further obtain the ground control points (GCPs) for stereo-mapping satellites in mountainous areas.<\/jats:p>","DOI":"10.3390\/rs13050863","type":"journal-article","created":{"date-parts":[[2021,2,26]],"date-time":"2021-02-26T04:36:24Z","timestamp":1614314184000},"page":"863","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":35,"title":["Signal Photon Extraction Method for Weak Beam Data of ICESat-2 Using Information Provided by Strong Beam Data in Mountainous Areas"],"prefix":"10.3390","volume":"13","author":[{"given":"Zhiyu","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Electronic Information, Wuhan University, Wuhan 430072, China"}]},{"given":"Xinyuan","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Electronic Information, Wuhan University, Wuhan 430072, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1241-8650","authenticated-orcid":false,"given":"Yue","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Electronic Information, Wuhan University, Wuhan 430072, China"},{"name":"School of Science, University of New South Wales, Canberra, BC 2610, Australia"}]},{"given":"Nan","family":"Xu","sequence":"additional","affiliation":[{"name":"College of Marine Science and Engineering, Nanjing Normal University, Nanjing 210023, China"}]},{"given":"Wenhao","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Electronic Information, Wuhan University, Wuhan 430072, China"}]},{"given":"Song","family":"Li","sequence":"additional","affiliation":[{"name":"School of Electronic Information, Wuhan University, Wuhan 430072, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,2,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1109\/TGRS.2006.887172","article-title":"Precision and accuracy of satellite radar and laser altimeter data over the continental ice sheets","volume":"45","author":"Brenner","year":"2007","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"3634","DOI":"10.1002\/jgrc.20266","article-title":"Sea ice freeboard in McMurdo Sound, Antarctica, derived by surface-validated ICESat laser altimeter data","volume":"118","author":"Price","year":"2013","journal-title":"J. Geophys. Res. Ocean."},{"key":"ref_3","first-page":"G02S03","article-title":"Characterization of ICESat\/GLAS waveforms over terrestrial ecosystems: Implications for vegetation mapping","volume":"113","author":"Neuenschwander","year":"2008","journal-title":"J. Geophys. Res."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2210","DOI":"10.3390\/rs4082210","article-title":"Influence of surface topography on ICESat\/GLAS forest height estimation and waveform shape","volume":"4","author":"Hilbert","year":"2012","journal-title":"Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Hajj, M.E., Baghdadi, N., Fayad, I., Vieilledent, G., Bailly, J.-S., and Minh, D.H.T. (2017). Interest of integrating spaceborne LiDAR data to improve the estimation of biomass in high biomass forested areas. Remote Sens., 9.","DOI":"10.3390\/rs9030213"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"L23S10","DOI":"10.1029\/2005GL024306","article-title":"ICESat sea level comparisons","volume":"32","author":"Urban","year":"2005","journal-title":"Geophys. Res. Lett."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"L21S01","DOI":"10.1029\/2005GL024009","article-title":"Overview of the ICESat Mission","volume":"32","author":"Schutz","year":"2005","journal-title":"Geophys. Res. Lett."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"L21S02","DOI":"10.1029\/2005GL024028","article-title":"Geoscience Laser Altimeter System (GLAS) on the ICESat mission: On-orbit measurement performance","volume":"32","author":"Abshire","year":"2005","journal-title":"Geophys. Res. Lett."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Neuenschwander, A.L., and Magruder, L.A. (2019). Canopy and terrain height retrievals with ICESat-2: A first look. Remote Sens., 11.","DOI":"10.3390\/rs11141721"},{"key":"ref_10","unstructured":"Neeck, S.P., Kimura, T., and Martimort, P. (2019). ICESat-2 mission overview and early performance. Sensors, Systems, and Next-Generation Satellites XXIII, SPIE."