92 citations as recorded by crossref.

1. Spatial and temporal dynamics of forest aboveground carbon stocks in response to climate and environmental changes L. Fu et al. 10.1007/s11368-014-1050-x
2. Ultra-fine grain landscape-scale quantification of dryland vegetation structure with drone-acquired structure-from-motion photogrammetry A. Cunliffe et al. 10.1016/j.rse.2016.05.019
3. Improving pantropical forest carbon maps with airborne LiDAR sampling A. Baccini & G. Asner 10.4155/cmt.13.66
4. A National, Detailed Map of Forest Aboveground Carbon Stocks in Mexico O. Cartus et al. 10.3390/rs6065559
5. Uncertainty of remotely sensed aboveground biomass over an African tropical forest: Propagating errors from trees to plots to pixels Q. Chen et al. 10.1016/j.rse.2015.01.009
6. Mapping tree height distributions in Sub-Saharan Africa using Landsat 7 and 8 data M. Hansen et al. 10.1016/j.rse.2016.02.023
7. Post-Fire Changes in Forest Biomass Retrieved by Airborne LiDAR in Amazonia L. Sato et al. 10.3390/rs8100839
8. Targeted carbon conservation at national scales with high-resolution monitoring G. Asner et al. 10.1073/pnas.1419550111
9. ASCAT IB: A radar-based vegetation optical depth retrieved from the ASCAT scatterometer satellite X. Liu et al. 10.1016/j.rse.2021.112587
10. Using simulated GEDI waveforms to evaluate the effects of beam sensitivity and terrain slope on GEDI L2A relative height metrics over the Brazilian Amazon Forest P. V.C. Oliveira et al. 10.1016/j.srs.2023.100083
11. Estimation of coarse dead wood stocks in intact and degraded forests in the Brazilian Amazon using airborne lidar M. Scaranello et al. 10.5194/bg-16-3457-2019
12. High resolution biomass mapping in tropical forests with LiDAR-derived Digital Models: Poás Volcano National Park (Costa Rica) A. Fernández-Landa et al. 10.3832/ifor1744-009
13. Uncertainty in the spatial distribution of tropical forest biomass: a comparison of pan-tropical maps E. Mitchard et al. 10.1186/1750-0680-8-10
14. Carbon mitigation in the peri urban forest of Xanthi, Greece: a GIS mapping application F. Doukalianou et al. 10.1007/s41207-020-00170-2
15. Modeling and Mapping Agroforestry Aboveground Biomass in the Brazilian Amazon Using Airborne Lidar Data Q. Chen et al. 10.3390/rs8010021
16. Using the Error-in-Variable Simultaneous Equations Approach to Construct Compatible Estimation Models of Forest Inventory Attributes Based on Airborne LiDAR C. Li et al. 10.3390/f14010065
17. Towards Operational Monitoring of Forest Canopy Disturbance in Evergreen Rain Forests: A Test Case in Continental Southeast Asia A. Langner et al. 10.3390/rs10040544
18. A Biodiversity Indicators Dashboard: Addressing Challenges to Monitoring Progress towards the Aichi Biodiversity Targets Using Disaggregated Global Data X. Han et al. 10.1371/journal.pone.0112046
19. Interacting municipal-level anthropogenic and ecological disturbances drive changes in Neotropical forest carbon storage G. Toro et al. 10.3389/fenvs.2022.937147
20. Global-scale assessment and inter-comparison of recently developed/reprocessed microwave satellite vegetation optical depth products X. Li et al. 10.1016/j.rse.2020.112208
21. Utilising RGB drone imagery and vegetation indices for accurate above-ground biomass estimation: a case study of the cradle nature reserve, Gauteng Province, South Africa C. Matyukira & P. Mhangara 10.1080/10106049.2024.2390512
22. Carbon storage landscapes of lowland Hawaii: the role of native and invasive species through space and time R. Hughes et al. 10.1890/12-2253.1
23. Brazil’s Amazonian forest carbon: the key to Southern Amazonia’s significance for global climate P. Fearnside 10.1007/s10113-016-1007-2
24. Understanding Measurement Reporting and Verification Systems for REDD+ as an Investment for Generating Carbon Benefits G. Di Lallo et al. 10.3390/f8080271
25. A new global C-band vegetation optical depth product from ASCAT: Description, evaluation, and inter-comparison X. Liu et al. 10.1016/j.rse.2023.113850
26. Reappraisal of SMAP inversion algorithms for soil moisture and vegetation optical depth L. Gao et al. 10.1016/j.rse.2021.112627
27. National and regional relationships of carbon storage and tropical biodiversity D. Armenteras et al. 10.1016/j.biocon.2015.10.014
28. Spatial validation reveals poor predictive performance of large-scale ecological mapping models P. Ploton et al. 10.1038/s41467-020-18321-y
29. Modelling aboveground biomass of a multistage managed forest through synergistic use of Landsat-OLI, ALOS-2 L-band SAR and GEDI metrics H. Padalia et al. 10.1016/j.ecoinf.2023.102234
