{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T21:18:49Z","timestamp":1781644729726,"version":"3.54.5"},"reference-count":60,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2022,2,22]],"date-time":"2022-02-22T00:00:00Z","timestamp":1645488000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100013316","name":"Strategic Environmental Research and Development Program","doi-asserted-by":"publisher","award":["RC-19-1119"],"award-info":[{"award-number":["RC-19-1119"]}],"id":[{"id":"10.13039\/100013316","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Terrestrial laser scanning of forest structure is used increasingly in place of traditional technologies; however, deriving physical parameters from point clouds remains challenging because LiDAR returns do not have defined areas or volumes. While voxelization methods overcome this challenge, estimation of canopy gaps and other structural attributes are often performed by reducing the point cloud to two-dimensions, thus decreasing the fidelity of the data. Furthermore, relatively few studies have evaluated voxel-size effects on estimation accuracy. Here, we show that voxelized laser-scanning data can be used for canopy-gap estimation without performing dimensionality reduction to the point cloud. Both airborne and terrestrial LiDAR were used to estimate canopy gaps along six vertical transects and four height intervals. Voxel-based estimates were evaluated against hemispherical photography and a sensitivity analysis was performed to identify an optimal voxel size. While the results indicate that our approach can be used with both airborne and terrestrial LiDAR, voxel size has a considerable influence on canopy-gap estimation. Results from our sensitivity analysis indicate that TLS estimation performs best when using 10 cm voxels, yielding canopy gaps ranging from 32\u201378%. The optimal voxel size for ALS estimation was obtained with 25 cm voxels, yielding estimates ranging from 25\u201368%.<\/jats:p>","DOI":"10.3390\/rs14051054","type":"journal-article","created":{"date-parts":[[2022,2,22]],"date-time":"2022-02-22T22:35:00Z","timestamp":1645569300000},"page":"1054","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":34,"title":["LiDAR Voxel-Size Optimization for Canopy Gap Estimation"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2989-7945","authenticated-orcid":false,"given":"C. Wade","family":"Ross","sequence":"first","affiliation":[{"name":"Tall Timbers Research Station, Tallahassee, FL 32312, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"E. Louise","family":"Loudermilk","sequence":"additional","affiliation":[{"name":"United States Department of Agriculture Forest Service, Southern Research Station, Center for Forest Disturbance Science, Athens, GA 30602, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5801-5614","authenticated-orcid":false,"given":"Nicholas","family":"Skowronski","sequence":"additional","affiliation":[{"name":"United States Department of Agriculture Forest Service, Northern Research Station, Morgantown, WV 26505, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5753-4132","authenticated-orcid":false,"given":"Scott","family":"Pokswinski","sequence":"additional","affiliation":[{"name":"Tall Timbers Research Station, Tallahassee, FL 32312, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"J. Kevin","family":"Hiers","sequence":"additional","affiliation":[{"name":"Tall Timbers Research Station, Tallahassee, FL 32312, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joseph","family":"O\u2019Brien","sequence":"additional","affiliation":[{"name":"United States Department of Agriculture Forest Service, Southern Research Station, Center for Forest Disturbance Science, Athens, GA 30602, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,2,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Gonzalez-Benecke, C.A., Zhao, D., Samuelson, L.J., Martin, T.A., LeDuc, D.J., and Jack, S.B. (2018). Local and General Above-Ground Biomass Functions for Pinus Palustris Trees. Forests, 9.","DOI":"10.3390\/f9060310"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1080\/07038992.2016.1217482","article-title":"Mapping Forest Structure and Composition from Low-Density LiDAR for Informed Forest, Fuel, and Fire Management at Eglin Air Force Base, Florida, USA","volume":"42","author":"Hudak","year":"2016","journal-title":"Can. J. Remote Sens."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Ross, C.W., Hanan, N.P., Prihodko, L., Anchang, J., Ji, W., and Yu, Q. (2021). Woody-biomass projections and drivers of change in sub-Saharan Africa. Nat. Clim. Chang., 1\u20137.","DOI":"10.1038\/s41558-021-01034-5"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"554","DOI":"10.1080\/07038992.2016.1196582","article-title":"Imputation of Individual Longleaf Pine (Pinus palustris Mill.) Tree Attributes from Field and LiDAR Data","volume":"42","author":"Silva","year":"2016","journal-title":"Can. J. Remote Sens."