Publications

2026

  1. Sánchez-López, N., Hudak, A. T., Xia, J., Robertson, K., Bright, B. C., Prichard, S., Nemens, D. G., Hawley, C., Loudermilk, E. L., Keane, R., Woodall, C. W., Mauro, F., Boschetti, L., Silva, C. A., & Cabo, C. (2026). Modeling tree crown-mediated accumulation of downed woody debris in fire-maintained longleaf pine forests of the southeastern US from laser scanning data. Fire Ecology. https://doi.org/10.1186/s42408-026-00548-7
  2. Fareed, N., Silva, C. A., Gaskins, A. J., Prichard, S. J., Hudak, A. T., Xia, J., & Alvites Diaz, C. I. (2026). From Wood–Foliar Semantics to 3D Fuel Characterization: Transferable Deep Learning for Terrestrial LiDAR Across Global Forest Ecosystems. Remote Sensing, 18(18), 3158. https://doi.org/10.3390/rs18183158
  3. Hudak, A. T., Bakken, J. L., Lister, A., Mauro, F., Gregory, M. J., Riley, K., Wilson, B. T., Santoro, M., Healey, S. P., Ma, L., Yu, Y., Bright, B. C., Byrne, J. C., Mita, R., Houtman, R., Shaw, J. D., Fekety, P. A., Domke, G. M., Walters, B. F., Bell, D. M., Weiskittel, A., Atkins, J. W., Duncanson, L., Hunka, N., Kennedy, R., Babcock, C., Saatchi, S., Raczka, B., Silva, C., Tang, H., & Hurtt, G. (2026). A quantitative evaluation of forest aboveground biomass density map products in Oregon, USA. Environmental Research Letters, 21, 143007. https://doi.org/10.1088/1748-9326/ae8b04
  4. Corado, L., Godinho, S., Silva, C. A., Pascual, A., Guerra-Hernández, J., Valerio, F., Gonçalves, T., & Salgueiro, P. (2026). GEDICorrect: A scalable Python tool for orbit-, beam-, and footprint-level GEDI geolocation correction. Science of Remote Sensing, 14, 100469. https://doi.org/10.1016/j.srs.2026.100469
  5. Prichard, S. J., Nemens, D. G., Rowell, E., Batchelor, J. L., Bester, M. S., Bright, B. C., Cova, G. R., Cronan, J. B., Drye, B., Hudak, A. T., Eagle, P. C., Kennedy, M. C., Loudermilk, E. L., Redford, H. E., Parsons, R. A., Silva, C. A., Skowronski, N. S., & Thoreson, J. (2026). Hierarchically scaled remote sensing and field datasets for three-dimensional wildland fuel characterization. Fire Ecology. https://doi.org/10.1186/s42408-026-00507-2
  6. Duncanson, L., Montesano, P. M., Neuenschwander, A., Zarringhalam, A., Thomas, N., Minor, D. M., Wulder, M. A., White, J. C., Guenther, E., Feng, T., Leitold, V., Hancock, S., Armston, J., Puliti, S., Mandel, A. I., Shah, S., Silva, C., Purslow, M., Bruening, J., Breidenbach, J., Næsset, E., Saarela, S., Hunka, N., Kellner, J. R., Healey, S. P., Schepaschenko, D., Wallerman, J., Neigh, C. S. R., Carvalhais, N., & Dubayah, R. (2026). Global and boreal estimates of woody aboveground biomass for 2020: Filling GEDI's northern data gap with ICESat-2 and Harmonized Landsat Sentinel-2. Remote Sensing of Environment, 340, 115406. https://doi.org/10.1016/j.rse.2026.115406
  7. Zheng, C., Magee, L., Cayetano, D., Rocha, K. D., Lu, Y., Bohlman, S., et al. (2026). Discriminating temporal decline and death of a savanna oak using multi-year imaging spectroscopy. Remote Sensing Applications: Society and Environment, 43, 102117. https://doi.org/10.1016/j.rsase.2026.102117