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1016\/j.rse.2016.12.029","article-title":"The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2): Science requirements, concept, and implementation","volume":"190","author":"Markus","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Tang, H., Swatantran, A., Barrett, T., DeCola, P., and Dubayah, R. (2016). Voxel-based spatial filtering method for canopy height retrieval from airborne single-photon lidar. Remote Sens., 8.","DOI":"10.3390\/rs8090771"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1258","DOI":"10.1109\/LGRS.2017.2704917","article-title":"An adaptive ellipsoid searching filter for airborne single-photon lidar","volume":"14","author":"Wang","year":"2017","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"455","DOI":"10.14358\/PERS.82.7.455","article-title":"First evaluation on single photon-sensitive lidar data","volume":"82","author":"Li","year":"2016","journal-title":"Photogramm. Eng. Remote Sens"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2170","DOI":"10.1109\/TPAMI.2007.1122","article-title":"Bayesian analysis of lidar signals with multiple returns","volume":"29","author":"Wallace","year":"2007","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"445","DOI":"10.1109\/TCI.2017.2706028","article-title":"A Few photons among many: Unmixing signal and noise for photon-efficient active imaging","volume":"3","author":"Rapp","year":"2017","journal-title":"IEEE Trans. Comput. Imag."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Magruder, L.A., Wharton, M.E., Stout, K.D., and Neuenschwander, A.L. (2012). Noise filtering techniques for photon-counting Ladar data. SPIE Defense, Security, and Sensing. International Society for Optics and Photonics, SPIE.","DOI":"10.1117\/12.919139"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1151","DOI":"10.1175\/JTECH-D-13-00120.1","article-title":"Profiling sea ice with a Multiple Altimeter Beam Experimental Lidar (MABEL)","volume":"31","author":"Kwok","year":"2014","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2109","DOI":"10.1109\/TGRS.2013.2258350","article-title":"Algorithm for detection of ground and canopy cover in micropulse photon-counting lidar altimeter data in preparation for the ICESat-2 mission","volume":"52","author":"Herzfeld","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"5263","DOI":"10.1080\/01431161.2014.939780","article-title":"Applicability of an automatic surface detection approach to micro-pulse photon-counting lidar altimetry data: Implications for canopy height retrieval from future ICESat-2 data","volume":"35","author":"Moussavi","year":"2014","journal-title":"Int. J. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1016\/j.isprsjprs.2016.04.009","article-title":"Prospects of the ICESat-2 laser altimetry mission for Savanna ecosystem structural studies based on airborne simulation data","volume":"118","author":"Gwenzi","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1874","DOI":"10.1109\/TGRS.2016.2617323","article-title":"Surface-height determination of crevassed glaciers\u2014Mathematical principles of an autoadaptive density-dimension algorithm and validation using ICESat-2 simulator (SIMPL) data","volume":"55","author":"Herzfeld","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1016\/j.rse.2018.02.019","article-title":"Photon counting LiDAR: An adaptive ground and canopy height retrieval algorithm for ICESat-2 data","volume":"208","author":"Popescu","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/j.rse.2018.11.005","article-title":"The ATL08 land and vegetation product for the ICESat-2 Mission","volume":"221","author":"Neuenschwander","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"111352","DOI":"10.1016\/j.rse.2019.111352","article-title":"Land ice height-retrieval algorithm for NASA\u2019s ICESat-2 photon-counting laser altimeter","volume":"233","author":"Smith","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Liu, M., Popescu, S., and Malambo, L. (2019). Feasibility of burned area mapping based on ICESAT\u22122 photon counting data. Remote Sens., 12.","DOI":"10.3390\/rs12010024"},{"key":"ref_27","unstructured":"Neuenschwander, A.L., Pitts, K.L., Jelley, B.P., Robbins, J., Klotz, B., Popescu, S.C., Nelson, R.F., Harding, D., Pederson, D., and Sheridan, R. (2020). ICE, CLOUD, and Land Elevation Satellite-2 (ICESat-2) Algorithm Theoretical Basis Document (ATBD) for Land-Vegetation Along-Track Products(ATL08), Land\/Vegetation SDT Team Members and ICESat-2 Project Science Office."},{"key":"ref_28","unstructured":"Morison, J., Hancock, D., Dickinson, J., Robbins, T., Roberts, L., Kwok, R., Palm, S., Jasinski, M., Plant, B., and Urban, T. (2020). ICE, CLOUD, and Land Elevation Satellite-2 (ICESat-2) Project Algorithm Theoretical Basis Document (ATBD) for Ocean Surface Height (ATL12), Goddard Space Flight Center."