30. Mapping selective logging impacts in Borneo with GPS and airborne lidar P. Ellis et al. 10.1016/j.foreco.2016.01.020
31. Sensitivity of L-band vegetation optical depth to carbon stocks in tropical forests: a comparison to higher frequencies and optical indices D. Chaparro et al. 10.1016/j.rse.2019.111303
32. Influence of Prediction Cell Size on LiDAR-Derived Area-Based Estimates of Total Volume in Mixed-Species and Multicohort Forests in Northeastern North America R. Hayashi et al. 10.1080/07038992.2016.1229597
33. Fire disturbance data improves the accuracy of remotely sensed estimates of aboveground biomass for boreal forests in eastern Canada D. Irulappa Pillai Vijayakumar et al. 10.1016/j.rsase.2017.07.010
34. Understanding Forest Health with Remote Sensing -Part I—A Review of Spectral Traits, Processes and Remote-Sensing Characteristics A. Lausch et al. 10.3390/rs8121029
35. Carbon and Beyond: The Biogeochemistry of Climate in a Rapidly Changing Amazon K. Covey et al. 10.3389/ffgc.2021.618401
36. Approaches to monitoring changes in carbon stocks for REDD+ R. Birdsey et al. 10.4155/cmt.13.49
37. Live aboveground carbon stocks in natural forests of Colombia J. Phillips et al. 10.1016/j.foreco.2016.05.009
38. Hydrological Networks and Associated Topographic Variation as Templates for the Spatial Organization of Tropical Forest Vegetation M. Detto et al. 10.1371/journal.pone.0076296
39. Mapping tree diversity in the tropical forest region of Chocó-Colombia J. Fagua et al. 10.1088/1748-9326/abf58a
40. Forest Canopy Gap Distributions in the Southern Peruvian Amazon G. Asner et al. 10.1371/journal.pone.0060875
41. SMOS retrieval over forests: Exploitation of optical depth and tests of soil moisture estimates C. Vittucci et al. 10.1016/j.rse.2016.03.004
42. Magnitude, spatial distribution and uncertainty of forest biomass stocks in Mexico P. Rodríguez-Veiga et al. 10.1016/j.rse.2016.06.004
43. Spatial variability in tropical forest leaf area density from multireturn lidar and modeling M. Detto et al. 10.1002/2014JG002774
44. Selective logging emissions and potential emission reductions from reduced-impact logging in the Congo Basin P. Umunay et al. 10.1016/j.foreco.2019.01.049
45. Remote sensing of forest degradation in Southeast Asia—Aiming for a regional view through 5–30 m satellite data J. Miettinen et al. 10.1016/j.gecco.2014.07.007
46. Towards the use of satellite-based tropical forest disturbance alerts to assess selective logging intensities A. Welsink et al. 10.1088/1748-9326/acd018
47. Linking imaging spectroscopy and LiDAR with floristic composition and forest structure in Panama M. Higgins et al. 10.1016/j.rse.2013.09.032
48. Genetic diversity of Astronium graveolens Jacq. in Colombian seasonally dry tropical forest: support for the dry forest refugia hypothesis? E. Thomas et al. 10.1016/j.ppees.2021.125642
49. Hydrological effects of tree invasion on a dry coastal Hawaiian ecosystem B. Dudley et al. 10.1016/j.foreco.2019.117653
50. Modeling plant–water interactions: an ecohydrological overview from the cell to the global scale S. Fatichi et al. 10.1002/wat2.1125
51. UAV LiDAR for below-canopy forest surveys R. Chisholm et al. 10.1139/juvs-2013-0017
52. The linkages between photosynthesis, productivity, growth and biomass in lowland Amazonian forests Y. Malhi et al. 10.1111/gcb.12859
53. Variations in forest aboveground biomass in Miyun Reservoir of Beijing over the past two decades L. Fu et al. 10.1007/s11368-017-1718-0
54. Markedly divergent estimates of Amazon forest carbon density from ground plots and satellites E. Mitchard et al. 10.1111/geb.12168
55. Airborne laser scanning for terrain modeling in the Amazon forest M. ANDRADE et al. 10.1590/1809-4392201800132
56. Carbon Farming: Prospects and Challenges M. Sharma et al. 10.3390/su131911122
57. An integrated pan‐tropical biomass map using multiple reference datasets V. Avitabile et al. 10.1111/gcb.13139
58. Estimating aboveground carbon density across forest landscapes of Hawaii: Combining FIA plot-derived estimates and airborne LiDAR R. Hughes et al. 10.1016/j.foreco.2018.04.053
59. CO2 Capture Capacity Measurement Using Multitemporal Analysis and Biophysical Variables in a Tropical Humid Forest in the Colombian Andes L. Vega et al. 10.3390/su16114809
60. High-fidelity national carbon mapping for resource management and REDD+ G. Asner et al. 10.1186/1750-0680-8-7
61. 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
62. Design and Testing of a Novel Unoccupied Aircraft System for the Collection of Forest Canopy Samples S. Krisanski et al. 10.3390/f13020153