  8. Preprint / discussion paperMitra, A., Harris, N., Gamarra, J. G. P., Bastian, M. L., Crowther, T. W., Picard, N., Herold, M., Hui, C., de-Miguel, S., Powell, W. G., Beane, N. R., Shallock, J. R., van der Plas, F., Lawes, M. J., Zhou, M., Jahanshahi, M., Tchebakova, N. M., Parfenova, E. I., Reich, P., et al., including Silva, C. A., et al. (2026). The global forest diameter spectrum using a machine learning approach. Earth System Science Data Discussions. https://doi.org/10.5194/essd-2026-226
  9. Gaskins, A. J., Xia, J., Bueno, I. T., & Silva, C. A. (2026). Advancing terrestrial laser scanning for 3D classification of Spanish moss (Tillandsia usneoides L.) using unsupervised, machine learning, and deep learning methods. Scientific Reports, 16, 18295. https://doi.org/10.1038/s41598-026-49230-7
  10. Cardil, A., Rodrigues, M., Ascoli, D., Ortega, M., Quiñones, T., Erdozain, M., Oliveras Menor, I., Spadoni, G. L., Ramírez, J., Molina, J. R., Mouillot, F., Silva, C. A., Mohan, M., Martínez-Bentué, C., & de-Miguel, S. (2026). Protected areas influence fire regimes globally. Journal of Environmental Management, 398, 128285. https://doi.org/10.1016/j.jenvman.2025.128285

2025

  1. Haneda, L. E., Brancalion, P. H. S., Valle, D., Silva, C. A., Gorgens, E. B., Prata, G. A., Kamimura, R. A., Gomes, S. H. M., Sanchez, A. K., Almeida, D. R. A. Edge effect impacts on forest structure and carbon stocks in REDD+ projects: An assessment in the Amazon using UAV‑LiDAR. Forest Ecology and Management, 585, 122646 (2025). https://doi.org/10.1016/j.foreco.2025.122646
  2. Santoro, G. B., Molin, P. G., Viveiros, J. M. S. M., Ferreira, G. de A., Costa, V. M., Haneda, L. E., Sinegalia, M. K. S. D., Cullen Jr, L., Brancalion, P. H. S., Silva, C. A., Almeida, D. R. A. de Monitoring the structure of restored forests and assessing aboveground carbon density through canopy metrics derived from digital aerial photogrammetry and LiDAR. Restoration Ecology. https://doi.org/10.1111/rec.70077
  3. Jiang, F., Pu, X., Schmid, B., Reich, P. B., Liang, J., Abbasi, A. O., *et al.* Mycorrhizal symbioses and tree diversity in global forest communities. Science Advances, 11, eadt5743 (2025). https://doi.org/10.1126/sciadv.adt5743
  4. Xia, J., Martin, T. A., Peter, G. F., Brock, K. M., Atkins, J. W., Gitzendanner, M. A., Bueno, I., Calders, K., Dalla Corte, A. P., Hudak, A. T., Schlickmann, M. B., Andreu, M. G., Hamamura, C., Klauberg, C., Silva, C. A. Combined impact of semantic segmentation and quantitative structure modelling of Southern pine trees using terrestrial laser scanning. Scientific Reports, 15, 24427 (2025). https://doi.org/10.1038/s41598-025-09681-w
  5. Karasinski, M. A., Leite, R. d. S., Guaraná, E. C., Figueiredo, E. O., Broadbent, E. N., Silva, C. A., Santos, E. K. M., Sanquetta, C. R., Dalla Corte, A. P. Automated Detection of Araucaria angustifolia (Bertol.) Kuntze in Urban Areas Using Google Earth Images and YOLOv7x. Remote Sensing, 17, 809 (2025). https://doi.org/10.3390/rs17050809
