38 citations as recorded by crossref.

1. Multisensor Data Fusion for Improved Segmentation of Individual Tree Crowns in Dense Tropical Forests M. Aubry-Kientz et al. 10.1109/JSTARS.2021.3069159
2. Effect of assisted natural regeneration on forest biomass and carbon stocks in the Living Mountain Lab (LML), Lalitpur, Nepal N. Joshi et al. 10.1016/j.envc.2024.100858
3. Point cloud-based crown volume improves tree biomass estimation: Evaluating different crown volume extraction algorithms F. Wang et al. 10.1016/j.compag.2024.109288
4. Exploring Tropical Forests With GEDI and 3-D SAR Tomography Y. Ngo et al. 10.1109/LGRS.2023.3298142
5. The BIOMASS Level 2 Prototype Processor: Design and Experimental Results of Above-Ground Biomass Estimation F. Banda et al. 10.3390/rs12060985
6. Residents’ Willingness to Pay for Forest Ecosystem Services Based on Forest Ownership Classification in South Korea Y. Son et al. 10.3390/f15030551
7. Modelos de biomasa aérea y subterránea de Hevea brasilienses y Theobroma grandiflorum en la Amazonía colombiana H. Andrade et al. 10.14483/2256201X.18464
8. Mapping Canopy Heights in Dense Tropical Forests Using Low-Cost UAV-Derived Photogrammetric Point Clouds and Machine Learning Approaches H. Zhang et al. 10.3390/rs13183777
9. Impacts of selective logging on Amazon forest canopy structure and biomass with a LiDAR and photogrammetric survey sequence M. d'Oliveira et al. 10.1016/j.foreco.2021.119648
10. Old growth Afrotropical forests critical for maintaining forest carbon J. Poulsen et al. 10.1111/geb.13150
11. AGB Estimation in a Tropical Mountain Forest (TMF) by Means of RGB and Multispectral Images Using an Unmanned Aerial Vehicle (UAV) V. González-Jaramillo et al. 10.3390/rs11121413
12. Diversity, distribution and dynamics of large trees across an old-growth lowland tropical rain forest landscape D. Clark et al. 10.1371/journal.pone.0224896
13. Forest degradation and biomass loss along the Chocó region of Colombia V. Meyer et al. 10.1186/s13021-019-0117-9
14. Ground and Volume Decomposition as a Proxy for AGB from P-Band SAR Data F. Banda et al. 10.3390/rs12020240
15. Aboveground Biomass Estimation in Amazonian Tropical Forests: a Comparison of Aircraft- and GatorEye UAV-borne LiDAR Data in the Chico Mendes Extractive Reserve in Acre, Brazil M. d’Oliveira et al. 10.3390/rs12111754
16. Sparse large trees in secondary and planted forests highlight the need to improve forest conservation and management C. Jin et al. 10.1016/j.scitotenv.2024.176363
17. Carbon storage potential in degraded forests of Kalimantan, Indonesia A. Ferraz et al. 10.1088/1748-9326/aad782
18. Pantropical variability in tree crown allometry G. Loubota Panzou et al. 10.1111/geb.13231
19. Carbon storages and sequestration potentials in remnant forests of different patch sizes in northern Ethiopia: an implication for climate change mitigation M. Muluneh & B. Worku 10.1186/s40066-022-00395-0
20. Seeing the wood for the trees: Carbon storage and conservation in temperate forests of the Himalayas I. Måren & L. Sharma 10.1016/j.foreco.2021.119010
21. Deciphering the fingerprint of disturbance on the three‐dimensional structure of the world’s forests T. Jucker 10.1111/nph.17729
22. The European Space Agency BIOMASS mission: Measuring forest above-ground biomass from space S. Quegan et al. 10.1016/j.rse.2019.03.032
23. Interferometric Ground Cancellation for Above Ground Biomass Estimation M. Mariotti d'Alessandro et al. 10.1109/TGRS.2020.2976854
24. UAV-based canopy textures assess changes in forest structure from long-term degradation C. Bourgoin et al. 10.1016/j.ecolind.2020.106386
25. High-resolution data reveal a surge of biomass loss from temperate and Atlantic pine forests, contextualizing the 2022 fire season distinctiveness in France L. Vallet et al. 10.5194/bg-20-3803-2023
26. What controls local-scale aboveground biomass variation in central Africa? Testing structural, composition and architectural attributes G. Loubota Panzou et al. 10.1016/j.foreco.2018.07.056
27. Structure metrics to generalize biomass estimation from lidar across forest types from different continents N. Knapp et al. 10.1016/j.rse.2019.111597
28. Mapping tropical forest aboveground biomass using airborne SAR tomography N. Ramachandran et al. 10.1038/s41598-023-33311-y
29. Effect of Forest Management on Carbon Stock of Tropical Moist Afromontane Forest D. Daba et al. 10.1155/2022/3691638
30. Estimating aboveground carbon density and its uncertainty in Borneo's structurally complex tropical forests using airborne laser scanning T. Jucker et al. 10.5194/bg-15-3811-2018
31. Tropical tree size–frequency distributions from airborne lidar A. Ferraz et al. 10.1002/eap.2154
32. Aboveground biomass density models for NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar mission L. Duncanson et al. 10.1016/j.rse.2021.112845
33. Non-destructive estimation of individual tree biomass: Allometric models, terrestrial and UAV laser scanning B. Brede et al. 10.1016/j.rse.2022.113180
34. Quantifying tropical forest structure through terrestrial and UAV laser scanning fusion in Australian rainforests L. Terryn et al. 10.1016/j.rse.2022.112912
35. Indicators for monitoring reduced impact logging in the Brazilian amazon derived from airborne laser scanning technology Q. Barros et al. 10.1016/j.ecoinf.2024.102654
36. Tree Biomass Equations from Terrestrial LiDAR: A Case Study in Guyana A. Lau et al. 10.3390/f10060527
37. The Status of Technologies to Measure Forest Biomass and Structural Properties: State of the Art in SAR Tomography of Tropical Forests S. Tebaldini et al. 10.1007/s10712-019-09539-7
38. Savanna vegetation structure in the Brazilian Cerrado allows for the accurate estimation of aboveground biomass using terrestrial laser scanning B. Zimbres et al. 10.1016/j.foreco.2019.117798