{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T08:57:37Z","timestamp":1777625857595,"version":"3.51.4"},"reference-count":60,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2021,3,3]],"date-time":"2021-03-03T00:00:00Z","timestamp":1614729600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["Nos. 42090013, 41971288, and 41801237"],"award-info":[{"award-number":["Nos. 42090013, 41971288, and 41801237"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Clumping index (CI) is a canopy structural variable important for modeling the terrestrial biosphere, but its retrieval from remote sensing data remains one of the least reliable. The majority of regional or global CI products available so far were generated from multiangle optical reflectance data. However, these reflectance-based estimates have well-known limitations, such as the mere use of a linear relationship between the normalized difference hotspot and darkspot (NDHD) and CI, uncertainties in bidirectional reflectance distribution function (BRDF) models used to calculate the NDHD, and coarse spatial resolutions (e.g., hundreds of meters to several kilometers). To remedy these limitations and develop alternative methods for large-scale CI mapping, here we explored the use of spaceborne lidar\u2014the Geoscience Laser Altimeter System (GLAS)\u2014and proposed a semi-physical algorithm to estimate CI at the footprint level. Our algorithm was formulated to leverage the full vertical canopy profile information of the GLAS full-waveform data; it converted raw waveforms to forest canopy gap distributions and gap fractions of random canopies, which was used to estimate CI based on the radiative transfer theory and a revised Beer\u2013Lambert model. We tested our algorithm over two areas in China\u2014the Saihanba National Forest Park and Heilongjiang Province\u2014and assessed its relative accuracies against field-measured CI and MODIS CI products. We found that reliable estimation of CI was possible only for GLAS waveforms with high signal-to-noise ratios (e.g., &gt;65) and at gentle slopes (e.g., &lt;12\u00b0). Our GLAS-based CI estimates for high-quality waveforms compared well to field-based CI (i.e., R2 = 0.72, RMSE = 0.07, and bias = 0.02), but they showed less correlation to MODIS CI (e.g., R2 = 0.26, RMSE = 0.12, and bias = 0.04). The difference highlights the impact of the scale effect in conducting comparisons of products with huge differences resolution. Overall, our analyses represent the first attempt to use spaceborne lidar to retrieve high-resolution forest CI and our algorithm holds promise for mapping CI globally.<\/jats:p>","DOI":"10.3390\/rs13050948","type":"journal-article","created":{"date-parts":[[2021,3,3]],"date-time":"2021-03-03T20:33:57Z","timestamp":1614803637000},"page":"948","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Retrieving Forest Canopy Elements Clumping Index Using ICESat GLAS Lidar Data"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9477-9155","authenticated-orcid":false,"given":"Lei","family":"Cui","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 Normal University, 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"},{"name":"Ohio Agricultural Research and Development Center, School of Environment and Natural Resources, The Ohio State University, Wooster, OH 44691, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3701-0830","authenticated-orcid":false,"given":"Ziti","family":"Jiao","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 Normal University, 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"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kaiguang","family":"Zhao","sequence":"additional","affiliation":[{"name":"Ohio Agricultural Research and Development Center, School of Environment and Natural Resources, The Ohio State University, Wooster, OH 44691, USA"},{"name":"Environmental Science Graduate Program, School of Environment and Natural Resources, The Ohio State University, Columbus, OH 43210, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mei","family":"Sun","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 Normal University, 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"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yadong","family":"Dong","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 Normal University, Beijing 100875, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Siyang","family":"Yin","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 Normal University, 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"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1352-5143","authenticated-orcid":false,"given":"Xiaoning","family":"Zhang","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 Normal University, 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"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Guo","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 Normal University, 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"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rui","family":"Xie","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 Normal University, 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"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zidong","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 Normal University, 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"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sijie","family":"Li","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 Normal University, 