{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T01:53:19Z","timestamp":1780537999301,"version":"3.54.1"},"reference-count":60,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2020,10,12]],"date-time":"2020-10-12T00:00:00Z","timestamp":1602460800000},"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":["41930102"],"award-info":[{"award-number":["41930102"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41971333"],"award-info":[{"award-number":["41971333"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012246","name":"Priority Academic Program Development of Jiangsu Higher Education Institutions","doi-asserted-by":"publisher","award":["164320H116"],"award-info":[{"award-number":["164320H116"]}],"id":[{"id":"10.13039\/501100012246","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Accurate topographic mapping is a critical task for various environmental applications because elevation affects hydrodynamics and vegetation distributions. UAV photogrammetry is popular in terrain modelling because of its lower cost compared to laser scanning. However, this method is restricted in vegetation area with a complex terrain, due to reduced ground visibility and lack of robust and automatic filtering algorithms. To solve this problem, this work proposed an ensemble method of deep learning and terrain correction. First, image matching point cloud was generated by UAV photogrammetry. Second, vegetation points were identified based on U-net deep learning network. After that, ground elevation was corrected by estimating vegetation height to generate the digital terrain model (DTM). Two scenarios, namely, discrete and continuous vegetation areas were considered. The vegetation points in the discrete area were directly removed and then interpolated, and terrain correction was applied for the points in the continuous areas. Case studies were conducted in three different landforms in the loess plateau of China, and accuracy assessment indicated that the overall accuracy of vegetation detection was 95.0%, and the MSE (Mean Square Error) of final DTM (Digital Terrain Model) was 0.024 m.<\/jats:p>","DOI":"10.3390\/rs12203318","type":"journal-article","created":{"date-parts":[[2020,10,14]],"date-time":"2020-10-14T21:24:39Z","timestamp":1602710679000},"page":"3318","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["UAV-Based Terrain Modeling under Vegetation in the Chinese Loess Plateau: A Deep Learning and Terrain Correction Ensemble Framework"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6696-975X","authenticated-orcid":false,"given":"Jiaming","family":"Na","sequence":"first","affiliation":[{"name":"Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Nanjing 210023, China"},{"name":"School of Geography, Nanjing Normal University, Nanjing 210023, China"},{"name":"Department of Geodesy and Geoinformation, TU Wien, 1040 Vienna, Austria"},{"name":"Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing Normal University, Nanjing 210023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kaikai","family":"Xue","sequence":"additional","affiliation":[{"name":"Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing Normal University, Nanjing 210023, China"},{"name":"Northwest Engineering Corporation Limited, Power Construction Corporation of China (POWERCHINA), Xi\u2019an 710065, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7930-3319","authenticated-orcid":false,"given":"Liyang","family":"Xiong","sequence":"additional","affiliation":[{"name":"Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Nanjing 210023, China"},{"name":"School of Geography, Nanjing Normal University, Nanjing 210023, China"},{"name":"Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing Normal University, Nanjing 210023, China"},{"name":"State Key Laboratory Cultivation Base of Geographical Environment Evolution, Nanjing Normal University, Nanjing 210023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guoan","family":"Tang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Nanjing 210023, China"},{"name":"School of Geography, Nanjing Normal University, Nanjing 210023, China"},{"name":"Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing Normal University, Nanjing 210023, China"},{"name":"State Key Laboratory Cultivation Base of Geographical Environment Evolution, Nanjing Normal University, Nanjing 210023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5695-5485","authenticated-orcid":false,"given":"Hu","family":"Ding","sequence":"additional","affiliation":[{"name":"School of Geography, South China Normal University, Guangzhou 510631, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6234-9812","authenticated-orcid":false,"given":"Josef","family":"Strobl","sequence":"additional","affiliation":[{"name":"Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing Normal University, Nanjing 210023, China"},{"name":"Department of Geoinformatics\u2013Z_GIS, University of Salzburg, Salzburg 5020, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2348-7929","authenticated-orcid":false,"given":"Norbert","family":"Pfeifer","sequence":"additional","affiliation":[{"name":"Department of Geodesy and Geoinformation, TU Wien, 1040 Vienna, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,10,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"173","DOI":"10.15287\/afr.2016.719","article-title":"Airborne lidar remote sensing applications in non-forested short stature environments: A review","volume":"60","author":"Kulawardhana","year":"2017","journal-title":"Ann. For. Res."