93 citations as recorded by crossref.

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2. Evaluating Prospects for Improved Forest Parameter Retrieval From Satellite LiDAR Using a Physically-Based Radiative Transfer Model J. Rosette et al. 10.1109/JSTARS.2013.2244199
3. Earth observation from space – The issue of environmental sustainability S. Durrieu & R. Nelson 10.1016/j.spacepol.2013.07.003
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5. An IPCC-Compliant Technique for Forest Carbon Stock Assessment Using Airborne LiDAR-Derived Tree Metrics and Competition Index C. Lin et al. 10.3390/rs8060528
6. An Error Model for Mapping Forest Cover and Forest Cover Change Using L-Band SAR O. Cartus et al. 10.1109/LGRS.2017.2775659
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10. Determination of Structural Characteristics of Old-Growth Forest in Ukraine Using Spaceborne LiDAR B. Spracklen & D. Spracklen 10.3390/rs13071233
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24. Remote Sensing of Wetlands in the Prairie Pothole Region of North America J. Montgomery et al. 10.3390/rs13193878
25. Fine-resolution forest tree height estimation across the Sierra Nevada through the integration of spaceborne LiDAR, airborne LiDAR, and optical imagery Y. Su et al. 10.1080/17538947.2016.1227380
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28. Exploring the Relationship between Forest Canopy Height and Canopy Density from Spaceborne LiDAR Observations H. Kay et al. 10.3390/rs13244961
29. Tree Crowns Cause Border Effects in Area-Based Biomass Estimations from Remote Sensing N. Knapp et al. 10.3390/rs13081592
30. Estimating Canopy Gap Fraction Using ICESat GLAS within Australian Forest Ecosystems C. Mahoney et al. 10.3390/rs9010059
31. Regionalization of an Existing Global Forest Canopy Height Model for Forests of the Southern United States N. Ku et al. 10.3390/rs13091722
32. Deriving and validating Leaf Area Index (LAI) at multiple spatial scales through lidar remote sensing: A case study in Sierra National Forest, CA H. Tang et al. 10.1016/j.rse.2013.12.007
33. Effects of Non‐Photosynthetic Vegetation on Dust Emissions X. Huang & H. Foroutan 10.1029/2021JD035243
34. ICESat-2 for Canopy Cover Estimation at Large-Scale on a Cloud-Based Platform E. Akturk et al. 10.3390/s23073394
35. The global distribution of leaf chlorophyll content H. Croft et al. 10.1016/j.rse.2019.111479
36. The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2): Science requirements, concept, and implementation T. Markus et al. 10.1016/j.rse.2016.12.029
37. Living Earth: Implementing national standardised land cover classification systems for Earth Observation in support of sustainable development C. Owers et al. 10.1080/20964471.2021.1948179
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39. Temperate forest and open landscapes are distinct alternative states as reflected in canopy height and tree cover C. Xu et al. 10.1016/j.tree.2015.07.002
40. Forest age mapping based on multiple-resource remote sensing data X. Yang et al. 10.1007/s10661-020-08694-4
41. A lesson unlearned? Underestimating tree cover in drylands biases global restoration maps M. Fagan 10.1111/gcb.15187
42. Canopy Height Estimation in Mediterranean Forests of Spain With TanDEM-X Data C. Gomez et al. 10.1109/JSTARS.2021.3060691
43. Forest signal detection for photon counting LiDAR using Random Forest B. Chen et al. 10.1080/2150704X.2019.1682708
44. Characterizing global forest canopy cover distribution using spaceborne lidar H. Tang et al. 10.1016/j.rse.2019.111262
45. Rare, Intense, Big fires dominate the global tropics under drier conditions S. Hantson et al. 10.1038/s41598-017-14654-9
46. Forest biomass is strongly shaped by forest height across boreal to tropical forests in China X. Wu et al. 10.1093/jpe/rtv001
47. Livestock Herbivory Shapes Fire Regimes and Vegetation Structure Across the Global Tropics R. Bernardi et al. 10.1007/s10021-019-00349-x
48. The impact of geolocation uncertainty on GEDI tropical forest canopy height estimation and change monitoring D. Roy et al. 10.1016/j.srs.2021.100024
49. Atmospheric removal of PM 2.5 by man-made Three Northern Regions Shelter Forest in Northern China estimated using satellite retrieved PM 2.5 concentration X. Zhang et al. 10.1016/j.scitotenv.2017.03.206
50. Post-drought decline of the Amazon carbon sink Y. Yang et al. 10.1038/s41467-018-05668-6
51. Integrating Disparate Lidar Data at the National Scale to Assess the Relationships between Height Above Ground, Land Cover and Ecoregions J. Stoker et al. 10.14358/PERS.80.1.59
52. Parameter Estimation of Radar Noise Model for Terrain Referenced Navigation Using a New EM Initialization Method J. Park et al. 10.1109/TAES.2019.2911766
53. Forest canopy height estimation using satellite laser altimetry: a case study in the Western Ghats, India S. Ghosh & M. Behera 10.1007/s12518-017-0190-2
54. Investigation of ICESat-2 Data Capabilities for Forest-Height Estimation over Russia S. Bartalev et al. 10.1134/S0010952522700022
55. Ground and Top of Canopy Extraction From Photon-Counting LiDAR Data Using Local Outlier Factor With Ellipse Searching Area B. Chen et al. 10.1109/LGRS.2019.2899011
