{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T13:50:25Z","timestamp":1780321825135,"version":"3.54.1"},"reference-count":30,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2011,3,22]],"date-time":"2011-03-22T00:00:00Z","timestamp":1300752000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>With the progression of LiDAR (Light Detection and Ranging) towards a mainstream resource management tool, it has become necessary to understand how best to process and analyze the data. While most ground surface identification algorithms remain proprietary and have high purchase costs; a few are openly available, free to use, and are supported by published results. Two of the latter are the multiscale curvature classification and the Boise Center Aerospace Laboratory LiDAR (BCAL) algorithms. This study investigated the accuracy of these two algorithms (and a combination of the two) to create a digital terrain model from a raw LiDAR point cloud in a semi-arid landscape. Accuracy of each algorithm was assessed via comparison with &gt;7,000 high precision survey points stratified across six different cover types. The overall performance of both algorithms differed by only 2%; however, within specific cover types significant differences were observed in accuracy. The results highlight the accuracy of both algorithms across a variety of vegetation types, and ultimately suggest specific scenarios where one approach may outperform the other. Each algorithm produced similar results except in the ceanothus and conifer cover types where BCAL produced lower errors.<\/jats:p>","DOI":"10.3390\/rs3030638","type":"journal-article","created":{"date-parts":[[2011,3,25]],"date-time":"2011-03-25T11:14:25Z","timestamp":1301051665000},"page":"638-649","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":47,"title":["A Comparison of Two Open Source LiDAR Surface Classification Algorithms"],"prefix":"10.3390","volume":"3","author":[{"given":"Wade T.","family":"Tinkham","sequence":"first","affiliation":[{"name":"Department of Forest Ecology and Biogeosciences, College of Natural Resources, University of Idaho, 975 W. 6th St., Moscow, ID 83844, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongyu","family":"Huang","sequence":"additional","affiliation":[{"name":"Spatial Information Research Center, Fuzhou University, Fuzhou, Fujian 350002, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0071-9958","authenticated-orcid":false,"given":"Alistair M. S.","family":"Smith","sequence":"additional","affiliation":[{"name":"Department of Forest Ecology and Biogeosciences, College of Natural Resources, University of Idaho, 975 W. 6th St., Moscow, ID 83844, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rupesh","family":"Shrestha","sequence":"additional","affiliation":[{"name":"Boise Center Aerospace Laboratory, Department of Geosciences, Idaho State University, Boise, ID 83702, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael J.","family":"Falkowski","sequence":"additional","affiliation":[{"name":"School of Forest Resources and Environmental Science, Michigan Technological University, Houghton, MI 49931, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7480-1458","authenticated-orcid":false,"given":"Andrew T.","family":"Hudak","sequence":"additional","affiliation":[{"name":"Rocky Mountain Research Station, Forest Service, US Department of Agriculture, 1221 S. Main St., Moscow, ID 83843, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Timothy E.","family":"Link","sequence":"additional","affiliation":[{"name":"Department of Forest Ecology and Biogeosciences, College of Natural Resources, University of Idaho, 975 W. 6th St., Moscow, ID 83844, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nancy F.","family":"Glenn","sequence":"additional","affiliation":[{"name":"Boise Center Aerospace Laboratory, Department of Geosciences, Idaho State University, Boise, ID 83702, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Danny G","family":"Marks","sequence":"additional","affiliation":[{"name":"Northwest Watershed Research Center, Agricultural Research Service, US Department of Agriculture, Boise, ID 83712, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2011,3,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2533","DOI":"10.1016\/j.rse.2009.07.002","article-title":"Mapping snags and understory shrubs for a lidar-based assessment of wildlife habitat suitability","volume":"113","author":"Martinuzzi","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"946","DOI":"10.1016\/j.rse.2009.01.003","article-title":"Characterizing forest succession with lidar data: An evaluation for the Inland Northwest, USA","volume":"113","author":"Falkowski","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1175\/2007JHM870.1","article-title":"Radiative transfer modeling of a coniferous canopy characterized by airborne remote sensing","volume":"9","author":"Essery","year":"2008","journal-title":"J. Hydrometeorol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1088\/1748-9326\/4\/3\/034009","article-title":"Tropical forest carbon assessment: Integrating satellite and airborne mapping approaches","volume":"4","author":"Asner","year":"2009","journal-title":"Environ. Res. Lett."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"53","DOI":"10.5194\/tc-4-53-2010","article-title":"On the potential of very high-resolution repeat DEMs in glacial and periglacial environments","volume":"4","author":"Abermann","year":"2010","journal-title":"The Cryosphere"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"2109","DOI":"10.1002\/1099-1085(20000815\/30)14:11\/12<2109::AID-HYP58>3.0.CO;2-1","article-title":"Integration of high-resolution topographic data with floodplain flow models","volume":"14","author":"Marks","year":"2000","journal-title":"Hydrol. Process."