{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T19:07:21Z","timestamp":1774379241516,"version":"3.50.1"},"reference-count":57,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2021,8,2]],"date-time":"2021-08-02T00:00:00Z","timestamp":1627862400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Understory vegetation plays an important role in the structure and function of forest ecosystems. Light detection and ranging (LiDAR) can provide understory information in the form of either point cloud or full-waveform data. Point cloud data have a remarkable ability to represent the three-dimensional structures of vegetation, while full-waveform data contain more detailed information on the interactions between laser pulses and vegetation; both types have been widely used to estimate various forest canopy structural parameters, including leaf area index (LAI). Here, we present a new method for quantifying understory LAI in a temperate forest by combining the advantages of both types of LiDAR data. To achieve this, we first estimated the vertical distribution of the gap probability using point cloud data to automatically determine the height boundary between overstory and understory vegetation at the plot level. We then deconvolved the full-waveform data to remove the blurring effect caused by the system pulse to restore the vertical resolution of the LiDAR system. Subsequently, we decomposed the deconvolved data and integrated the plot-level boundary height to differentiate the waveform components returned from the overstory, understory, and soil layers. Finally, we modified the basic LiDAR equations introducing understory leaf spectral information to quantify the understory LAI. Our results, which were validated against ground-based measurements, show that the new method produced a good estimation of the understory LAI with an R2 of 0.54 and a root-mean-square error (RMSE) of 0.21. Our study demonstrates that the understory LAI can be successfully quantified through the combined use of point cloud and full-waveform LiDAR data.<\/jats:p>","DOI":"10.3390\/rs13153036","type":"journal-article","created":{"date-parts":[[2021,8,4]],"date-time":"2021-08-04T02:16:07Z","timestamp":1628043367000},"page":"3036","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["A Method for Quantifying Understory Leaf Area Index in a Temperate Forest through Combining Small Footprint Full-Waveform and Point Cloud LiDAR Data"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0812-7164","authenticated-orcid":false,"given":"Jinling","family":"Song","sequence":"first","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Aerospace Information Research Institute of Chinese Academy of Sciences, Beijing 100875, China"},{"name":"Beijing Engineering Research Center for Global Land Remote Sensing Products, Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}]},{"given":"Xiao","family":"Zhu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Aerospace Information Research Institute of Chinese Academy of Sciences, Beijing 100875, China"},{"name":"Beijing Engineering Research Center for Global Land Remote Sensing Products, Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6601-7882","authenticated-orcid":false,"given":"Jianbo","family":"Qi","sequence":"additional","affiliation":[{"name":"Key Laboratory for Silviculture and Conservation of Ministry of Education, Beijing Forestry University, Beijing 100083, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9760-6580","authenticated-orcid":false,"given":"Yong","family":"Pang","sequence":"additional","affiliation":[{"name":"Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China"}]},{"given":"Lei","family":"Yang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Aerospace Information Research Institute of Chinese Academy of Sciences, Beijing 100875, China"},{"name":"Beijing Engineering Research Center for Global Land Remote Sensing Products, Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}]},{"given":"Lihong","family":"Yu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Aerospace Information Research Institute of Chinese Academy of Sciences, Beijing 100875, China"},{"name":"Beijing Engineering Research Center for Global Land Remote Sensing Products, Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Shugart, H.H., Saatchi, S., and Hall, F.G. (2010). Importance of structure and its measurement in quantifying function of forest ecosystems. J. Geophys. Res. Biogeosciences, 115.","DOI":"10.1029\/2009JG000993"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"186","DOI":"10.1016\/j.isprsjprs.2017.10.002","article-title":"Mapping the height and spatial cover of features beneath the forest canopy at small-scales using airborne scanning discrete return Lidar","volume":"133","author":"Sumnall","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"730","DOI":"10.1109\/LGRS.2011.2179635","article-title":"A