  6. Bueno, I. T., Silva, C. A., Hamamura, C., Donovan, V. M., Sharma, A., Qiu, J., Xia, J., Brock, K. M., Schlickmann, M. B., Atkins, J. W., Valle, D. R., Vogel, J., Susaeta, A., Karasinski, M. A., Klauberg, C. Aboveground biomass density maps for post‑hurricane Ian forest monitoring in Florida. Scientific Data, 12, 1189 (2025). https://doi.org/10.1038/s41597-025-05464-0
  7. Bueno, I. T., Silva, C. A., Schlickmann, M. B., Donovan, V. M., Atkins, J. W., Brock, K. M., Xia, J., Valle, D. R., Qiu, J., Vogel, J., White, K. L., Xu, L. M., Young, M. N., Zeng, O. P. Upscaling Frameworks Drive Prediction Accuracy and Ununcertainty When Mapping Aboveground Biomass Density from the Synergism of Spaceborne LiDAR, SAR, and Passive Optical Data. Remote Sensing, 17, 2340 (2025). https://doi.org/10.3390/rs17142340
  8. Vedovato, L. B., Aragão, L. E. O. C., Almeida, D. R. A., Bartholomew, D. C., Assis, M., Dalagnol, R., Gorgens, E. B., Silva-Junior, C. H. L., Ometto, J. P., Pontes-Lopes, A., Silva, C. A., Valbuena, R., Feldpausch, T. R. Impacts of fire on canopy structure and its resilience depend on successional stage in Amazonian secondary forests. Remote Sensing in Ecology and Conservation. https://doi.org/10.1002/rse2.431
  9. Duncanson, L., Hunka, N., Jucker, T., Armston, J., Harris, N., Fatoyinbo, L., Williams, C. A., Atkins, J. W., Raczka, B., Serbin, S., Keller, M., Dubayah, R., Babcock, C., Cochrane, M. A., Hudak, A., Hurtt, G. C., Montesano, P. M., Moskal, L. M., Park, T., Saatchi, S., Silva, C. A., Tang, H., Vargas, R., Weiskittel, A., Wessels, K., & Goetz, S. J. (2025). Spatial resolution for forest carbon maps. Science, 387(6732), 371. https://doi.org/10.1126/science.adv6429
  10. Schlickmann, M.B.; Bueno, I.T.; Valle, D.; Hammond, W.M.; Prichard, S.J.; Hudak, A.T.; Klauberg, C.; Karasinski, M.A.; Brock, K.M.; Rocha, K.D.; Silva, C.. Statewide Forest Canopy Cover Mapping of Florida Using Synergistic Integration of Spaceborne LiDAR, SAR, and Optical Imagery. Remote Sens. 2025, 17, 320. https://doi.org/10.3390/rs17020320
  11. Almeida, D. R. A. de, Vedovato, L. B., Fuza, M., Molin, P., Cassol, H., Resende, A. F., Krainovic, P. M., de Almeida, C. T., Amaral, C., Haneda, L., Albuquerque, R. W., Gorgens, E., Romanelli, J., Ferreira, M., Salk, C., Espinoza, N., Silva, C., Broadbent, E., & Brancalion, P. H. S. (2024). Remote sensing approaches to monitor tropical forest restoration: Current methods and future possibilities. Journal of Applied Ecology. https://doi.org/10.1111/1365-2664.14830
  12. Bueno, I.T.; Silva, C.A.; Anderson-Teixeira, K.; Magee, L.; Zheng, C.; Broadbent, E.N.; Zambrano, A.M.A.; Johnson, D.J. Aboveground Biomass and Tree Mortality Revealed Through Multi-Scale LiDAR Analysis. Remote Sens. 2025, 17, 796. https://doi.org/10.3390/rs17050796
  13. Forkel, M., Wessollek, C., Andela, N., de Laat, J., Huijnen, V., Kinalczyk, D., Marrs, C., van Wees, D., Bastos, A., Ciais, P., Fawcett, D., Kaiser, J. W., Kutchartt, E., Klauberg, C., Leite, R. V., Li, W., Silva, C., Sitch, S., Goncalves De Souza, J., & Plummer, S. (2024). Burning of woody debris dominates fire emissions in the Amazon and Cerrado. Nat. Geosci. 18, 140–147 (2025). https://doi.org/10.1038/s41561-024-01637-5