63. Monitoring tropical forest carbon stocks and emissions using Planet satellite data O. Csillik et al. 10.1038/s41598-019-54386-6
64. Optimizing aboveground carbon mapping in Afrotemperate forests to fulfil IPCC carbon reporting standards J. Fisher 10.1016/j.foreco.2023.121583
65. Landscape-scale changes in forest structure and functional traits along an Andes-to-Amazon elevation gradient G. Asner et al. 10.5194/bg-11-843-2014
66. Forest biomass mapping with airborne LiDAR in Yokohama City M. HAYASHI et al. 10.4287/jsprs.52.306
67. Estimating aboveground carbon using airborne LiDAR in Cambodian tropical seasonal forests for REDD+ implementation T. Ota et al. 10.1007/s10310-015-0504-3
68. A Tale of Two “Forests”: Random Forest Machine Learning Aids Tropical Forest Carbon Mapping J. Mascaro et al. 10.1371/journal.pone.0085993
69. Environmental variables controlling soil organic carbon in top- and sub-soils in karst region of southwestern China J. Zhu et al. 10.1016/j.ecolind.2018.03.073
70. Carbon Stocks in Peri-Urban Areas: A Case Study of Remote Sensing Capabilities P. Villa et al. 10.1109/JSTARS.2014.2328862
71. Estimation of Airborne Lidar-Derived Tropical Forest Canopy Height Using Landsat Time Series in Cambodia T. Ota et al. 10.3390/rs61110750
72. Continuous monitoring of land change activities and post-disturbance dynamics from Landsat time series: A test methodology for REDD+ reporting P. Arévalo et al. 10.1016/j.rse.2019.01.013
73. Mapping Global Forest Aboveground Biomass with Spaceborne LiDAR, Optical Imagery, and Forest Inventory Data T. Hu et al. 10.3390/rs8070565
74. Generalized models for subtropical forest inventory attribute estimations using a rule-based exhaustive combination approach with airborne LiDAR-derived metrics C. Li et al. 10.1080/15481603.2023.2194601
75. Multi-Resolution Mapping and Accuracy Assessment of Forest Carbon Density by Combining Image and Plot Data from a Nested and Clustering Sampling Design E. Yan et al. 10.3390/rs8070571
76. Classification of multilayered forest development classes from low-density national airborne lidar datasets R. Valbuena et al. 10.1093/forestry/cpw010
77. Country-wide high-resolution vegetation height mapping with Sentinel-2 N. Lang et al. 10.1016/j.rse.2019.111347
78. Spatially-Explicit Testing of a General Aboveground Carbon Density Estimation Model in a Western Amazonian Forest Using Airborne LiDAR P. Molina et al. 10.3390/rs8010009
79. Degradation impacts on riparian forests of the lower Mearim river, eastern periphery of Amazonia R. da Silva et al. 10.1016/j.foreco.2017.07.019
80. A dataset of forest biomass structure for Eurasia D. Schepaschenko et al. 10.1038/sdata.2017.70
81. The Role and Need for Space-Based Forest Biomass-Related Measurements in Environmental Management and Policy M. Herold et al. 10.1007/s10712-019-09510-6
82. Improving LandTrendr Forest Disturbance Mapping in China Using Multi-Season Observations and Multispectral Indices D. Qiu et al. 10.3390/rs15092381
83. Canopy Height and Above-Ground Biomass Retrieval in Tropical Forests Using Multi-Pass X- and C-Band Pol-InSAR Data A. Berninger et al. 10.3390/rs11182105
84. Intercomparison of the DART model and GEDI simulator for simulating GEDI waveforms in forests Z. Wang et al. 10.1016/j.jag.2024.104148
85. Spatial Structure of Above-Ground Biomass Limits Accuracy of Carbon Mapping in Rainforest but Large Scale Forest Inventories Can Help to Overcome S. Guitet et al. 10.1371/journal.pone.0138456
86. Computer and remote‐sensing infrastructure to enhance large‐scale testing of individual‐based forest models H. Shugart et al. 10.1890/140327
87. Large-scale estimation of change in aboveground biomass in miombo woodlands using airborne laser scanning and national forest inventory data L. Ene et al. 10.1016/j.rse.2016.10.046
88. Above ground biomass estimation in an African tropical forest with lidar and hyperspectral data G. Vaglio Laurin et al. 10.1016/j.isprsjprs.2014.01.001
89. Harvesting tree biomass at the stand level to assess the accuracy of field and airborne biomass estimation in savannas M. Colgan et al. 10.1890/12-0922.1
90. Current remote sensing approaches to monitoring forest degradation in support of countries measurement, reporting and verification (MRV) systems for REDD+ A. Mitchell et al. 10.1186/s13021-017-0078-9
91. Environmental drivers of tree community turnover in western Amazonian forests C. Baldeck et al. 10.1111/ecog.01575
92. Monitoring selective logging in western Amazonia with repeat lidar flights H. Andersen et al. 10.1016/j.rse.2013.08.049