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"553","DOI":"10.1111\/cgf.13657","article-title":"A Review of Digital Terrain Modeling","volume":"38","author":"Galin","year":"2019","journal-title":"Comput. Graph. Forum"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Tmu\u0161i\u0107, G., Manfreda, S., Aasen, H., James, M.R., Gon\u00e7alves, G., Ben Dor, E., Brook, A., Polinova, M., Arranz, J.J., and M\u00e9sz\u00e1ros, J. (2020). Current Practices in UAS-based Environmental Monitoring. Remote Sens., 12.","DOI":"10.3390\/rs12061001"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1016\/j.rse.2012.01.018","article-title":"Accuracy assessment and correction of a LIDAR-derived salt marsh digital elevation model","volume":"121","author":"Hladik","year":"2012","journal-title":"Remote. Sens. Environ."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1016\/j.rse.2013.08.003","article-title":"Salt marsh elevation and habitat mapping using hyperspectral and LIDAR data","volume":"139","author":"Hladik","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Tsouros, D.C., Bibi, S., and Sarigiannidis, P.G. (2019). A review on UAV-based applications for precision agriculture. Information, 10.","DOI":"10.3390\/info10110349"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Szab\u00f3, Z., T\u00f3th, C.A., Holb, I., and Szabo, S. (2020). Aerial Laser Scanning Data as a Source of Terrain Modeling in a Fluvial Environment: Biasing Factors of Terrain Height Accuracy. Sensors, 20.","DOI":"10.3390\/s20072063"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Liu, K., Ding, H., Tang, G., Na, J., Huang, X., Xue, Z., Yang, X., and Li, F. (2016). Detection of Catchment-Scale Gully-Affected Areas Using Unmanned Aerial Vehicle (UAV) on the Chinese Loess Plateau. ISPRS Int. J. Geo-Inf., 5.","DOI":"10.3390\/ijgi5120238"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1016\/j.earscirev.2017.05.005","article-title":"Comparison of soil erosion models used to study the Chinese Loess Plateau","volume":"170","author":"Li","year":"2017","journal-title":"Earth-Science Rev."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/S0924-2716(99)00039-8","article-title":"State-of-the-art of elevation extraction from satellite SAR data","volume":"55","author":"Toutin","year":"2000","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1016\/j.isprsjprs.2006.05.003","article-title":"Validation of digital elevation models from SRTM X-SAR for applications in hydrologic modeling","volume":"60","author":"Ludwig","year":"2006","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"3219","DOI":"10.1109\/TGRS.2006.879544","article-title":"Imaging Simulation of Polarimetric SAR for a Comprehensive Terrain Scene Using the Mapping and Projection Algorithm","volume":"44","author":"Xu","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1170","DOI":"10.1109\/TGRS.2015.2476352","article-title":"Terrain and Surface Modeling Using Polarimetric SAR Data Features","volume":"54","author":"Sabry","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1109\/36.210443","article-title":"Micro pulse lidar","volume":"31","author":"Spinhirne","year":"1993","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Shan, J., and Toth, C.K. (2018). Introduction to Laser Ranging, Profiling, and Scanning. Topographic Laser Ranging And Scanning: Principles And Processing, CRC Press. [2nd ed.].","DOI":"10.1201\/9781315154381"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Milenkovi\u0107, M., Ressl, C., Piermattei, L., Mandlburger, G., and Pfeifer, N. (2018). Roughness Spectra Derived from Multi-Scale LiDAR Point Clouds of a Gravel Surface: A Comparison and Sensitivity Analysis. ISPRS Int. J. Geo-Information, 7.","DOI":"10.3390\/ijgi7020069"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1016\/0031-8663(84)90016-4","article-title":"Automatic stereophotogrammetry: A method based on feature detection and dynamic programming","volume":"39","author":"Benard","year":"1984","journal-title":"Photogrammetria"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"559","DOI":"10.1016\/S0094-5765(01)00020-0","article-title":"The Shuttle Radar Topography Mission (SRTM): A breakthrough in remote sensing of topography","volume":"48","year":"2001","journal-title":"Acta Astronaut."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"249","DOI":"10.14358\/PERS.72.3.249","article-title":"A Global Assessment of the SRTM Performance","volume":"72","author":"Morris","year":"2006","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"3343","DOI":"10.1080\/01431160701469040","article-title":"Mapping canopy height using a combination of digital stereo-photogrammetry and lidar","volume":"29","author":"Vega","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1016\/S0924-2716(02)00047-3","article-title":"Estimating relative lidar accuracy information from overlapping flight lines","volume":"56","author":"Latypov","year":"2002","journal-title":"ISPRS J. Photogramm. Remote. Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"331","DOI":"10.14358\/PERS.70.3.331","article-title":"Accuracy of Airborne Lidar-Derived Elevation","volume":"70","author":"Hodgson","year":"2004","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Salach, A., Baku\u0142a, K., Pilarska, M., Ostrowski, W., G\u00f3rski, K., and Kurczy\u0144ski, Z. (2018). Accuracy Assessment of Point Clouds from LiDAR and Dense Image Matching Acquired Using the UAV Platform for DTM Creation. ISPRS Int. J. Geo-Inf., 7.","DOI":"10.3390\/ijgi7090342"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.envsoft.2017.05.009","article-title":"Terrestrial laser scanning improves digital elevation models and topsoil pH modelling in regions with complex topography and dense vegetation","volume":"95","author":"Baltensweiler","year":"2017","journal-title":"Environ. Model. Softw."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"322","DOI":"10.1016\/j.autcon.2018.07.020","article-title":"Comparison and utilization of point cloud generated from photogrammetry and laser scanning: 3D world model for smart heavy equipment planning","volume":"98","author":"Moon","year":"2019","journal-title":"Autom. Constr."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1065","DOI":"10.12989\/sss.2014.13.6.1065","article-title":"A review of rotorcraft Unmanned Aerial Vehicle (UAV) developments and applications in civil engineering","volume":"13","author":"Liu","year":"2014","journal-title":"Smart Struct. Syst."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1007\/s10846-017-0483-z","article-title":"Survey on Computer Vision for UAVs: Current Developments and Trends","volume":"87","author":"Kanellakis","year":"2017","journal-title":"J. Intell. Robot. Syst."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1109\/MGRS.2018.2867592","article-title":"Mini-UAV-Borne Hyperspectral Remote Sensing: From Observation and Processing to Applications","volume":"6","author":"Zhong","year":"2018","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1016\/j.isprsjprs.2017.03.017","article-title":"An accelerated image matching technique for UAV orthoimage registration","volume":"128","author":"Tsai","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"904","DOI":"10.3390\/rs9090904","article-title":"A small uav based multi-temporal image registration for dynamic agricultural terrace monitoring","volume":"9","author":"Ziquan","year":"2017","journal-title":"Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1016\/j.isprsjprs.2016.05.016","article-title":"Illumination-invariant image matching for autonomous UAV localisation based on optical sensing","volume":"119","author":"Wan","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"222","DOI":"10.1016\/j.isprsjprs.2018.06.009","article-title":"Hierarchical motion consistency constraint for efficient geometrical verification in UAV stereo image matching","volume":"142","author":"Jiang","year":"2018","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Zhao, J., Zhang, X., Gao, C., Qiu, X., Tian, Y., Zhu, Y., and Cao, W. (2019). Rapid Mosaicking of Unmanned Aerial Vehicle (UAV) Images for Crop Growth Monitoring Using the SIFT Algorithm. Remote Sens., 11.","DOI":"10.3390\/rs11101226"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.isprsjprs.2014.02.013","article-title":"Unmanned aerial systems for photogrammetry and remote sensing: A review","volume":"92","author":"Colomina","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1141","DOI":"10.1007\/s11263-019-01266-1","article-title":"The Unmanned Aerial Vehicle Benchmark: Object Detection, Tracking and Baseline","volume":"128","author":"Yu","year":"2019","journal-title":"Int. J. Comput. Vis."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/j.geomorph.2018.12.013","article-title":"3D mapping efficacy of a drone and terrestrial laser scanner over a temperate beach-dune zone","volume":"328","author":"Jackson","year":"2019","journal-title":"Geomorphology"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Meng, X., Shang, N., Zhang, X., Li, C., Zhao, K., Qiu, X., and Weeks, E. (2017). Photogrammetric UAV Mapping of Terrain under Dense Coastal Vegetation: An Object-Oriented Classification Ensemble Algorithm for Classification and Terrain Correction. Remote Sens., 9.","DOI":"10.3390\/rs9111187"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1016\/j.isprsjprs.2020.04.011","article-title":"A multi-plot assessment of vegetation structure using a micro-unmanned aerial system (UAS) in a semi-arid savanna environment","volume":"164","author":"Kolarik","year":"2020","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Jensen, J.L.R., and Mathews, A.J. (2016). Assessment of Image-Based Point Cloud Products to Generate a Bare Earth Surface and Estimate Canopy Heights in a Woodland Ecosystem. Remote Sens., 8.","DOI":"10.3390\/rs8010050"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"168","DOI":"10.1016\/j.isprsjprs.2017.02.015","article-title":"Comparison of low-altitude UAV photogrammetry with terrestrial laser scanning as data-source methods for terrain covered in low vegetation","volume":"126","author":"Matwij","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1127\/pfg\/2016\/0288","article-title":"Dense Image Matching vs. Airborne Laser Scanning\u2014Comparison of two methods for deriving terrain models","volume":"2016","author":"Ressl","year":"2016","journal-title":"Photogramm. Fernerkund. Geoinf."