New Method for Incorporating Hillslope Effects to Improve Canopy-Height Estimates From Large-Footprint LIDAR Waveforms","volume":"9","author":"Allouis","year":"2012","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.rse.2013.02.021","article-title":"Direct retrieval of canopy gap probability using airborne waveform lidar","volume":"134","author":"Armston","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"386","DOI":"10.1016\/j.rse.2019.02.017","article-title":"Slope-adaptive waveform metrics of large footprint lidar for estimation of forest aboveground biomass","volume":"224","author":"Wang","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_6","first-page":"212","article-title":"Estimating riparian understory vegetation cover with beta regression and copula models","volume":"57","author":"Eskelson","year":"2011","journal-title":"For. Sci."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1345","DOI":"10.1139\/x06-025","article-title":"On the formation of dense understory layers in forests worldwide: Consequences and implications for forest dynamics, biodiversity, and succession","volume":"36","author":"Royo","year":"2006","journal-title":"Can. J. For. Res."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1016\/j.foreco.2015.02.018","article-title":"Understory plant biomass dynamics of prescribed burned Pinus palustris stands","volume":"344","author":"Samuelson","year":"2015","journal-title":"For. Ecol. Manag."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"266","DOI":"10.5424\/fs\/2011202-10923","article-title":"Potential crown fire behavior in Pinus pinea stands following different fuel treatments","volume":"20","author":"Molina","year":"2011","journal-title":"For. Syst."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1111\/j.1744-7348.1953.tb02364.x","article-title":"Comparative physiological studies on the growth of field crops","volume":"40","author":"Watson","year":"1953","journal-title":"Ann. Appl. Biol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"421","DOI":"10.1111\/j.1365-3040.1992.tb00992.x","article-title":"Defining leaf area index for non-flat leaves","volume":"15","author":"Chen","year":"1992","journal-title":"Plant Cell Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1016\/0034-4257(95)00195-6","article-title":"Retrieving leaf area index of boreal conifer forests using landsat TM images","volume":"55","author":"Chen","year":"1996","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/j.rse.2011.10.032","article-title":"Generating global Leaf Area Index from Landsat: Algorithm formulation and demonstration","volume":"122","author":"Ganguly","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1016\/j.rse.2013.12.007","article-title":"Deriving and validating Leaf Area Index (LAI) at multiple spatial scales through lidar remote sensing: A case study in Sierra National Forest, CA","volume":"143","author":"Tang","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"276","DOI":"10.1016\/j.agrformet.2018.08.026","article-title":"Improving leaf area index (LAI) estimation by correcting for clumping and woody effects using terrestrial laser scanning","volume":"263","author":"Zhu","year":"2018","journal-title":"Agric. For. Meteorol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1111\/j.1466-822X.2004.00094.x","article-title":"Leaf area index and net primary productivity along subtropical to alpine gradients in the Tibetan Plateau","volume":"13","author":"Luo","year":"2004","journal-title":"Glob. Ecol. Biogeogr."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"502","DOI":"10.1126\/science.275.5299.502","article-title":"Modeling the Exchanges of Energy, Water, and Carbon Between Continents and the Atmosphere","volume":"275","author":"Sellers","year":"1997","journal-title":"Science"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"S56","DOI":"10.1016\/j.rse.2008.01.026","article-title":"PROSPECT plus SAIL models: A review of use for vegetation characterization","volume":"113","author":"Jacquemoud","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"791","DOI":"10.1038\/nclimate3004","article-title":"Greening of the Earth and its drivers","volume":"6","author":"Zhu","year":"2016","journal-title":"Nat. Clim. Chang."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"14415","DOI":"10.1029\/94JD00483","article-title":"A simple hydrologically based model of land surface water and energy fluxes for general circulation models","volume":"99","author":"Liang","year":"1994","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"G02028","DOI":"10.1029\/2007JG000635","article-title":"Validation and intercomparison of global Leaf Area Index products derived from remote sensing data","volume":"113","author":"Garrigues","year":"2008","journal-title":"J. Geophys. Res."