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"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yidong","family":"Tong","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 Normal University, 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"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,3,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1016\/0168-1923(92)90040-B","article-title":"Foliage Area and Architecture of Plant Canopies from Sunfleck Size Disributions","volume":"60","author":"Chen","year":"1992","journal-title":"Agric. Forest Meteorol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/0002-1571(71)90092-6","article-title":"Theoretical Analysis of Frequency of Gaps in Plant Stands","volume":"8","author":"Nilson","year":"1971","journal-title":"Agric. Meteorol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1109\/TGRS.2013.2237780","article-title":"Use of General Regression Neural Networks for Generating the Glass Leaf Area Index Product from Time-Series Modis Surface Reflectance","volume":"52","author":"Xiao","year":"2014","journal-title":"IEEE Trans. Geosci. Remote"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2219","DOI":"10.1109\/TGRS.2006.872100","article-title":"Algorithm for Global Leaf Area Index Retrieval Using Satellite Imagery","volume":"44","author":"Deng","year":"2006","journal-title":"IEEE Trans. Geosci. Remote"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"G04003","DOI":"10.1029\/2012JG002084","article-title":"Retrospective Retrieval of Long-Term Consistent Global Leaf Area Index (1981\u20132011) From Combined Avhrr and Modis Data","volume":"117","author":"Liu","year":"2012","journal-title":"J. Geophys. Res. Biogeosci."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/S0304-3800(99)00156-8","article-title":"Daily Canopy Photosynthesis Model through Temporal and Spatial Scaling for Remote Sensing Applications","volume":"124","author":"Chen","year":"1999","journal-title":"Ecol. Model."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"5052","DOI":"10.1029\/2018GL077560","article-title":"Changes in the Shadow: The Shifting Role of Shaded Leaves in Global Carbon and Water Cycles Under Climate Change","volume":"45","author":"He","year":"2018","journal-title":"Geophys. Res. Lett."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"GB4017","DOI":"10.1029\/2011GB004053","article-title":"Integration of Modis Land and Atmosphere Products with a Coupled-Process Model to Estimate Gross Primary Productivity and Evapotranspiration From 1 Km to Global Scales","volume":"25","author":"Ryu","year":"2011","journal-title":"Glob. Biogeochem. Cycles"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2010GB003996","article-title":"Effects of Foliage Clumping on the Estimation of Global Terrestrial Gross Primary Productivity","volume":"26","author":"Chen","year":"2012","journal-title":"Glob. Biogeochem. Cycles"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1016\/j.agrformet.2015.09.017","article-title":"Assessment of Foliage Clumping Effects on Evapotranspiration Estimates in Forested Ecosystems","volume":"216","author":"Chen","year":"2016","journal-title":"Agric. Forest Meteorol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"447","DOI":"10.1016\/j.rse.2005.05.003","article-title":"Global Mapping of Foliage Clumping Index Using Multi-Angular Satellite Data","volume":"97","author":"Chen","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1316","DOI":"10.1109\/36.628798","article-title":"A Four-Scale Bidirectional Reflectance Model Based on Canopy Architecture","volume":"35","author":"Chen","year":"1997","journal-title":"IEEE Trans. Geosci. Remote"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1016\/j.rse.2016.08.007","article-title":"A Method for Improving Hotspot Directional Signatures in Brdf Models Used for Modis","volume":"186","author":"Jiao","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1016\/j.isprsjprs.2010.03.002","article-title":"Expanding Global Mapping of the Foliage Clumping Index with Multi-Angular Polder Three Measurements: Evaluation and Topographic Compensation","volume":"65","author":"Pisek","year":"2010","journal-title":"ISPRS J. Photogramm."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"111296","DOI":"10.1016\/j.rse.2019.111296","article-title":"Global 500 M Clumping Index Product Derived from Modis Brdf Data (2001\u20132017)","volume":"232","author":"Wei","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1016\/j.rse.2011.12.008","article-title":"Global Clumping Index Map Derived from the Modis Brdf Product","volume":"119","author":"He","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"594","DOI":"10.1016\/j.rse.2018.02.041","article-title":"An Algorithm for the Retrieval of the Clumping Index (Ci) From the Modis Brdf Product Using an Adjusted Version of the Kernel-Driven Brdf Model","volume":"209","author":"Jiao","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1016\/j.rse.2013.07.014","article-title":"Retrieving Vegetation Clumping Index from Multi-Angle Imaging Spectroradiometer (Misr) Data at 275M Resolution","volume":"138","author":"Pisek","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"476","DOI":"10.1016\/j.rse.2016.10.039","article-title":"Estimation of Canopy Clumping Index from Misr and Modis Sensors Using the Normalized Difference Hotspot and Darkspot (Ndhd) Method: The Influence of Brdf Models and Solar Zenith Angle","volume":"187","author":"Wei","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1016\/j.rse.2003.12.006","article-title":"Bidirectional Reflectance of Earth Targets: Evaluation of Analytical Models Using a Large Set of Spaceborne Measurements with Emphasis on the Hot Spot","volume":"90","author":"Maignan","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1016\/j.isprsjprs.2008.01.006","article-title":"Accuracy Assessment of High Resolution Satellite Imagery Orientation by Leave-One-Out Method (Article)","volume":"63","author":"Brovelli","year":"2008","journal-title":"ISPRS J. Photogramm."