  14. Rex, F.E.; Silva, C.A.; Broadbent, E.N.; Dalla Corte, A.P.; Leite, R.; Hudak, A.; Hamamura, C.; Latifi, H.; Xiao, J.; Atkins, J. Spatial Characterization of Woody Species Diversity in Tropical Savannas Using GEDI and Optical Data. Sensors 2025, 25, 308. https://doi.org/10.3390/s25020308

2024

  1. Leitep, R.V., Amaral, C., Neigh, C.S.R., Cosenza, D.N., Klauberg, C., Hudak, A.T., Aragão, L., Morton, D.C., Coffield, S., McCabe, T. and Silva, C.A. (2024), Leveraging the next generation of spaceborne Earth observations for fuel monitoring and wildland fire management. Remote Sens Ecol Conserv. https://doi.org/10.1002/rse2.416
  2. Montagnoli, A., Hudak, A. T., Raumonen, P., Lasserre, B., Terzaghi, M., Silva, C. A., Bright, B. C., Vierling, L. A., Vasconcellos, B. N. de, Chiatante, D., & Dumroese, R. K. (2024). Terrestrial laser scanning and low magnetic field digitization yield similar architectural coarse root traits for 32-year-old Pinus ponderosa trees. Plant Methods, 20, 102. https://doi.org/10.1186/s13007-024-01229-9
  3. Viedma, O., Silva, C. A., Moreno, J. M., & Hudak, A. T. (2024). LadderFuelsR: A new automated tool for vertical fuel continuity analysis and crown base height detection using light detection and ranging. Methods in Ecology and Evolution, August 2024, https://doi.org/10.1111/2041-210X.14427
  4. Cardil, A., Rodrigues, M., Barbero, R. Ramirez, J., Stoof, C., Silva, C., Mohan, M. Reply to: Satellite artifacts modulate FireCCILT11 global burned area. Nature Communication 15, 2080 (2024). https://doi.org/10.1038/s41467-024-46169-z
  5. Blanton, A., Mohang, M., Galgamuwa, G.A.P., Watt, M.S., Montenegro, J.F., Mills, F., Carlsen, S.C.H., Valasquez-Camacho, L., Bomfim, B., Pons, J., Broadbent, E.N., Kaur, A., Direk, S., de-Miguel, S., Ortega, M., Abdullah, M., Rondon, M., Wan Mohd Jaafar, W.S., Silva, C.A., Cardil, A., Doaemo, W., Ewane, B.E. (2024). The status of forest carbon markets in Latin America. Journal of Environmental Management, 352, 119921. https://doi.org/10.1016/j.jenvman.2023.119921

2023

  1. Merrick, T.; Bennartz, R.; Jorge, M.L.S.P.; Merrick, C.; Bohlman, S.A.; Silva, C.A.; Pau, S. (2023). Comparing Phenology of a Temperate Deciduous Forest Captured by Solar-Induced Fluorescence and Vegetation Indices. Remote Sens. 2023, 15, 5101. https://doi.org/10.3390/rs15215101
  2. Hooman, L., Valbuena, R., Silva, C.A. (2023). Towards Complex Applications of Active Remote Sensing for Ecology and Conservation. Methods in Ecology and Evolution. v. 14; p1578–1586. https://doi.org/10.1111/2041-210X.14154
  3. Abbasi, A., Tang, X., Harris, N.L., Goldman, E.D., Gamarra, J.G.P., Herold,M., Kim, H.S., Luo, W., Silva, C.A., Tchebakova, N.M., Mitra,A., Finegold, Y., Jahanshahi, M.R, Alvarez, C.I., Kim, T. K., Ryu, D., Liang, J. (2023). Artificial-intelligence augmented spatial database of planted trees (A-SDPT) in East Asia. Scientific Data. 10(1):480. https://doi.org/10.1038/s41597-023-02383-w
  4. Pinagép, E., Longo, M., Csillik, O., Huete, A., David, Silva, C., Keller, M. (2023). Surface energy dynamics and canopy structural properties in intact and disturbed forests in the Southern Amazon. Journal of Geophysical Research. 128(9): 96-114. https://doi.org/10.1029/2023JG007465