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1038\/523403a","article-title":"Agree on biodiversity metrics to track from space","volume":"523","author":"Skidmore","year":"2015","journal-title":"Nature"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1016\/S0169-5347(03)00071-5","article-title":"From space to species: Ecological applications for remote sensing","volume":"18","author":"Kerr","year":"2003","journal-title":"Trends Ecol. Evol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2753","DOI":"10.1016\/j.rse.2011.01.024","article-title":"Characterizing 3D vegetation structure from space: Mission requirements","volume":"115","author":"Hall","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_25","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_26","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1016\/j.isprsjprs.2008.12.004","article-title":"Mapping the understorey of deciduous woodland from leaf-on and leaf-off airborne LiDAR data: A case study in lowland Britain","volume":"64","author":"Hill","year":"2009","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1403","DOI":"10.1016\/j.rse.2010.01.023","article-title":"Discrimination of vegetation strata in a multi-layered Mediterranean forest ecosystem using height and intensity information derived from airborne laser scanning","volume":"114","author":"Morsdorf","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"730","DOI":"10.1016\/j.rse.2012.06.024","article-title":"Prediction of understory vegetation cover with airborne lidar in an interior ponderosa pine forest","volume":"124","author":"Wing","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"330","DOI":"10.1016\/j.rse.2018.06.023","article-title":"Quantifying understory vegetation density using small-footprint airborne lidar","volume":"215","author":"Campbell","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"418","DOI":"10.1016\/j.rse.2016.07.010","article-title":"Simulation of satellite, airborne and terrestrial LiDAR with DART (I): Waveform simulation with quasi-Monte Carlo ray tracing","volume":"184","author":"Yin","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"161","DOI":"10.5194\/isprs-annals-III-3-161-2016","article-title":"Helios: A multi-purpose lidar simulation framework for research, planning and training of laser scanning operations with airborne, ground-based mobile and stationary platforms","volume":"3","author":"Bechtold","year":"2016","journal-title":"ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/j.rse.2006.09.036","article-title":"Forest vertical structure from GLAS: An evaluation using LVIS and SRTM data","volume":"112","author":"Sun","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1897","DOI":"10.3390\/rs70201897","article-title":"Forest Canopy LAI and Vertical FAVD Profile Inversion from Airborne Full-Waveform LiDAR Data Based on a Radiative Transfer Model","volume":"7","author":"Ma","year":"2015","journal-title":"Remote Sens."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1943","DOI":"10.1109\/36.951085","article-title":"Modeling lidar waveforms in heterogeneous and discrete canopies","volume":"39","author":"Jupp","year":"2001","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1016\/j.rse.2012.05.005","article-title":"Retrieval of vertical LAI profiles over tropical rain forests using waveform lidar at La Selva, Costa Rica","volume":"124","author":"Tang","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"239","DOI":"10.5194\/bg-13-239-2016","article-title":"Characterizing leaf area index (LAI) and vertical foliage profile (VFP) over the United States","volume":"13","author":"Tang","year":"2016","journal-title":"Biogeosciences"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"10142","DOI":"10.1364\/OE.24.010142","article-title":"Generating pseudo large footprint waveforms from small footprint full-waveform airborne LiDAR data for the layered retrieval of LAI in orchards","volume":"24","author":"Li","year":"2016","journal-title":"Opt. Express"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1936","DOI":"10.1007\/s11434-012-5660-7","article-title":"Soil aggregate fraction-based C-14 analysis and its application in the study of soil organic carbon turnover under forests of different ages","volume":"58","author":"Tan","year":"2013","journal-title":"Chin. Sci. Bull."