{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T02:47:38Z","timestamp":1772765258185,"version":"3.50.1"},"reference-count":45,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2023,7,24]],"date-time":"2023-07-24T00:00:00Z","timestamp":1690156800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["42074016"],"award-info":[{"award-number":["42074016"]}]},{"name":"National Natural Science Foundation of China","award":["42030112"],"award-info":[{"award-number":["42030112"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The TanDEM-X Digital Elevation Model (DEM) is limited by the radar side-view imaging mode, which still has gaps and anomalies that directly affect the application potential of the data. Many methods have been used to improve the accuracy of TanDEM-X DEM, but these algorithms primarily focus on eliminating systematic errors trending over a large area in the DEM, rather than random errors. Therefore, this paper presents the least-squares collocation-based error correction algorithm (LSC-TXC) for TanDEM-X DEM, which effectively eliminates both systematic and random errors, to enhance the accuracy of TanDEM-X DEM. The experimental results demonstrate that TanDEM-X DEM corrected by the LSC-TXC algorithm reduces the root mean square error (RMSE) from 6.141 m to 3.851 m, resulting in a significant improvement in accuracy (by 37.3%). Compared to three conventional algorithms, namely Random Forest, Height Difference Fitting Neural Network and Back Propagation in Neural Network, the presented algorithm demonstrates a reduction in the RMSEs of the corrected TanDEM-X DEMs by 6.5%, 7.6%, and 18.1%, respectively. This algorithm provides an efficient tool for correcting DEMs such as TanDEM-X for a wide range of areas.<\/jats:p>","DOI":"10.3390\/rs15143695","type":"journal-article","created":{"date-parts":[[2023,7,25]],"date-time":"2023-07-25T01:27:32Z","timestamp":1690248452000},"page":"3695","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Improving the Accuracy of TanDEM-X Digital Elevation Model Using Least Squares Collocation Method"],"prefix":"10.3390","volume":"15","author":[{"given":"Xingdong","family":"Shen","sequence":"first","affiliation":[{"name":"College of Computer and Information Engineering & College of Science, Central South University of Forestry and Technology, Changsha 410004, China"}]},{"given":"Cui","family":"Zhou","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering & College of Science, Central South University of Forestry and Technology, Changsha 410004, China"}]},{"given":"Jianjun","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Geosciences and Info-Physics, Central South University, Changsha 410083, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,7,24]]},"reference":[{"key":"ref_1","first-page":"1305","article-title":"Research progress of digital elevation model and digital terrain analysis in China","volume":"69","author":"Tang","year":"2014","journal-title":"Acta Geogr. Sin."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"130878","DOI":"10.1109\/ACCESS.2020.3009851","article-title":"An adaptive terrain-dependent method for SRTM DEM correction over mountainous areas","volume":"8","author":"Zhou","year":"2020","journal-title":"IEEE Access"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Lee, H., and Hahn, M. (2019). KOMPSAT-3 digital elevation model correction based on point-to-surface matching. Remote Sens., 11.","DOI":"10.3390\/rs11202340"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1016\/j.isprsjprs.2017.09.014","article-title":"DEM generation from contours and a low-resolution DEM","volume":"134","author":"Li","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"220","DOI":"10.3189\/002214308784886162","article-title":"Performance of ASTER and SRTM DEMs, and their potential for assessing glacial lakes in the Lunana region, Bhutan Himalaya","volume":"54","author":"Fujita","year":"2008","journal-title":"J. Glaciol."},{"key":"ref_6","unstructured":"Tadono, T., Takaku, J., Tsutsui, K., Oda, F., and Nagai, H. (2015, January 26\u201331). Status of \u201cALOS World 3D (AW3D)\u201d global DSM generation. Proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Milan, Italy."