  5. Cardil, A., Monedereo, S., Selegue, P., De Miguel, S., Marshall, g., Chavez, T., Silva, C.A., Ramirez, J. (2023). Performance of operational fire spread models in California. International Journal of Wildland Fire. 32(11), 1492–1502 . https://doi.org/10.1071/WF22128
  6. Crockettp, E. T.H., Atkins, J. W., Guo, Q., Sun, G., Potter, K. M., Ollinger, S., Silva, C.A., Tang, H.A., Woodall, C. W., Holgerson, J., Xiao, J. (2023). Structural and species diversity are associated with aboveground carbon storage in forests across the United States: evidence from GEDI and forest inventory data. Remote Sensing of Environment. 295(2): 113703. https://doi.org/10.1016/j.rse.2023.113703
  7. Atkins, J. W., Costanza, J., Dahlin, K. M., Dannenberg, M. P., Elmore, A. J., Fitzpatrick, M. C., Hakkenberg, C. R., Hardiman, B. S., Kamoske, A., LaRue, E. A., Silva, C. A., Stovall, A. E. L., Tielens, E. K. (2023). Scale dependency of lidar-derived forest structural diversity. Methods in Ecology and Evolution, 14, 708– 723. https://doi.org/10.1111/2041-210X.14040
  8. Haneda, L.E., Brancalion, P.H., Molin, P.G., Ferreira, M.P., Silva, C.A., de Almeida, C.T., Resende, A.F., Santoro, G.B., Rosa, M., Guillemot, J., Le Maire, G. (2023). Forest landscape restoration: SPECTRAL behavior and diversity of tropical tree cover classes. Remote Sens. Appl.: Society and Environment . https://doi.org/10.1016/j.rsase.2022.100882
  9. Ewane, E.B.; Mohan, M.; Bajaj, S.; Galgamuwa, G.A.P.; Watt, M.S.; Arachchige, P.P.; Hudak, A.T.; Richardson, G.; Ajithkumar, N.; Srinivasan, S.; Corte, A.P.D.; Johnson, D.J.; Broadbent, E.N.; de-Miguel, S.; Bruscolini, M.; Young, D.J.N.; Shafai, S.; Abdullah, M.M.; Jaafar, W.S.W.M.; Doaemo, W.; Silva, C.A.; Cardil, A. (2023) Climate-Change-Driven Droughts and Tree Mortality: Assessing the Potential of UAV-Derived Early Warning Metrics. Remote Sens., 15, 2627. https://doi.org/10.3390/rs15102627
  10. Sánchez-Lópezp, N., Hudak, A.T., Boschetti, L., Silva, C.A., Robertson, K., Loudermilk, E.L., Bright, B.C., Callaham, M.A., Taylor, M.K., (2023). A spatially explicit model of tree leaf litter accumulation in fire maintained longleaf pine forests of the southeastern USA. Ecological Modelling. Vol. 481. https://doi.org/10.1016/j.ecolmodel.2023.110369
  11. Heinrichg, V. H. A., Vancutsem, C., Dalagnol, R., Rosan, T. M., Fawcett, D., Silva-Junior, C. H. L., Cassol, H. L. G., Achard, F., Jucker, T., Silva, C. A., House, Jo., Sitch, S., Hales, T., Aragão, Luiz E. O. C. (2023). The carbon sink of secondary and degraded humid tropical forests. Nature. 615, 436–442. https://doi.org/10.1038/s41586-022-05679-w
  12. Scheeresg, J.ç, Jong, J.J.ç Brede, B., Brancalion, P., Broadbent, E. ; Zambrano, A. M.; Gorgens, E. B.; Silva, C. A.; Valbuena, R.; Molin, P.; Stark, S.; Rodrigues, R.; Sandoro, G.; Resende, A.; Almeida, C. T.; Almeida, D. R. A (2023). Distinguishing forest types in restored tropical landscapes with UAV-borne LiDAR. Remote Sensing of Environment. Vol 29, 15. https://doi.org/10.1016/j.rse.2023.113533.