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"G00E07","DOI":"10.1029\/2008JG000898","article-title":"Synergistic Use of Spaceborne Lidar and Optical Imagery for Assessing Forest Disturbance: An Alaska Case Study","volume":"115","author":"Goetz","year":"2010","journal-title":"J. Geophys. Res. Biogeosci."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1016\/j.rse.2015.04.015","article-title":"Combining Airborne Hyperspectral and Lidar Data Across Local Sites for Upscaling Shrubland Structural Information: Lessons for Hyspiri","volume":"167","author":"Mitchell","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.rse.2015.01.030","article-title":"Canopy Clumping Appraisal Using Terrestrial and Airborne Laser Scanning","volume":"161","author":"Gajardo","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"308","DOI":"10.1016\/j.isprsjprs.2017.06.006","article-title":"Retrieving the Gap Fraction, Element Clumping Index, and Leaf Area Index of Individual Trees Using Single-Scan Data from a Terrestrial Laser Scanner","volume":"130","author":"Li","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"452","DOI":"10.1016\/j.rse.2018.03.034","article-title":"Retrieving Forest Canopy Clumping Index Using Terrestrial Laser Scanning Data","volume":"210","author":"Ma","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1864","DOI":"10.1111\/2041-210X.13273","article-title":"How to Better Estimate Leaf Area Index and Leaf Angle Distribution from Digital Hemispherical Photography? Switching to a Binary Nonlinear Regression Paradigm","volume":"10","author":"Zhao","year":"2019","journal-title":"Methods Ecol. Evol."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"8271","DOI":"10.1080\/01431161.2010.533211","article-title":"Leaf Area and Clumping Indices for a Boreal Mixed-Wood Forest: Lidar, Hyperspectral, and Landsat Models","volume":"32","author":"Thomas","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/j.rse.2012.07.007","article-title":"Measuring Gap Fraction, Element Clumping Index and Lai in Sierra Forest Stands Using a Full-Waveform Ground-Based Lidar","volume":"125","author":"Zhao","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Kuusk, A., Pisek, J., Lang, M., and M\u00e4rdla, S. (2018). Estimation of Gap Fraction and Foliage Clumping in Forest Canopies. Remote Sens. Basel, 10.","DOI":"10.3390\/rs10071153"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Cui, L., Jiao, Z., Zhao, K., Sun, M., Dong, Y., Yin, S., Li, Y., Chang, Y., Guo, J., and Xie, R. (2020). Retrieval of Vertical Foliage Profile and Leaf Area Index Using Transmitted Energy Information Derived from Icesat Glas Data. Remote Sens. Basel, 12.","DOI":"10.3390\/rs12152457"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"100002","DOI":"10.1016\/j.srs.2020.100002","article-title":"The Global Ecosystem Dy-namics Investigation: High-Resolution Laser Ranging of the Earth\u2019S Forests and Topography","volume":"1","author":"Dubayah","year":"2020","journal-title":"Sci. Remote Sens."},{"key":"ref_33","unstructured":"Heilongjiang Forestry and Grassland Bureau (2020, December 18). Available online: http:\/\/hljforest.com\/."},{"key":"ref_34","unstructured":"National Geomatics Center of China (NGCC) (2020, January 20). 30-Meter Global Land Cover Dataset (GlobeLand30)-Product Description Data, Available online: http:\/\/www.globallandcover.com\/GLC30Download\/index.aspx."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"434","DOI":"10.1038\/514434c","article-title":"Open Access to Earth Land-Cover Map","volume":"514","author":"Jun","year":"2014","journal-title":"Nature"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Pang, Y., Li, Z., Lefsky, M., Guoqing, S., and Yu, X. (August, January 31). Model Based Terrain Effect Analyses on ICEsat GLAS Waveforms. Proceedings of the 2006 IEEE International Symposium on Geoscience and Remote Sensing, Denver, CO, USA.","DOI":"10.1109\/IGARSS.2006.830"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"2005RG000183","DOI":"10.1029\/2005RG000183","article-title":"The Shuttle Radar Topography Mission","volume":"45","author":"Farr","year":"2007","journal-title":"Rev. Geophys."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1175\/1087-3562(2003)007<0001:GPTCAA>2.0.CO;2","article-title":"Global Percent Tree Cover at a Spatial Resolution of 500 Meters: First Results of the Modis Vegetation Continuous Fields Algorithm","volume":"7","author":"Hansen","year":"2003","journal-title":"Earth Interact."