{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T09:31:25Z","timestamp":1762507885926,"version":"build-2065373602"},"reference-count":52,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2019,10,9]],"date-time":"2019-10-09T00:00:00Z","timestamp":1570579200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000192","name":"National Oceanic and Atmospheric Administration","doi-asserted-by":"publisher","award":["NOAA-NOS-NGS-2013-2003505"],"award-info":[{"award-number":["NOAA-NOS-NGS-2013-2003505"]}],"id":[{"id":"10.13039\/100000192","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Digital elevation models (DEMs) have become ubiquitous and remarkably effective in the field of earth sciences as a tool to characterize surface topography. All DEMs have a degree of inherent error and uncertainty that is propagated to subsequent models and analyses, which can lead to misinterpretation and inaccurate estimates. A new method was developed to estimate local DEM errors and implement corrections while quantifying the uncertainties of the implemented corrections. The method is based on the flexibility and ability to model complex problems with ensemble neural networks (ENNs). The method was developed to be applied to any DEM created from a corresponding set of elevation points (point cloud) and a set of ground truth measurements. The method was developed and tested using hyperspatial resolution terrestrial laser scanning (TLS) data (sub-centimeter point spacing) collected from a marsh site located along the southern portion of the Texas Gulf Coast, USA. ENNs improve the overall DEM accuracy in the study area by 68% for six model inputs and by 75% for 12 model inputs corresponding to root mean square errors (RMSEs) of 0.056 and 0.045 m, respectively. The 12-input model provides more accurate tolerance interval estimates, particularly for vegetated areas. The accuracy of the method is confirmed based on an independent data set. Although the method still underestimates the 95% tolerance interval, 8% below the 95% target, results show that it is able to quantify the spatial variability in uncertainties due to a relationship between vegetation\/land cover and accuracy of the DEM for the study area. There are still opportunities and challenges in improving and confirming the applicability of this method for different study sites and data sets.<\/jats:p>","DOI":"10.3390\/ijgi8100444","type":"journal-article","created":{"date-parts":[[2019,10,9]],"date-time":"2019-10-09T11:25:57Z","timestamp":1570620357000},"page":"444","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Ensemble Neural Networks for Modeling DEM Error"],"prefix":"10.3390","volume":"8","author":[{"given":"Chuyen","family":"Nguyen","sequence":"first","affiliation":[{"name":"College of Science and Engineering, Texas A&amp;M University-Corpus Christi, Corpus Christi, TX 78412, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7996-0594","authenticated-orcid":false,"given":"Michael J.","family":"Starek","sequence":"additional","affiliation":[{"name":"College of Science and Engineering, Texas A&amp;M University-Corpus Christi, Corpus Christi, TX 78412, USA"},{"name":"School of Engineering and Computing Sciences, Conrad Blucher Institute for Surveying and Science, Texas A&amp;M University-Corpus Christi, Corpus Christi, TX 78412, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2954-2378","authenticated-orcid":false,"given":"Philippe E.","family":"Tissot","sequence":"additional","affiliation":[{"name":"School of Engineering and Computing Sciences, Conrad Blucher Institute for Surveying and Science, Texas A&amp;M University-Corpus Christi, Corpus Christi, TX 78412, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaopeng","family":"Cai","sequence":"additional","affiliation":[{"name":"School of Engineering and Computing Sciences, Conrad Blucher Institute for Surveying and Science, Texas A&amp;M University-Corpus Christi, Corpus Christi, TX 78412, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5400-2330","authenticated-orcid":false,"given":"James","family":"Gibeaut","sequence":"additional","affiliation":[{"name":"Harte Research Institute, Texas A&amp;M University-Corpus Christi, Corpus Christi, TX 78412, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,10,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1002\/esp.479","article-title":"Editorial: The generation of high quality topographic data for hydrology and geomorphology: New data sources, new applications and new problems","volume":"28","author":"Lane","year":"2003","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1657","DOI":"10.1002\/esp.1592","article-title":"Application