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"e87975","DOI":"10.1371\/journal.pone.0087975","article-title":"Nitrogen Deposition Enhances Carbon Sequestration by Plantations in Northern China","volume":"9","author":"Du","year":"2014","journal-title":"PLoS ONE"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Pang, Y., Li, Z.Y., Ju, H.B., Lu, H., Jia, W., Si, L., Guo, Y., Liu, Q.W., Li, S.M., and Liu, L.X. (2016). LiCHy: The CAF\u2019s LiDAR, CCD and Hyperspectral Integrated Airborne Observation System. Remote Sens., 8.","DOI":"10.3390\/rs8050398"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"400","DOI":"10.1016\/j.rse.2018.08.033","article-title":"Characterizing understory vegetation in Mediterranean forests using full-waveform airborne laser scanning data","volume":"217","author":"Pablo","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.isprsjprs.2016.03.016","article-title":"Improved progressive TIN densification filtering algorithm for airborne LiDAR data in forested areas","volume":"117","author":"Zhao","year":"2016","journal-title":"Isprs J. Photogramm. Remote Sens."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1016\/S0034-4257(03)00098-1","article-title":"Modeling airborne laser scanning data for the spatial generation of critical forest parameters in fire behavior modeling","volume":"86","author":"Meier","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.isprsjprs.2008.09.007","article-title":"Full-waveform topographic lidar: State-of-the-art","volume":"64","author":"Mallet","year":"2009","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_45","unstructured":"Jalobeanu, A., and Gon\u00e7alves, G. (2012, January 19\u201323). The full-waveform LiDAR RIEGL LMS-Q680I: From reverse engineering to sensor modeling. Proceedings of the American Society for Photogrammetry and Remote Sensing Annual Conference, Sacramento, CA, USA."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1364\/JOSAA.12.000058","article-title":"Blind deconvolution by means of the Richardson\u2013Lucy algorithm","volume":"12","author":"Fish","year":"1995","journal-title":"J. Opt. Soc. Am. Opt. Image Sci. Vis."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"2402","DOI":"10.1109\/TGRS.2010.2103080","article-title":"A comparison of signal deconvolution algorithms based on small-footprint LiDAR waveform simulatioin","volume":"40","author":"Wu","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1627","DOI":"10.1021\/ac60214a047","article-title":"Smoothing and Differentiation of Data by Simplified Least Squares Procedures","volume":"36","author":"Savitzky","year":"1964","journal-title":"Anal. Chem."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1016\/j.isprsjprs.2005.12.001","article-title":"Gaussian decomposition and calibration of a novel small-footprint full-waveform digitising airborne laser scanner","volume":"60","author":"Wagner","year":"2006","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1017\/S0962492900002518","article-title":"Sequential Quadratic Programming","volume":"4","author":"Boggs","year":"1995","journal-title":"Acta Numer."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"6211","DOI":"10.1364\/AO.34.006211","article-title":"Plant canopy gap-size analysis theory for improving optical measurements of leaf-area index","volume":"34","author":"Chen","year":"1995","journal-title":"Appl. Opt."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"29429","DOI":"10.1029\/97JD01107","article-title":"Leaf area index of boreal forests: Theory, techniques, and measurements","volume":"102","author":"Chen","year":"1997","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1016\/j.rse.2014.08.007","article-title":"Large-scale retrieval of leaf area index and vertical foliage profile from the spaceborne waveform lidar (GLAS\/ICESat)","volume":"154","author":"Tang","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Tian., J., and Philpot, W.D. (2014, January 13\u201318). Spectral reflectance of drying soil. Proceedings of the IEEE Geoscience and Remote Sensing Symposium, Quebec, QC, Canada.","DOI":"10.1109\/IGARSS.2014.6947272"},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Wu, Q., Song, C., Song, J., Wang, J., and Bo, Y. (2018). Impacts of Leaf Age on Canopy Spectral Signature Variation in Evergreen Chinese Fir Forests. Remote Sens., 10.","DOI":"10.3390\/rs10020262"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"1301","DOI":"10.1016\/j.scitotenv.2019.01.379","article-title":"Leaf age effects on the spectral predictability of leaf traits in Amazonian canopy trees","volume":"666","author":"Malhi","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Gara, T.W., Darvishzadeh, R., Skidmore, A.K., and Wang, T. (2018). Impact of Vertical Canopy Position on Leaf Spectral Properties and Traits across Multiple Species. Remote Sens., 10.","DOI":"10.3390\/rs10020346"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/15\/3036\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:39:19Z","timestamp":1760164759000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/15\/3036"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,2]]},"references-count":57,"journal-issue":{"issue":"15","published-online":{"date-parts":[[2021,8]]}},"alternative-id":["rs13153036"],"URL":"https:\/\/doi.org\/10.3390\/rs13153036","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,8,2]]}}}