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"817","DOI":"10.14358\/PERS.71.7.817","article-title":"An evaluation of lidar-derived elevation and terrain slope in leaf-off conditions","volume":"71","author":"Hodgson","year":"2005","journal-title":"Photogramm. Eng. Remote Sensing"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"323","DOI":"10.1016\/j.isprsjprs.2006.05.002","article-title":"Accuracy of large-scale canopy heights derived from lidar data under operational constraints in a complex alpine environment","volume":"60","author":"Hollaus","year":"2006","journal-title":"ISPRS J. Photogram. Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1016\/S0924-2716(99)00016-7","article-title":"Airborne laser scanning: Existing systems and firms and other resources","volume":"54","author":"Baltsavias","year":"1999","journal-title":"ISPRS J. Photogram. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1016\/S0034-4257(02)00114-1","article-title":"An evaluation of lidar- and IFSAR-derived digital elevation models in leaf-on conditions with USGS Level 1 and Level 2 DEMs","volume":"84","author":"Hodgson","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_11","unstructured":"Smith, S.L., Holland, D.A., and Longley, P.A. (2004, January 12\u201323). The importance of understanding error in lidar digital elevation models. Proceedings of XXth ISPRS Congress: Commission IV \u201cGeo-Imagery Bridging Continents\u201d, Istanbul, Turkey."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"527","DOI":"10.5589\/m03-022","article-title":"Accuracy of a high-resolution lidar terrain model under a conifer forest canopy","volume":"29","author":"Reutebuch","year":"2003","journal-title":"Can. J. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"331","DOI":"10.14358\/PERS.70.3.331","article-title":"Accuracy of airborne lidar-derived elevation: Empirical assessment and error budget","volume":"70","author":"Hodgson","year":"2004","journal-title":"Photogram. Eng. Remote Sensing"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"3889","DOI":"10.1080\/01431160500181671","article-title":"Lidar density and linear interpolator effects on elevation estimates","volume":"26","author":"Anderson","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_15","unstructured":"Hyypp\u00e4, H., Yu, Z., Hyyppa, J., Kaartinen, H., Kaasalainen, S., Honkavaara, E., and Ronnholm, P. (2005, January 12\u201314). Factors affecting the quality of DTM generation in forested areas. Proceedings of the ISPRS Workshop Laser Scanning 2005, Enschede, The Netherlands."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1265","DOI":"10.14358\/PERS.72.11.1265","article-title":"Influence of vegetation, slope, and lidar sampling angle on DEM accuracy","volume":"72","author":"Su","year":"2006","journal-title":"Photogram. Eng. Remote Sensing"},{"key":"ref_17","first-page":"289","article-title":"Evaluating error associated with lidar-derived DEM interpolation","volume":"35","author":"Bates","year":"2008","journal-title":"Comput. Geosci."},{"key":"ref_18","unstructured":"Shan, J., and Toth, C.K. (2009). Topographic Laser Ranging and Scanning: Principles and Processing, CRC Press."},{"key":"ref_19","unstructured":"Spaete, L.P., Glenn, N.F., Derryberry, D.P., Sanki, T.T., Mitchell, J., and Hardegree, S.P. (2011). The effects of slope and vegetation cover type on the accuracy of a small-footprint airborne lidar derived digital elevation model. Remote Sens. Lett., in press."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1","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":"Photogram. Eng. Remote Sensing"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"776","DOI":"10.3390\/rs1040776","article-title":"Discrete return lidar in natural resources: Recommendations for project planning, data processing, and deliverables","volume":"1","author":"Evans","year":"2009","journal-title":"Remote Sens."},{"key":"ref_22","unstructured":"Jensen, J.R. (2007). Remote Sensing of the Environment: An Earth Resource Perspective, Prentice Hall."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1029","DOI":"10.1109\/TGRS.2006.890412","article-title":"A multiscale curvature algorithm for classifying discrete return lidar in forested environments","volume":"45","author":"Evans","year":"2007","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1016\/j.rse.2006.02.011","article-title":"lidar measurement of sagebrush steppe vegetation heights","volume":"102","author":"Streutker","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"126","DOI":"10.5589\/m06-007","article-title":"Regression modeling and mapping of coniferous forest basal area and tree density from discrete-return lidar and multispectral satellite data","volume":"32","author":"Hudak","year":"2006","journal-title":"Can. J. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"2232","DOI":"10.1016\/j.rse.2007.10.009","article-title":"Nearest neighbor imputation of species-level, plot-scale forest structure attributes from lidar data","volume":"112","author":"Hudak","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"3947","DOI":"10.1016\/j.rse.2008.07.001","article-title":"Discrete return lidar-based prediction of leaf area index in two conifer forests","volume":"112","author":"Jensen","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1139\/X09-183","article-title":"Landscape-scale parameterization of a tree-level forest growth model: A k-nearest neighbor imputation approach incorporating lidar data","volume":"40","author":"Falkowski","year":"2010","journal-title":"Can. J. For. Res."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Glenn, N.F., Spaete, L., Sankey, T., Derryberry, D.R., and Hardegree, S. (2011). Lidar-derived shrub height and crown area: development of methods and the lack of influence from sloped terrain. J. Arid Environ., in press.","DOI":"10.1016\/j.jaridenv.2010.11.005"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"92","DOI":"10.2111\/REM-D-10-00019.1","article-title":"LiDAR-based classification of sagebrush community types","volume":"64","author":"Sankey","year":"2011","journal-title":"Rangeland Ecol. 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