of a 3D laser scanner in the assessment of erosion and deposition volumes and channel change in a proglacial river","volume":"32","author":"Milan","year":"2007","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1002\/esp.1375","article-title":"Towards a protocol for laser scanning in fluvial geomorphology","volume":"32","author":"Heritage","year":"2007","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1127\/0372-8854\/2011\/0055S2-0043","article-title":"Topographic airborne LiDAR in geomorphology: A technological perspective","volume":"55","author":"Hofle","year":"2011","journal-title":"Z. Geomorphol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"300","DOI":"10.1016\/j.geomorph.2012.08.021","article-title":"\u2018Structure-from-Motion\u2019 photogrammetry: A low-cost, effective tool for geoscience applications","volume":"179","author":"Westoby","year":"2012","journal-title":"Geomorphology"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"6880","DOI":"10.3390\/rs5126880","article-title":"Using Unmanned Aerial Vehicles (UAV) for high-resolution reconstruction of topography: The structure from motion approach on coastal environments","volume":"5","author":"Mancini","year":"2013","journal-title":"Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Starek, M.J., Davis, T., Prouty, D., and Berryhill, J. (2014, January 20\u201321). Small-scale UAS for geoinformatics applications on an island campus. Proceedings of the IEEE Ubiquitous Positioning Indoor Navigation and Location Based Service (UPINLBS), Corpus Christ, TX, USA.","DOI":"10.1109\/UPINLBS.2014.7033718"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Collins, B.D., Brown, K.M., and Fairley, H.C. (2019, October 07). Evaluation of Terrestrial LIDAR for Monitoring Geomorphic Change at Archeological Sites in Grand Canyon National Park, Arizona, Available online: https:\/\/pubs.usgs.gov\/of\/2008\/1384\/.","DOI":"10.3133\/ofr20081384"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1340","DOI":"10.1130\/GES00699.1","article-title":"Modeling and analysis of landscape evolution using airborne, terrestrial, and laboratory laser scanning","volume":"7","author":"Starek","year":"2011","journal-title":"Geosphere"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1764","DOI":"10.1002\/esp.3753","article-title":"Bank erosion of legacy sediment at the transition from vertical to lateral stream incision. Earth Surface Processes and Landforms","volume":"40","author":"Lyons","year":"2015","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"805","DOI":"10.14358\/PERS.71.7.805","article-title":"Effects of terrain morphology, sampling density, and interpolation methods on grid DEM accuracy","volume":"71","author":"Aguilar","year":"2005","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Guisado-Pintado, E., Jackson, D.W., and Rogers, D. (2018). 3D mapping efficacy of a drone and terrestrial laser scanner over a temperate beach-dune zone. Geomorphology.","DOI":"10.1016\/j.geomorph.2018.12.013"},{"key":"ref_13","unstructured":"Kirk, D. (2016). Analysis of Sediment Erosion and Deposition across High Marsh and Tide Channel Sites in Well Fleet, Massachusetts. [Master\u2019s Thesis, East Carolina University]. Available online: http:\/\/hdl.handle.net\/10342\/5909."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1016\/j.geomorph.2013.10.010","article-title":"A methodological intercomparison of topographic survey techniques for characterizing wadeable streams and rivers","volume":"206","author":"Bangen","year":"2014","journal-title":"Geomorphology"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1016\/j.geomorph.2015.09.020","article-title":"Landscape-scale geomorphic change detection: Quantifying spatially variable uncertainty and circumventing legacy data issues","volume":"250","author":"Schaffrath","year":"2015","journal-title":"Geomorphology"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1369","DOI":"10.1109\/LGRS.2013.2241730","article-title":"Space-time cube representation of stream bank evolution mapped by terrestrial laser scanning","volume":"10","author":"Starek","year":"2013","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1081","DOI":"10.14358\/PERS.72.9.1081","article-title":"Quantifying DEM uncertainty and its effect on topographic parameters","volume":"72","author":"Wechsler","year":"2006","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1016\/j.geomorph.2009.06.024","article-title":"Influence of survey strategy and interpolation model on DEM quality","volume":"112","author":"Heritage","year":"2009","journal-title":"Geomorphology"},{"key":"ref_19","first-page":"1113","article-title":"Effects of various