},{"key":"ref_5","first-page":"752","article-title":"Light Transmittance Estimates in a Longleaf Pine Woodland","volume":"49","author":"Battaglia","year":"2003","journal-title":"For. Sci."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"33","DOI":"10.2307\/1942998","article-title":"Dynamics of Canopy Structure and Light Interception in Pinus Elliottii Stands, North Florida","volume":"61","author":"Gholz","year":"1991","journal-title":"Ecol. Monogr."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1021\/ed039p333","article-title":"The Beer-Lambert Law","volume":"39","author":"Swinehart","year":"1962","journal-title":"J. Chem. Educ."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Ross, J. (1981). The Radiation Regime and Architecture of Plant Stands (Tasks for Vegetation Science), Springer.","DOI":"10.1007\/978-94-009-8647-3"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1597","DOI":"10.1016\/j.mex.2018.11.006","article-title":"A novel approach to fuel biomass sampling for 3D fuel characterization","volume":"5","author":"Hawley","year":"2018","journal-title":"MethodsX"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s42408-020-0070-8","article-title":"Prescribed fire science: The case for a refined research agenda","volume":"16","author":"Hiers","year":"2020","journal-title":"Fire Ecol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"676","DOI":"10.1071\/WF07138","article-title":"Ground-based LIDAR: A novel approach to quantify fine-scale fuelbed characteristics","volume":"18","author":"Loudermilk","year":"2009","journal-title":"Int. J. Wildland Fire"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Skowronski, N.S., Gallagher, M.R., and Warner, T.A. (2020). Decomposing the Interactions between Fire Severity and Canopy Fuel Structure Using Multi-Temporal, Active, and Passive Remote Sensing Approaches. Fire, 3.","DOI":"10.3390\/fire3010007"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1984","DOI":"10.1139\/x02-087","article-title":"The effect of spatially variable overstory on the understory light environment of an open-canopied longleaf pine forest","volume":"32","author":"Battaglia","year":"2002","journal-title":"Can. J. For. Res."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"103","DOI":"10.2307\/2257250","article-title":"Hemisperical and Woodland Canopy Photography and the Light Climate","volume":"47","author":"Evans","year":"1959","journal-title":"J. Ecol."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Chianucci, F. (2019). An overview of in situ digital canopy photography in forestry. Can. J. For. Res., 227\u2013242.","DOI":"10.1139\/cjfr-2019-0055"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1016\/j.agrformet.2005.06.003","article-title":"Assessment of automatic gap fraction estimation of forests from digital hemispherical photography","volume":"132","author":"Jonckheere","year":"2005","journal-title":"Agric. For. Meteorol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"228","DOI":"10.3832\/ifor0957-006","article-title":"On the exposure of hemispherical photographs in forests","volume":"6","author":"Seidel","year":"2013","journal-title":"iForest\u2014Biogeosci. For."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1016\/S0168-1923(97)00073-7","article-title":"Calibration of grey values of hemispherical photographs for image analysis","volume":"90","author":"Wagner","year":"1998","journal-title":"Agric. For. Meteorol."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Andersen, H.-E., Reutebuch, S.E., and McGaughey, R.J. (2006). Active Remote Sensing. Computer Applications in Sustainable Forest Management, Springer.","DOI":"10.1007\/978-1-4020-4387-1_3"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Shan, J., and Toth, C.K. (2018). Topographic Laser Ranging and Scanning: Principles and Processing, CRC Press. [2nd ed.].","DOI":"10.1201\/9781315154381"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1227","DOI":"10.1080\/01431160903380672","article-title":"Mapping gap fraction, LAI and defoliation using various ALS penetration variables","volume":"31","author":"Solberg","year":"2010","journal-title":"Int. J. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"607","DOI":"10.5589\/m03-026","article-title":"Using airborne and ground-based ranging lidar to measure canopy structure in Australian forests","volume":"29","author":"Lovell","year":"2003","journal-title":"Can. J. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1016\/S0034-4257(99)00052-8","article-title":"Lidar Remote Sensing of the Canopy Structure and Biophysical Properties of Douglas-Fir Western Hemlock Forests","volume":"70","author":"Lefsky","year":"1999","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"6770","DOI":"10.1038\/s41598-017-07200-0","article-title":"Forest understory trees can be segmented accurately within sufficiently dense airborne laser scanning point clouds","volume":"7","author":"Hamraz","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_25","first-page":"33","article-title":"Recognising Structure in Laser Scanner Point Clouds","volume":"46","author":"Vosselman","year":"2004","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Wang, Y., and Fang, H. (2020). Estimation of LAI with the LiDAR Technology: A Review. Remote Sens., 12.","DOI":"10.3390\/rs12203457"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1016\/j.agrformet.2014.04.013","article-title":"Effects of voxel size and sampling setup on the estimation of forest canopy gap fraction from terrestrial laser scanning data","volume":"194","author":"Cifuentes","year":"2014","journal-title":"Agric. For. Meteorol."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1109\/LGRS.2006.887064","article-title":"Forest Canopy Gap Fraction From Terrestrial Laser Scanning","volume":"4","author":"Danson","year":"2007","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"777","DOI":"10.1109\/TGRS.2012.2205003","article-title":"Retrieval of Effective Leaf Area Index in Heterogeneous Forests with Terrestrial Laser Scanning","volume":"51","author":"Zheng","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"428","DOI":"10.1016\/j.agrformet.2007.10.004","article-title":"Estimating the plant area density of a Japanese larch (Larix kaempferi Sarg.) plantation using a ground-based laser scanner","volume":"148","author":"Takeda","year":"2008","journal-title":"Agric. For. Meteorol."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Wang, L., Xu, Y., Li, Y., and Zhao, Y. (2018). Voxel segmentation-based 3D building detection algorithm for airborne LIDAR data. PLoS ONE, 13.","DOI":"10.1371\/journal.pone.0208996"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"589","DOI":"10.1093\/aob\/mcx095","article-title":"Exploring trees in three dimensions: VoxR, a novel voxel-based R package dedicated to analysing the complex arrangement of tree crowns","volume":"121","author":"Lecigne","year":"2017","journal-title":"Ann. Bot."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1016\/j.agrformet.2013.09.005","article-title":"On seeing the wood from the leaves and the role of voxel size in determining leaf area distribution of forests with terrestrial LiDAR","volume":"184","author":"Baldocchi","year":"2014","journal-title":"Agric. For. Meteorol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1023\/A:1009776020438","article-title":"Effects of long-term fire exclusion on tree species composition and stand structure in an old-growth Pinus palustris (Longleaf pine) forest","volume":"140","author":"Gilliam","year":"1999","journal-title":"Plant Ecol."},{"key":"ref_35","first-page":"176","article-title":"The History of Fire in the Southern United States","volume":"14","author":"Fowler","year":"2007","journal-title":"Hum. Ecol. Rev."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"2733","DOI":"10.1016\/j.ecolmodel.2011.05.004","article-title":"Longleaf pine (Pinus palustris) and hardwood dynamics in a fire-maintained ecosystem: A simulation approach","volume":"222","author":"Loudermilk","year":"2011","journal-title":"Ecol. Model."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"92","DOI":"10.3368\/er.19.2.92","article-title":"Restoration Fire and Hurricanes in Longleaf Pine Sandhills","volume":"19","author":"Provencher","year":"2001","journal-title":"Ecol. Restor."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"542","DOI":"10.1579\/0044-7447-37.7.542","article-title":"Interactions among Overstory Structure, Seedling Life-history Traits, and Fire in Frequently Burned Neotropical Pine Forests","volume":"37","author":"Hiers","year":"2008","journal-title":"Ambio"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1458","DOI":"10.1139\/x97-081","article-title":"Effects of canopy structure on resource availability and seedling responses in a longleaf pine ecosystem","volume":"27","author":"Palik","year":"1997","journal-title":"Can. J. For. Res."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Jose, S., Jokela, E.J., and Miller, D.L. (2006). The Longleaf Pine Ecosystem. The Longleaf Pine Ecosystem: Ecology, Silviculture, and Restoration, Springer.","DOI":"10.1007\/978-0-387-30687-2"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"301","DOI":"10.3375\/043.029.0309","article-title":"Old Forests and Endangered Woodpeckers: Old-Growth in the Southern Coastal Plain","volume":"29","author":"Mitchell","year":"2009","journal-title":"Nat. Areas J."