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Manfreda, S., McCabe, M.F., Miller, P.E., Lucas, R., Pajuelo Madrigal, V., Mallinis, G., Ben-Dor, E., Helman, D., Estes, L., and Ciraolo, G. (2018). On the Use of Unmanned Aerial Systems for Environmental Monitoring. Remote Sens., 10.","DOI":"10.20944\/preprints201803.0097.v1"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1016\/j.landusepol.2004.05.004","article-title":"Grain-for-green policy and its impacts on grain supply in West China","volume":"22","author":"Feng","year":"2005","journal-title":"Land Use Policy"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Delang, C.O., and Yuan, Z. (2016). China\u2019s Reforestation and Rural Development Programs. China\u2019s Grain for Green Program, Springer International Publishing.","DOI":"10.1007\/978-3-319-11505-4_2"},{"key":"ref_45","unstructured":"(2020, September 28). DJI Inspire 1. Available online: https:\/\/www.dji.com\/inspire-1?site=brandsite&from=landing_page."},{"key":"ref_46","unstructured":"(2020, September 28). Zenmuse X5. Available online: https:\/\/www.dji.com\/zenmuse-x5?site=brandsite&from=landing_page."},{"key":"ref_47","unstructured":"(2020, September 28). HiPer SR. Available online: https:\/\/www.topcon.co.jp\/en\/positioning\/products\/pdf\/HiPerSR_E.pdf."},{"key":"ref_48","unstructured":"(2020, September 28). Pix4D. Available online: https:\/\/www.pix4d.com\/product\/pix4dmapper-photogrammetry-software."},{"key":"ref_49","unstructured":"Chollet, F. (2017). What is deep learning?. Deep Learning with Python, Manning Publications."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"4790","DOI":"10.1364\/AO.29.004790","article-title":"Parallel distributed processing model with local space-invariant interconnections and its optical architecture","volume":"29","author":"Zhang","year":"1990","journal-title":"Appl. Opt."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"232","DOI":"10.1016\/j.matcom.2020.04.031","article-title":"Application of the residue number system to reduce hardware costs of the convolutional neural network implementation","volume":"177","author":"Valueva","year":"2020","journal-title":"Math. Comput. Simul."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Ronneberger, O., Fischer, P., and Brox, T. (2015). U-net: Convolutional networks for biomedical image segmentation. Proceedings of the 18th International Conference on Medical Image Computing and Computer-Assisted Intervention, Springer.","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref_53","first-page":"221","article-title":"Comparison of Different U-Net Models for Building Extraction from High-Resolution Aerial Imagery","volume":"7","author":"Erdem","year":"2020","journal-title":"Int. J. Environ. Geoinf."},{"key":"ref_54","unstructured":"(2020, September 28). Arcgis Pro. Available online: https:\/\/www.esri.com\/en-us\/arcgis\/products\/arcgis-pro\/overview."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Long, J., Shelhamer, E., and Darrell, T. (2015, January 8\u201310). Fully convolutional networks for semantic segmentation. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Boston, MA, USA.","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"606","DOI":"10.1109\/JSTARS.2017.2781132","article-title":"LiDAR Point Clouds to 3-D Urban Models: A Review","volume":"11","author":"Wang","year":"2018","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/j.rse.2017.04.027","article-title":"Airborne Laser Scanning for calibration and validation of inshore satellite altimetry: A proof of concept","volume":"197","author":"Zlinszky","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Kl\u00e1p\u0161t\u011b, P., Fogl, M., Bart\u00e1k, V., Gdulov, K., Urban, R., and Moudr\u00fd, V. (2020). Sensitivity analysis of parameters and contrasting performance of ground filtering algorithms with UAV photogrammetry-based and LiDAR point clouds. Int. J. Digit. Earth, 1\u201323.","DOI":"10.1080\/17538947.2020.1791267"},{"key":"ref_59","first-page":"1033","article-title":"Segmentation of objects with multi layer perceptron by using informations of window","volume":"18","author":"Kwak","year":"2007","journal-title":"J. Korean Data Inf. Sci. Soc."},{"key":"ref_60","first-page":"374","article-title":"Precision global dem generation based on adaptive surface filter and poisson terrain editing","volume":"48","author":"Han","year":"2019","journal-title":"Acta Geod. Cartogr. Sin."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/20\/3318\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:19:48Z","timestamp":1760177988000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/20\/3318"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,12]]},"references-count":60,"journal-issue":{"issue":"20","published-online":{"date-parts":[[2020,10]]}},"alternative-id":["rs12203318"],"URL":"https:\/\/doi.org\/10.3390\/rs12203318","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,10,12]]}}}