factors on the accuracy of DEMs: An intensive experimental investigation","volume":"66","author":"Gong","year":"2000","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1016\/S0016-7061(00)00081-1","article-title":"Digital elevation model resolution: Effects on terrain attribute calculation and quantitative soil-landscape modeling","volume":"100","author":"Thompson","year":"2001","journal-title":"Geoderma"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"406","DOI":"10.1016\/j.geoderma.2005.06.004","article-title":"Horizontal resolution and data density effects on remotely sensed LIDAR-based DEM","volume":"132","author":"Anderson","year":"2006","journal-title":"Geoderma"},{"key":"ref_22","unstructured":"Liu, X., Zhang, Z., Peterson, J., and Chandra, S. (2007, January 10\u201313). The effect of LiDAR data density on DEM accuracy. Proceedings of the International Congress on Modelling and Simulation (MODSIM07), Christchurch, New Zealand."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1080\/01431161.2010.515267","article-title":"Vegetation and slope effects on accuracy of a LiDAR-derived DEM in the sagebrush steppe","volume":"2","author":"Spaete","year":"2011","journal-title":"Remote Sens. Lett."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"973","DOI":"10.1002\/1096-9837(200008)25:9<973::AID-ESP111>3.0.CO;2-Y","article-title":"Monitoring and modelling morphological change in a braided gravel-bed river using high resolution GPS-based survey","volume":"25","author":"Brasington","year":"2000","journal-title":"Earth Surf. Process. Landf. J. Br. Geomorphol. Res. Group"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1016\/S0169-555X(02)00320-3","article-title":"Methodological sensitivity of morphometric estimates of coarse fluvial sediment transport","volume":"53","author":"Brasington","year":"2003","journal-title":"Geomorphology"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1002\/esp.483","article-title":"Estimation of erosion and deposition volumes in a large, gravel-bed, braided river using synoptic remote sensing","volume":"28","author":"Lane","year":"2003","journal-title":"Earth Surf. Process. Landf. J. Br. Geomorphol. Res. Group"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1176","DOI":"10.1002\/2015WR018299","article-title":"Error modeling of DEMs from topographic surveys of rivers using fuzzy inference systems","volume":"52","author":"Bangen","year":"2016","journal-title":"Water Resour. Res."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1016\/j.geomorph.2010.09.012","article-title":"Filtering spatial error from DEMs: Implications for morphological change estimation","volume":"125","author":"Milan","year":"2011","journal-title":"Geomorphology"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1116","DOI":"10.1002\/esp.3363","article-title":"Variations in multiscale curvature distribution and signatures of LiDAR DTM errors","volume":"38","author":"Sofia","year":"2013","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.cageo.2009.06.005","article-title":"Modelling the spatial distribution of DEM error with geographically weighted regression: An experimental study","volume":"36","author":"Erdogan","year":"2010","journal-title":"Comput. Geosci."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1002\/esp.1886","article-title":"Accounting for uncertainty in DEMs from repeat topographic surveys: Improved sediment budgets","volume":"35","author":"Wheaton","year":"2010","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"626","DOI":"10.1109\/TPWRS.2002.800906","article-title":"Neural network load forecasting with weather ensemble predictions","volume":"17","author":"Taylor","year":"2002","journal-title":"IEEE Trans. Power Syst."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"6486","DOI":"10.1002\/wrcr.20517","article-title":"Urban water demand forecasting and uncertainty assessment using ensemble wavelet-bootstrap-neural network models","volume":"49","author":"Tiwari","year":"2013","journal-title":"Water Resour. Res."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"993","DOI":"10.1109\/34.58871","article-title":"Neural Network Ensembles","volume":"12","author":"Hansen","year":"1990","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"894","DOI":"10.1190\/1.1803501","article-title":"Mapping coastal environments with lidar and EM on Mustang Island, Texas, U.S","volume":"23","author":"Paine","year":"2004","journal-title":"Lead. Edge"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"05014004","DOI":"10.1061\/(ASCE)SU.1943-5428.0000137","article-title":"Measuring land subsidence using GPS: Ellipsoid height versus orthometric height","volume":"141","author":"Wang","year":"2014","journal-title":"J. Surv. Eng."