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Zhao, S., Liu, J., Cheng, W., and Zhou, C. (2022). Fusion Scheme and Implementation Based on SRTM1, ASTER GDEM V3, and AW3D30. ISPRS Int. J. Geo-Inf., 11.","DOI":"10.3390\/ijgi11030207"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.isprsjprs.2017.08.008","article-title":"Generation and performance assessment of the global TanDEM-X digital elevation model","volume":"132","author":"Rizzoli","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_9","first-page":"594","article-title":"Influence of Resolutions of DEM on the Error of Slope","volume":"38","author":"Chen","year":"2013","journal-title":"Geomat. Inf. Sci. Wuhan Univ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"706","DOI":"10.1080\/2150704X.2018.1468098","article-title":"Comparative accuracy of the AW3D30 DSM, ASTER GDEM, and SRTM1 DEM: A case study on the Zaoksky testing ground, Central European Russia","volume":"9","author":"Florinsky","year":"2018","journal-title":"Remote Sens. Lett."},{"key":"ref_11","first-page":"625","article-title":"InSAR-Based Digital Elevation Model (DEM) Improvement Using Data Fusion Technique with Neural Networks on Diverse Topographic Indian Regions","volume":"4","author":"Girohi","year":"2022","journal-title":"Authorea Prepr."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"820","DOI":"10.3390\/ai3040050","article-title":"A Neural Network-Based Fusion Approach for Improvement of SAR Interferometry-Based Digital Elevation Models in Plain and Hilly Regions of India","volume":"3","author":"Girohi","year":"2022","journal-title":"AI"},{"key":"ref_13","first-page":"487","article-title":"A High Precision DEM Generation Method Based on Ascending and Descending Pass TerraSAR-X\/TanDEM-X BiSAR Data","volume":"7","author":"Qin","year":"2018","journal-title":"J. Radars"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Podg\u00f3rski, J., Kinnard, C., P\u0119tlicki, M., and Urrutia, R. (2019). Performance Assessment of TanDEM-X DEM for Mountain Glacier Elevation Change Detection. Remote Sens., 11.","DOI":"10.3390\/rs11020187"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"111777","DOI":"10.1016\/j.rse.2020.111777","article-title":"Which heterogeneous glacier melting patterns can be robustly observed from space? A multi-scale assessment in southeastern Tibetan Plateau","volume":"242","author":"Ke","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Wu, Q., Song, C., Liu, K., and Ke, L. (2020). Integration of TanDEM-X and SRTM DEMs and spectral imagery to improve the large-scale detection of opencast mining areas. Remote Sens., 12.","DOI":"10.3390\/rs12091451"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"111437","DOI":"10.1016\/j.rse.2019.111437","article-title":"Water storage estimation in ungauged small reservoirs with the TanDEM-X DEM and multi-source satellite observations","volume":"235","author":"Vanthof","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_18","first-page":"2277","article-title":"Error spatial distribution characteristics of TanDEM-X 90m DEM over China","volume":"22","author":"Li","year":"2020","journal-title":"J. Geo-Inf. Sci."},{"key":"ref_19","first-page":"111","article-title":"Accuracy Assessment of Alos W3d30, Aster Gdem and Srtm30 Dem: A Case Study of Nigeria, West Africa","volume":"11","author":"Apeh","year":"2019","journal-title":"J. Geogr. Inf. Syst."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Kim, D.E., Liong, S.Y., Gourbesville, P., Andres, L., and Liu, J. (2020). Simple-yet-effective SRTM DEM improvement scheme for dense urban cities using ANN and remote sensing data: Application to flood modeling. Water, 12.","DOI":"10.3390\/w12030816"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1515\/jag-2018-0050","article-title":"Using direct transformation approach as an alternative technique to fuse global digital elevation models with GPS\/levelling measurements in Egypt","volume":"13","author":"Elshambaky","year":"2019","journal-title":"J. Appl. Geod."},{"key":"ref_22","first-page":"205","article-title":"Study on DEM Fusion Methods Based on InSAR Technology in Complex Terrain Areas","volume":"44","author":"Yue","year":"2021","journal-title":"Geomat. Spat. Inf. Technol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.rse.2015.11.018","article-title":"Improving the TanDEM-X Digital Elevation Model for flood modelling using flood extents from Synthetic Aperture Radar images","volume":"173","author":"Mason","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Kim, D.E., Liu, J., Liong, S.Y., Gourbesville, P., and Strunz, G. (2021). Satellite DEM improvement using multispectral imagery and an artificial neural network. Water, 13.","DOI":"10.3390\/w13111551"},{"key":"ref_25","first-page":"7","article-title":"Vertical deformation analysis of adaptive fusion of GNSS level elevation change","volume":"45","author":"Guo","year":"2020","journal-title":"Geomat. Inf. Sci. Wuhan Univ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1080\/00396265.2018.1525981","article-title":"Precise local quasigeoid modelling using GNSS\/levelling height anomalies and gravity data","volume":"52","author":"Trojanowicz","year":"2020","journal-title":"Surv. Rev."