},{"key":"ref_29","unstructured":"Jasinski, M., Stoll, J., Hancock, D., Robbins, J., Nattala, J., Morison, J., Jones, B., Ondrusek, M., Pavelsky, T., and Parrish, C. (2020). ICE, CLOUD, and Land Elevation Satellite-2 (ICESat-2) Project Algorithm Theoretical Basis Document (ATBD) for Inland Water Data Products (ATL13), Goddard Space Flight Center."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Malambo, L., and Popescu, S.C. (2020). PhotonLabeler: An inter-disciplinary platform for bisual interpretation and labeling of ICESat-2 geolocated photon data. Remote Sens., 12.","DOI":"10.20944\/preprints202008.0293.v1"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"947","DOI":"10.1109\/LGRS.2016.2555308","article-title":"A novel noise filtering model for photon-counting laser altimeter data","volume":"13","author":"Wang","year":"2016","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_32","unstructured":"Zhang, J., Kerekes, J., Csatho, B., Schenk, T., and Wheelwright, R. (2014, January 13\u201318). A clustering approach for detection of ground in micropulse photon-counting LiDAR altimeter data. Proceedings of the IEEE Geoscience and Remote Sensing Symposium, Quebec City, QC, Canada."},{"key":"ref_33","unstructured":"Ester, M., Kriegel, H.-P., Sander, J., and Xu, X. (1996, January 2\u20134). A density-based algorithm for discovering clusters in large spatial databases with noise. Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD-96), Portland, OR, USA."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Ma, Y., Zhang, W., Sun, J., Li, G., Wang, X., Li, S., and Xu, N. (2019). Photon-counting lidar: An adaptive signal detection method for different land cover types in coastal areas. Remote Sens., 11.","DOI":"10.3390\/rs11040471"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"A520","DOI":"10.1364\/OE.26.00A520","article-title":"Estimating the vegetation canopy height using micro-pulse photon-counting LiDAR data","volume":"26","author":"Nie","year":"2018","journal-title":"Opt. Express"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Zhu, X., Nie, S., Wang, C., Xi, X., and Hu, Z. (2018). A ground elevation and vegetation height retrieval algorithm using micro-pulse photon-counting Lidar data. Remote Sens., 10.","DOI":"10.3390\/rs10121962"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Zhu, X., Nie, S., Wang, C., Xi, X., Wang, J., Li, D., and Zhou, H. (2020). A noise removal algorithm based on OPTICS for photon-counting LiDAR data. IEEE Geosci. Remote Sens. Lett.","DOI":"10.1109\/LGRS.2020.3003191"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Huang, J., Xing, Y., You, H., Qin, L., Tian, J., and Ma, J. (2019). Particle swarm optimization-based noise filtering algorithm for photon cloud data in forest area. Remote Sens., 11.","DOI":"10.3390\/rs11080980"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1707","DOI":"10.5194\/tc-10-1707-2016","article-title":"MABEL photon-counting laser altimetry data for ICESat-2 simulations and development","volume":"10","author":"Brunt","year":"2016","journal-title":"Cryosphere"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"111325","DOI":"10.1016\/j.rse.2019.111325","article-title":"The Ice, Cloud, and Land Elevation Satellite-2 mission: A global geolocated photon product derived from the Advanced Topographic Laser Altimeter System","volume":"233","author":"Neumann","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_41","unstructured":"Itzler, M.A., McIntosh, K.A., and Bienfang, J.C. (2019). IceSat-2 ATLAS photon-counting receiver: Initial on-orbit performance. Advanced Photon Counting Techniques XIII, SPIE."},{"key":"ref_42","unstructured":"Neumann, T.A., Brenner, A., Hancock, D., Robbins, J., Saba, J., Harbeck, K., Gibbons, A., Lee, J., Luthcke, S.B., and Rebold, T. (2020). ATLAS\/ICESat-2 L2A Global Geolocated Photon Data, Version 3."},{"key":"ref_43","unstructured":"Neumann, T., Brenner, A., Hancock, D., Robbins, J., Saba, J., Harbeck, K., and Gibbons, A. (2019). ICE, CLOUD, and Land Elevation Satellite-2 (ICESat-2) Project Algorithm Theoretical Basis Document (ATBD) for Global Geolocated Photons ATL03, Goddard Space Flight Center."