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1923","DOI":"10.1109\/LGRS.2015.2438394","article-title":"Accuracy of digital elevation models derived from terrestrial laser scanning data","volume":"12","author":"Fan","year":"2015","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"701","DOI":"10.14358\/PERS.76.6.701","article-title":"Effects of topographic variability and lidar sampling density on several dem interpolation methods","volume":"76","author":"Guo","year":"2010","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"2629","DOI":"10.3390\/rs2112629","article-title":"DEM development from ground-based lidar data: A method to remove non-surface objects","volume":"2","author":"Sharma","year":"2010","journal-title":"Remote Sens."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Nguyen, C., Starek, M.J., Tissot, P., and Gibeaut, J. (2018). Unsupervised clustering method for complexity reduction of terrestrial lidar data in marshes. Remote Sens., 10.","DOI":"10.3390\/rs10010133"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1847","DOI":"10.1002\/esp.2206","article-title":"Detection of surface change in complex topography using terrestrial laser scanning: Application to the Illgraben debris-flow channel","volume":"36","author":"Densmore","year":"2011","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1109\/TGRS.2014.2320134","article-title":"Empirical waveform decomposition and radiometric calibration of a terrestrial full-waveform laser scanner","volume":"53","author":"Hartzell","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1111\/j.1752-1688.2002.tb01532.x","article-title":"Evaluation of light detection and ranging (lidar) for measuring river corridor topography 1","volume":"38","author":"Bowen","year":"2002","journal-title":"JAWRA J. Am. Water Resour. Assoc."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"116","DOI":"10.5589\/m06-011","article-title":"Investigating laser pulse penetration through a conifer canopy by integrating airborne and terrestrial lidar","volume":"32","author":"Chasmer","year":"2006","journal-title":"Can. J. Remote Sens."},{"key":"ref_45","first-page":"79","article-title":"Assessment of LiDAR DTM accuracy in coastal vegetated areas","volume":"36","author":"Heipke","year":"2006","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1111\/j.1477-9730.2011.00647.x","article-title":"Terrestrial laser scan error in the presence of dense ground vegetation","volume":"26","author":"Coveney","year":"2011","journal-title":"Photogramm. Rec."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1016\/j.jhydrol.2004.12.001","article-title":"Groundwater level forecasting using artificial neural networks","volume":"309","author":"Daliakopoulos","year":"2005","journal-title":"J. Hydrol."},{"key":"ref_48","unstructured":"Lourakis, M.I. (2005). A Brief Description of the Levenberg-Marquardt Algorithm Implemented by Levmar, Foundation of Research and Technology."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"930","DOI":"10.1109\/TNN.2010.2045657","article-title":"Improved computation for Levenberg\u2013Marquardt training","volume":"21","author":"Wilamowski","year":"2010","journal-title":"IEEE Trans. Neural Netw."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"989","DOI":"10.1109\/72.329697","article-title":"Training feedforward networks with the Marquardt algorithm","volume":"5","author":"Hagan","year":"1994","journal-title":"IEEE Trans. Neural Netw."},{"key":"ref_51","unstructured":"Huang, G.-B., Zhu, Q.-Y., and Siew, C.-K. (2004, January 25\u201329). Extreme learning machine: A new learning scheme of feedforward neural networks. Proceedings of the IJCNN 2004 IEEE International Joint Conference on Neural Networks, Budapest, Hungary."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1061\/(ASCE)HE.1943-5584.0000188","article-title":"Comparing sigmoid transfer functions for neural network multistep ahead streamflow forecasting","volume":"5","author":"Yonaba","year":"2010","journal-title":"J. Hydrol. Eng."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/8\/10\/444\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:28:44Z","timestamp":1760189324000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/8\/10\/444"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,10,9]]},"references-count":52,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2019,10]]}},"alternative-id":["ijgi8100444"],"URL":"https:\/\/doi.org\/10.3390\/ijgi8100444","relation":{},"ISSN":["2220-9964"],"issn-type":[{"type":"electronic","value":"2220-9964"}],"subject":[],"published":{"date-parts":[[2019,10,9]]}}}