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.rse.2013.08.025","article-title":"Evaluation of Modis Albedo Product (Mcd43a) Over Grassland, Agriculture and Forest Surface Types During Dormant and Snow-Covered Periods","volume":"140","author":"Wang","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"2476","DOI":"10.1016\/j.rse.2009.07.009","article-title":"The Modis (Collection V005) Brdf\/Albedo Product: Assessment of Spatial Representativeness over Forested Landscapes","volume":"113","author":"Roman","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"2645","DOI":"10.1080\/01431161.2010.507611","article-title":"Estimation of Vegetation Clumping Index Using Modis Brdf Data","volume":"32","author":"Pisek","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_42","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_43","doi-asserted-by":"crossref","first-page":"1453","DOI":"10.1080\/01431160701736372","article-title":"Single and Two Epoch Analysis of Icesat Full Waveform Data Over Forested Areas","volume":"29","author":"Duong","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1989","DOI":"10.1109\/36.851780","article-title":"Decomposition of Laser Altimeter Waveforms","volume":"38","author":"Hofton","year":"2000","journal-title":"IEEE Trans. Geosci. Remote"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1016\/j.isprsjprs.2018.12.010","article-title":"Retrieving Leaf Area Index in Discontinuous Forest Using Icesat\/Glas Full-Waveform Data Based on Gap Fraction Model","volume":"148","author":"Yang","year":"2019","journal-title":"ISPRS J. Photogramm."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"745","DOI":"10.1080\/2150704X.2013.790573","article-title":"Retrieving Leaf Area Index Using Icesat\/Glas Full-Waveform Data","volume":"4","author":"Luo","year":"2013","journal-title":"Remote Sens. Lett."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1016\/0168-1923(95)02291-0","article-title":"Optically-Based Methods for Measuring Seasonal Variation of Leaf Area Index in Boreal Conifer Stands","volume":"80","author":"Chen","year":"1996","journal-title":"Agric. Forest Meteorol."},{"key":"ref_48","first-page":"104","article-title":"Monitoring Land Surface Albedo and Vegetation Dynamics Using High Spatial and Temporal Resolution Synthetic Time Series from Landsat and the Modis Brdf\/Nbar\/Albedo Product","volume":"59","author":"Wang","year":"2017","journal-title":"Int. J. Appl. Earth Obs."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/j.isprsjprs.2017.04.020","article-title":"Mapping Vegetation Heights in China Using Slope Correction Icesat Data, Srtm, Modis-Derived and Climate Data","volume":"129","author":"Huang","year":"2017","journal-title":"ISPRS J. Photogramm."},{"key":"ref_50","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_51","doi-asserted-by":"crossref","first-page":"4650","DOI":"10.1109\/TGRS.2013.2283272","article-title":"Forest Canopy Height Extraction in Rugged Areas with Icesat\/Glas Data","volume":"52","author":"Wang","year":"2014","journal-title":"IEEE Trans. Geosci. Remote"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"L21S10","DOI":"10.1029\/2005GL023471","article-title":"Icesat Waveform Measurements of within-Footprint Topographic Relief and Vegetation Vertical Structure","volume":"32","author":"Harding","year":"2005","journal-title":"Geophys. Res. Lett."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"2786","DOI":"10.1016\/j.rse.2011.01.026","article-title":"Satellite Lidar Vs. Small Footprint Airborne Lidar: Comparing the Accuracy of Aboveground Biomass Estimates and Forest Structure Metrics at Footprint Level","volume":"115","author":"Popescu","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"103104","DOI":"10.1117\/1.OE.53.10.103104","article-title":"Signal-to-Noise Ratio-Based Quality Assessment Method for Icesat\/Glas Waveform Data","volume":"53","author":"Nie","year":"2014","journal-title":"Opt. Eng."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Wang, M., Sun, R., and Xiao, Z. (2018). Estimation of Forest Canopy Height and Aboveground Biomass from Spaceborne Lidar and Landsat Imageries in Maryland. Remote Sens. Basel, 10.","DOI":"10.3390\/rs10020344"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.rse.2018.02.001","article-title":"Capturing Rapid Land Surface Dynamics with Collection V006 Modis Brdf\/Nbar\/Albedo (Mcd43) Products","volume":"207","author":"Wang","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1016\/0168-1923(86)90033-X","article-title":"Estimation of Leaf-Area Index from Transmission of Direct Sunlight in Discontinuous Canopies","volume":"37","author":"Lang","year":"1986","journal-title":"Agric. Forest Meteorol."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/j.agrformet.2004.09.006","article-title":"Methodology Comparison for Canopy Structure Parameters Extraction from Digital Hemispherical Photography in Boreal Forests","volume":"129","author":"Leblanc","year":"2005","journal-title":"Agric. Forest Meteorol."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"390","DOI":"10.1016\/j.agrformet.2018.11.033","article-title":"Review of Indirect Optical Measurements of Leaf Area Index: Recent Advances, Challenges, and Perspectives","volume":"265","author":"Yan","year":"2019","journal-title":"Agric. Forest Meteorol."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"5440","DOI":"10.1109\/TGRS.2017.2702126","article-title":"Icesat\/Glas Altimetry Measurements: Received Signal Dynamic Range and Saturation Correction","volume":"55","author":"Sun","year":"2017","journal-title":"IEEE Trans. Geosci. Remote"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/5\/948\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:32:14Z","timestamp":1760160734000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/5\/948"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,3,3]]},"references-count":60,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2021,3]]}},"alternative-id":["rs13050948"],"URL":"https:\/\/doi.org\/10.3390\/rs13050948","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,3,3]]}}}