  13. Cardil, A., Rodrigues, M., Tapia, M., Barbero, R., Ramírez, J., Stoof, C.R., Silva, C.A., Mohan M., de-Miguel, S. Climate teleconnections modulate global burned area. Nature Communication 14, 427 (2023). https://doi.org/10.1038/s41467-023-36052-8
  14. Klauberg, C.; Vogel, J.; Dalagnol, R.; Ferreira, M.P.; Hamamurap, C.; Broadbent, E.; Silva, C.A. Post-Hurricane Damage Severity Classification at the Individual Tree Level Using Terrestrial Laser Scanning and Deep Learning. Remote Sens. 2023, 15, 1165. https://doi.org/10.3390/rs15041165
  15. Rocha, K.D.; Silva, C.A.; CosenzaP, D.N.; Mohang, M.; Klauberg, C.; SchlickmannG, M.B.; XiaG, J.; LeiteG, R.V.; Almeida, D.R.A.d.; Atkins, J.W.; Cardil, A.; Rowell, E.; Parsons, R.; Sánchez-López, N.; Prichard, S.J.; Hudak, A.T. (2023). Crown-Level Structure and Fuel Load Characterization from Airborne and Terrestrial Laser Scanning in a Longleaf Pine (Pinus palustris Mill.) Forest Ecosystem. Remote Sens. 15, 1002. https://doi.org/10.3390/rs15041002

2022

  1. Liang, J., Gamarra, J.G.P., Picard, N., Silva, C. et al. Co-limitation towards lower latitudes shapes global forest diversity gradients. Nature Ecology and Evolution 6, 1423–1437 (2022). https://doi.org/10.1038/s41559-022-01831-x
  2. Leite, R. V., Silva, C.A., Amaral, C. H., Liebenberg, V., Almeida, D. R. A., Midhun, M. et al. Large scale multi-layer fuel load characterization in tropical savanna using GEDI spaceborne lidar data. Remote Sensing of Environment. 268, Jan 2022, 112764. https://doi.org/10.1016/j.rse.2021.112764
  3. Duncanson, L.; Kellner, J. R. et. al. Aboveground biomass density models for NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar mission, Remote Sensing of Environment, Volume 270,2022,112845 https://doi.org/10.1016/j.rse.2021.112845.
  4. Haneda, L. Brancalion, P. H. S., Molin, P.G., Ferreira, M.P., Silva,C.A., Almeida, C.T., Resende, A.F., Santoro, G.B., Rosa, M., Guillemot, J., Maire, G.L., Feret, J.B., Almeida, D.R.A.. Forest landscape restoration: Spectral behavior and diversity of tropical tree cover classes, Remote Sensing Applications: Society and Environment, 29, 2023. https://doi.org/10.1016/j.rsase.2022.100882
  5. Cosenza, D. N.; Vogel, J., Broadbent, E. N, Silva, C.A. 2022. Silvicultural experiment assessment using lidar data collected from an unmanned aerial vehicle, Forest Ecology and Management https://doi.org/10.1016/j.foreco.2022.120489.