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1175\/JTECH-D-12-00076.1","article-title":"The Multiple Altimeter Beam Experimental Lidar (MABEL): An Airborne Simulator for the ICESat-2 Mission","volume":"30","author":"McGill","year":"2013","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_45","unstructured":"Neuenschwander, A.L., Pitts, K.L., Jelley, B.P., Robbins, J., Klotz, B., Popescu, S.C., Nelson, R.F., Harding, D., Pederson, D., and Sheridan, R. (2020). ATLAS\/ICESat-2 L3A Land and Vegetation Height, Version 3."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1016\/S0264-3707(02)00045-5","article-title":"Photon-counting multikilohertz microlaser altimeters for airborne and spaceborne topographic measurements","volume":"34","author":"Degnan","year":"2002","journal-title":"J. Geodyn."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"A861","DOI":"10.1364\/OE.27.00A861","article-title":"Ranging performance models based on negative-binomial (NB) distribution for photon-counting lidars","volume":"27","author":"Li","year":"2019","journal-title":"Opt. Express"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"448","DOI":"10.1364\/AO.21.000448","article-title":"Target signatures for laser altimeters: An analysis","volume":"21","author":"Gardner","year":"1982","journal-title":"Appl. Opt."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"6542","DOI":"10.1109\/TGRS.2019.2907230","article-title":"Characterizing the system impulse response function from photon-counting LiDAR data","volume":"57","author":"Greeley","year":"2019","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"3261","DOI":"10.1364\/AO.48.003261","article-title":"Geiger-mode avalanche photodiode ladar receiver performance characteristics and detection statistics","volume":"48","author":"Gatt","year":"2009","journal-title":"Appl. Opt."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"15924","DOI":"10.1364\/OE.26.015924","article-title":"Theoretical ranging performance model and range walk error correction for photon-counting lidars with multiple detectors","volume":"26","author":"Ma","year":"2018","journal-title":"Opt. Express"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"16030","DOI":"10.1364\/OE.392904","article-title":"Land and snow-covered area classification method based on the background noise for satellite photon-counting laser altimeters","volume":"28","author":"Zhang","year":"2020","journal-title":"Opt. Express"},{"key":"ref_53","unstructured":"Heris, M.K. (2015). DBSCAN Clustering in MATLAB, Yarpiz. Available online: https:\/\/yarpiz.com\/255\/ypml110-dbscan-clustering."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"296","DOI":"10.1197\/jamia.M1733","article-title":"Agreement, the F-measure, and reliability in information retrieval","volume":"12","author":"Hripcsak","year":"2005","journal-title":"J. Am. Med. Inform. Assoc."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"112110","DOI":"10.1016\/j.rse.2020.112110","article-title":"Validation of ICESat-2 terrain and canopy heights in boreal forests","volume":"251","author":"Neuenschwander","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Tian, X., and Shan, J. (2021). Comprehensive evaluation of the ICESat-2 ATL08 terrain product. IEEE Trans. Geosci. Remote Sens.","DOI":"10.1109\/TGRS.2021.3051086"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"e2020GL090572","DOI":"10.1029\/2020GL090572","article-title":"Comparisons of satellite and airborne altimetry with ground-based data from the interior of the Antarctic ice sheet","volume":"48","author":"Brunt","year":"2020","journal-title":"Geophys. Res. Lett."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"e2020GL090708","DOI":"10.1029\/2020GL090708","article-title":"Mapping Sea Ice Surface Topography in High Fidelity with ICESat-2","volume":"47","author":"Farrell","year":"2020","journal-title":"Geophys. Res. Lett."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1111\/phor.12138","article-title":"ZY-3 Block adjustment supported by GLAS laser altimetry data","volume":"31","author":"Li","year":"2016","journal-title":"Photogramm. Rec."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/5\/863\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:28:51Z","timestamp":1760160531000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/5\/863"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,2,25]]},"references-count":59,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2021,3]]}},"alternative-id":["rs13050863"],"URL":"https:\/\/doi.org\/10.3390\/rs13050863","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,2,25]]}}}