},{"key":"ref_27","first-page":"127","article-title":"Application of combination model of quadric surfaces and least squares collocation in GPS height anomaly fitting","volume":"5","author":"Zhang","year":"2020","journal-title":"Bull. Surv. Mapp."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Rehman, K., Fareed, N., and Chu, H.-J. (2023). NASA ICESat-2: Space-Borne LiDAR for Geological Education and Field Mapping of Aeolian Sand Dune Environments. Remote Sens., 15.","DOI":"10.3390\/rs15112882"},{"key":"ref_29","unstructured":"Jin, G., Xu, Q., and Zhang, H. (2014). Synthetic Aperture Radar Interferometry, National Defense Industry Press."},{"key":"ref_30","first-page":"102438","article-title":"Orbit error removal in InSAR\/MTInSAR with a patch-based polynomial model","volume":"102","author":"Du","year":"2021","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_31","unstructured":"Zhang, Q., Zhang, J., and Yue, D. (2011). Modern Measurement Data Processing and Application, Surveying and Mapping Press."},{"key":"ref_32","first-page":"3089","article-title":"Generation of high precision DEM from TerraSAR-X\/TanDEM-X","volume":"58","author":"Du","year":"2015","journal-title":"Chin. J. Geophys."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.isprsjprs.2012.06.002","article-title":"Operational TanDEM-X DEM calibration and first validation results","volume":"73","author":"Gruber","year":"2012","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_34","first-page":"4011505","article-title":"Improved DEM reconstruction method based on multibaseline InSAR","volume":"19","author":"Zhang","year":"2021","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"421","DOI":"10.1029\/RG016i003p00421","article-title":"Least-squares collocation","volume":"16","author":"Helmut","year":"1978","journal-title":"Rev. Geophys."},{"key":"ref_36","first-page":"16","article-title":"Study on deformation and strain characteristics of Yunnan region based on least squares configuration","volume":"46","author":"Xu","year":"2021","journal-title":"Sci. Surv. Mapp."},{"key":"ref_37","first-page":"958","article-title":"Dynamic analysis of crust deformation in Xinjiang under least squares configuration","volume":"57","author":"Deng","year":"2022","journal-title":"Chin. J. Geol."},{"key":"ref_38","first-page":"53","article-title":"Regional gravity field model constructed by the Least squares collocation","volume":"42","author":"Ruan","year":"2020","journal-title":"Acta Seismol. Sin."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2478\/congeo-2013-0001","article-title":"Two covariance models in Least Squares Collocation (LSC) tested in interpolation of local topography","volume":"43","year":"2013","journal-title":"Contrib. Geophys. Geod."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"111724","DOI":"10.1016\/j.rse.2020.111724","article-title":"Accuracy assessment of the global TanDEM-X digital elevation model in a mountain environment","volume":"241","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_41","first-page":"646","article-title":"Vertical accuracy assessment and applicability analysis of TanDEM-X 90 m DEM in China","volume":"23","author":"Yu","year":"2021","journal-title":"J. Geo-Inf. Sci."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Chen, C., Yang, S., and Li, Y. (2020). Accuracy assessment and correction of SRTM DEM using ICESat\/GLAS data under data coregistration. Remote Sens., 12.","DOI":"10.3390\/rs12203435"},{"key":"ref_43","first-page":"854","article-title":"A Multi-source DEM Fusion Method Based on Elevation Difference Fitting Neural Network","volume":"47","author":"Shen","year":"2018","journal-title":"Acta Geod. Et Cartogr. Sin."},{"key":"ref_44","first-page":"2789","article-title":"An Improved BPNN Prediction Method Based on Multi-Strategy Sparrow Search Algorithm","volume":"74","author":"Tang","year":"2023","journal-title":"Comput. Mater. Contin."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/j.isprsjprs.2019.04.008","article-title":"Normalization of the temporal effect on the MODIS land surface temperature product using random forest regression","volume":"152","author":"Zhao","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/14\/3695\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T20:18:00Z","timestamp":1760127480000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/14\/3695"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,24]]},"references-count":45,"journal-issue":{"issue":"14","published-online":{"date-parts":[[2023,7]]}},"alternative-id":["rs15143695"],"URL":"https:\/\/doi.org\/10.3390\/rs15143695","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,7,24]]}}}