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"846","DOI":"10.1139\/x93-110","article-title":"Recent growth increases in old-growth longleaf pine","volume":"23","author":"West","year":"1993","journal-title":"Can. J. For. Res."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"144","DOI":"10.32614\/RJ-2013-014","article-title":"ggmap: Spatial Visualization with ggplot2","volume":"5","author":"Kahle","year":"2013","journal-title":"R J."},{"key":"ref_44","unstructured":"Walker, K. (2021). Tigris: Load Census TIGER\/Line Shapefiles, Available online: https:\/\/cran.r-project.org\/web\/packages\/tigris\/tigris.pdf."},{"key":"ref_45","first-page":"180214","article-title":"Present and future K\u00f6ppen-Geiger climate classification maps at 1-km resolution, Scientific Data","volume":"5","author":"Beck","year":"2018","journal-title":"Nature"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Robertson, K.M., Platt, W.J., and Faires, C.E. (2019). Patchy Fires Promote Regeneration of Longleaf Pine (Pinus palustris Mill.) in Pine Savannas. Forests, 10.","DOI":"10.3390\/f10050367"},{"key":"ref_47","unstructured":"Sanders, T. (1981). Soil Survey of Leon County."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"441","DOI":"10.2307\/2963498","article-title":"Effects of Fire Regime and Habitat on Tree Dynamics in North Florida Longleaf Pine Savannas","volume":"65","author":"Glitzenstein","year":"1995","journal-title":"Ecol. Monogr."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Khatib, O., Kumar, V., and Rus, D. (2008). A Four Wheel Drive Boom Lift Robot for Bush Fire Fighting. Experimental Robotics: The 10th International Symposium on Experimental Robotics, Springer. Springer Tracts in Advanced Robotics.","DOI":"10.1007\/978-3-540-77457-0"},{"key":"ref_50","unstructured":"R Core Team R (2020). A Language and Environment for Statistical Computing, R Foundation for Statistical Computing."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"112061","DOI":"10.1016\/j.rse.2020.112061","article-title":"lidR: An R package for analysis of Airborne Laser Scanning (ALS) data","volume":"251","author":"Roussel","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_52","unstructured":"Finley, A., Banerjee, S., and Hjelle, \u00d8. (2017). MBA: Multilevel B-Spline Approximation, Available online: https:\/\/rdrr.io\/cran\/MBA\/."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1109\/2945.620490","article-title":"Scattered data interpolation with multilevel B-splines","volume":"3","author":"Lee","year":"1997","journal-title":"IEEE Trans. Vis. Comput. Graph."},{"key":"ref_54","unstructured":"Guay, R. (2014). WinSCANOPY 2014 for Canopy Analysis, Regent Instruments Inc.. WinSCANOPY Manual Version 2014a."},{"key":"ref_55","unstructured":"Wickham, H., Fran\u00e7ois, R., Henry, L., and M\u00fcller, K. (2021). Dplyr: A Grammar of Data Manipulation. Available online: https:\/\/dplyr.tidyverse.org\/."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/S0378-1127(97)00308-3","article-title":"Gap-phase regeneration in longleaf pine wiregrass ecosystems","volume":"106","author":"Brockway","year":"1998","journal-title":"For. Ecol. Manag."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"424","DOI":"10.1016\/j.rse.2016.10.023","article-title":"Quantification of hidden canopy volume of airborne laser scanning data using a voxel traversal algorithm","volume":"194","author":"Schneider","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"323","DOI":"10.1080\/15481603.2021.1873588","article-title":"The impact of voxel size, forest type, and understory cover on visibility estimation in forests using terrestrial laser scanning","volume":"58","author":"Zong","year":"2021","journal-title":"GIScience Remote Sens."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"2724","DOI":"10.1139\/x06-100","article-title":"Silviculture that sustains: The nexus between silviculture, frequent prescribed fire, and conservation of biodiversity in longleaf pine forests of the southeastern United States","volume":"36","author":"Mitchell","year":"2006","journal-title":"Can. J. For. Res."},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Franklin, J.F., Mitchell, R.J., and Palik, B.J. (2007). Natural Disturbance and Stand Development Principles for Ecological Forestry, Tech. Rep. NRS-19; Newton Square, PA.","DOI":"10.2737\/NRS-GTR-19"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/5\/1054\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:24:33Z","timestamp":1760135073000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/5\/1054"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,22]]},"references-count":60,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2022,3]]}},"alternative-id":["rs14051054"],"URL":"https:\/\/doi.org\/10.3390\/rs14051054","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,2,22]]}}}