56. The Uncertainty of Plot-Scale Forest Height Estimates from Complementary Spaceborne Observations in the Taiga-Tundra Ecotone P. Montesano et al. 10.3390/rs61010070
57. Remotely sensed canopy height reveals three pantropical ecosystem states C. Xu et al. 10.1002/ecy.1470
58. Large-scale retrieval of leaf area index and vertical foliage profile from the spaceborne waveform lidar (GLAS/ICESat) H. Tang et al. 10.1016/j.rse.2014.08.007
59. Sensitivity of L-Band SAR Backscatter to Aboveground Biomass of Global Forests Y. Yu & S. Saatchi 10.3390/rs8060522
60. The global forest above-ground biomass pool for 2010 estimated from high-resolution satellite observations M. Santoro et al. 10.5194/essd-13-3927-2021
61. Joint Use of ICESat/GLAS and Landsat Data in Land Cover Classification: A Case Study in Henan Province, China C. Liu et al. 10.1109/JSTARS.2014.2327032
62. A global corrected SRTM DEM product for vegetated areas X. Zhao et al. 10.1080/2150704X.2018.1425560
63. Annual forest aboveground biomass changes mapped using ICESat/GLAS measurements, historical inventory data, and time-series optical and radar imagery for Guangdong province, China W. Shen et al. 10.1016/j.agrformet.2018.04.005
64. Moving Toward Consistent ALS Monitoring of Forest Attributes across Canada C. Hopkinson et al. 10.14358/PERS.79.2.159
65. Impact of Soil Reflectance Variation Correction on Woody Cover Estimation in Kruger National Park Using MODIS Data . Ibrahim et al. 10.3390/rs11080898
66. Stratifying forest overstory and understory using the Global Ecosystem Dynamic Investigation laser scanning data Z. Yun et al. 10.1016/j.jag.2023.103538
67. Potential of Forest Parameter Estimation Using Metrics from Photon Counting LiDAR Data in Howland Research Forest B. Chen et al. 10.3390/rs11070856
68. Estimating forest canopy parameters from satellite waveform LiDAR by inversion of the FLIGHT three-dimensional radiative transfer model I. Bye et al. 10.1016/j.rse.2016.10.048
69. Mapping vegetation heights in China using slope correction ICESat data, SRTM, MODIS-derived and climate data H. Huang et al. 10.1016/j.isprsjprs.2017.04.020
70. Integration of allometric equations in the water cloud model towards an improved retrieval of forest stem volume with L-band SAR data in Sweden M. Santoro et al. 10.1016/j.rse.2020.112235
71. UniFHy v0.1.1: a community modelling framework for the terrestrial water cycle in Python T. Hallouin et al. 10.5194/gmd-15-9177-2022
72. Taking stock of circumboreal forest carbon with ground measurements, airborne and spaceborne LiDAR C. Neigh et al. 10.1016/j.rse.2013.06.019
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75. Improved derivation of forest stand canopy height structure using harmonized metrics of full-waveform data C. Lin 10.1016/j.rse.2019.111436
76. Integrating Multi-Source Remote Sensing to Assess Forest Aboveground Biomass in the Khingan Mountains of North-Eastern China Using Machine-Learning Algorithms X. Wang et al. 10.3390/rs14041039
77. Global estimation of above-ground biomass from spaceborne C-band scatterometer observations aided by LiDAR metrics of vegetation structure M. Santoro et al. 10.1016/j.rse.2022.113114
78. A global climate niche for giant trees M. Scheffer et al. 10.1111/gcb.14167
79. The uncertainty of biomass estimates from modeled ICESat-2 returns across a boreal forest gradient P. Montesano et al. 10.1016/j.rse.2014.10.029
80. Mapping Forest Canopy Height at Large Scales Using ICESat-2 and Landsat: An Ecological Zoning Random Forest Approach Z. Wu & F. Shi 10.1109/TGRS.2022.3231926
81. Light-driven growth in Amazon evergreen forests explained by seasonal variations of vertical canopy structure H. Tang & R. Dubayah 10.1073/pnas.1616943114
82. How did we get here? An early history of forestry lidar1 R. Nelson 10.5589/m13-011
83. Characterizing leaf area index (LAI) and vertical foliage profile (VFP) over the United States H. Tang et al. 10.5194/bg-13-239-2016
84. Variations of the glacier mass balance and lake water storage in the Tarim Basin, northwest China, over the period of 2003–2009 estimated by the ICESat-GLAS data N. Wang et al. 10.1007/s12665-015-4662-6
85. Mapping forest height using photon-counting LiDAR data and Landsat 8 OLI data: A case study in Virginia and North Carolina, USA X. Zhu et al. 10.1016/j.ecolind.2020.106287
86. A Structural Classification of Australian Vegetation Using ICESat/GLAS, ALOS PALSAR, and Landsat Sensor Data P. Scarth et al. 10.3390/rs11020147
87. Evaluation of the Simard et al. 2011 Global Canopy Height Map in Boreal Forests W. Yang & A. Kondoh 10.3390/rs12071114
88. A combined GLAS and MODIS estimation of the global distribution of mean forest canopy height Y. Wang et al. 10.1016/j.rse.2015.12.005
89. Slope Estimation from ICESat/GLAS C. Mahoney et al. 10.3390/rs61010051
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91. Towards Integration of GLAS into a National Fuel Mapping Program B. Peterson et al. 10.14358/PERS.79.2.175
92. Measuring forests with dual wavelength lidar: A simulation study over topography S. Hancock et al. 10.1016/j.agrformet.2012.03.014
93. Mapping Forest Height in Alaska Using GLAS, Landsat Composites, and Airborne LiDAR B. Peterson & K. Nelson 10.3390/rs61212409