53 citations as recorded by crossref.

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20. Spatial prediction of basal area and volume in Eucalyptus stands using Landsat TM data: an assessment of prediction methods A. dos Reis et al. 10.1186/s40490-017-0108-0
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22. Mapping Forest Health Using Spectral and Textural Information Extracted from SPOT-5 Satellite Images J. Meng et al. 10.3390/rs8090719
23. Exploring the Potential of WorldView-2 Red-Edge Band-Based Vegetation Indices for Estimation of Mangrove Leaf Area Index with Machine Learning Algorithms Y. Zhu et al. 10.3390/rs9101060
24. Spatiotemporal Variations of Aboveground Biomass under Different Terrain Conditions A. Shen et al. 10.3390/f9120778
25. Woody Biomass Mobilization for Bioenergy in a Constrained Landscape: A Case Study from Cold Lake First Nations in Alberta, Canada N. Mansuy et al. 10.3390/en13236289
26. Regional and historical factors supplement current climate in shaping global forest canopy height J. Zhang et al. 10.1111/1365-2745.12510
27. Carbon storage and sequestration rates of trees inside and outside forests in Great Britain F. Zellweger et al. 10.1088/1748-9326/ac74d5
28. Estimation and Spatial Distribution of Individual Tree Aboveground Biomass in a Chinese Fir Plantation in the Dabieshan Mountains of Western Anhui, China A. Chen et al. 10.3390/f15101743
29. Mapping Forest Ecosystem Biomass Density for Xiangjiang River Basin by Combining Plot and Remote Sensing Data and Comparing Spatial Extrapolation Methods J. Zhu et al. 10.3390/rs9030241
30. Enfoque espacial para modelación de carbono en el mantillo de bosques bajo manejo forestal maderable Z. Pérez-Vázquez et al. 10.21829/myb.2021.2712122
31. Drone-acquired data reveal the importance of forest canopy structure in predicting tree diversity J. Zhang et al. 10.1016/j.foreco.2021.119945
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35. Modeling Carbon Emissions of Post-Selective Logging in the Production Forests of Ulu Jelai, Pahang, Malaysia S. Saad et al. 10.3390/rs15041016
36. Quantifying the evidence for co-benefits between species conservation and climate change mitigation in giant panda habitats R. Li et al. 10.1038/s41598-017-12843-0
37. Forest canopy height variation in relation to topography and forest types in central Japan with LiDAR M. Farhadur Rahman et al. 10.1016/j.foreco.2021.119792
38. Using synthetic data to evaluate the benefits of large field plots for forest biomass estimation with LiDAR F. Fassnacht et al. 10.1016/j.rse.2018.05.007
39. Comprehensive analysis of gap formation in the canopy of an old-growth broadleaved forest A. Portnov et al. 10.31857/S1026347024010136
40. Seeing the forest from drones: Testing the potential of lightweight drones as a tool for long-term forest monitoring J. Zhang et al. 10.1016/j.biocon.2016.03.027
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42. Analyzing the Spatiotemporal Patterns of Forests Carbon Sink and Sources Between 2000 and 2019 A. Alaniz et al. 10.1029/2021EF002560
43. Biomass valorization in the management of woody plant invaders: The case of Pittosporum undulatum in the Azores L. Borges Silva et al. 10.1016/j.biombioe.2017.12.025
44. Seasonal behavior of vegetation determined by sensor on an unmanned aerial vehicle F. FELIX et al. 10.1590/0001-3765202120200712
45. Mapping Above-Ground Biomass in a Tropical Forest in Cambodia Using Canopy Textures Derived from Google Earth M. Singh et al. 10.3390/rs70505057
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48. Estimating and mapping forest biomass in northeast China using joint forest resources inventory and remote sensing data X. Wang et al. 10.1007/s11676-017-0504-6
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50. Evaluating the performance of airborne and spaceborne lidar for mapping biomass in the United States' largest dry woodland ecosystem M. Campbell et al. 10.1016/j.rse.2024.114196
51. Hazard rating of coastal pine forests for a black pine bast scale using self-organizing map (SOM) and random forest approaches Y. Nam et al. 10.1016/j.ecoinf.2014.11.001
52. Integration of Landsat time series and field plots for forest productivity estimates in decision support models C. Boisvenue et al. 10.1016/j.foreco.2016.06.022
53. A comparison of machine learning regression techniques for LiDAR-derived estimation of forest variables J. García-Gutiérrez et al. 10.1016/j.neucom.2014.09.091