  6. Adrah, E.; Wan Mohd Jaafar, W.S.; Omar, H.; Bajaj, S.; Leite, R.V.; Mazlan, S.M.; Silva, C.A.; Chel Gee Ooi, M.; Mohd Said, M.N.; Abdul Maulud, K.N.; Cardil, A.; Mohan, M. Analyzing Canopy Height Patterns and Environmental Landscape Drivers in Tropical Forests Using NASA’s GEDI Spaceborne LiDAR. Remote Sens. 2022, 14, 3172. https://doi.org/10.3390/rs14133172
  7. Silva, C.A.; Hudak, A.T; Vierling, L.A.; Valbuena, R.; Cardil, A.; Mohan, M.; Almeida, D. A.; Broadbent,E.N.; Zambrano,A. M. A.; Wilkinson, B., Sharma,A., Drake,J. B.; Medley,P. B., Vogel, J. G.; Prata,G. A.; Atkins, J.; Hamamura,C.; Klauberg, C. 2021. TreeTop: A Shiny-based Application for Extracting Forest Information from LiDAR data for Ecologists and Conservationists. Methods in Ecology and Evolution. V13, pg1164-1176. https://doi.org/10.1111/2041-210X.13830
  8. Valle; D,; Silva, C.; Longo, M.; Silverio, D.V.; Maracahipes, L.; Brando, P. Mapping forest degradation using the Latent Dirichlet Allocation model applied to airborne LiDAR data: a case study on the effect of forest fragmentation and fire in the Amazon region. Methods in Ecology and Evolution. 2021, in review. 2022. V. 13, pg 1329-1342 https://doi.org/10.1111/2041-210X.13836
  9. Stitt, J.M.; Hudak, A.T.; Silva, C.A.; Vierling, L.A.; Vierling, K.T. Evaluating the Use of Lidar to Discern Snag Characteristics Important for Wildlife. Remote Sens. 2022, 14, 72. https://doi.org/10.3390/rs14030720
  10. Pinagé, E. R., Bell, D., Longo, M., Gao, S., Keller, M., Silva, C.A., Köhler, P., Frankenberg, C., Huet, A. Forest structure and photosynthesis across intact and degraded forests in the Amazon. Remote Sensing of Environment. V. 274. https://doi.org/10.1016/j.rse.2022.112998
  11. Atkins, Jeff W.; Stovall, Atticus E.L.; Silva, C. 2022. Open-Source tools in R for forestry and forest ecology. Forest Ecology and Management. 503(6): 119813. https://doi.org/10.1016/j.foreco.2021.119813
  12. Corte, A.P.D.; da Cunha Neto, E.M.; Rex, F.E.; Souza, D.; Behling, A.; Mohan, M.; Sanquetta, M.N.I.; Silva, C.A.; Klauberg, C.; Sanquetta, C.R.; Veras, H.F.P.; de Almeida, D.R.A.; Prata, G.; Zambrano, A.M.A.; Trautenmüller, J.W.; de Moraes, A.; Karasinski, M.A.; Broadbent, E.N. High-Density UAV-LiDAR in an Integrated Crop-Livestock-Forest System: Sampling Forest Inventory or Forest Inventory Based on Individual Tree Detection (ITD). Drones 2022, 6, 48. https://doi.org/10.3390/drones6020048
  13. Silveira, A. B., Carvalho, S. P. C., Nicoletti, M. N., Silva, C.A., Drescher, R.,Carvalho, M. L. C., Madi, J.P.S., Topanotti, L. R., Zeviani, W. M.,Andrade, V. C. L 2022.Impact of plot size on tropical forest structure and diversity estimation. Revista de Biología Tropical. Vol. 70: 437-449 https://doi.org/10.15517/rev.biol.trop.2022.48640
  14. Stoddart, J.; de Almeida, D.R.A.; Silva, C.A.; Görgens, E.B.; Keller, M.; Valbuena, R. A Conceptual Model for Detecting Small-Scale Forest Disturbances Based on Ecosystem Morphological Traits. Remote Sens. 2022, 14, 933. https://doi.org/10.3390/rs14040933
  15. Dalla Corte, A.P.; de Vasconcellos, B.N.; Rex, F.E.; Sanquetta, C.R.; Mohan, M.; Silva, C.A..; Klauberg, C.; de Almeida, D.R.A.; Zambrano, A.M.A.; Trautenmüller, J.W.; Leite, R.V.; do Amaral, C.H.; Veras, H.F.P.; Rocha, K.d.S.; de Moraes, A.; Karasinski, M.A.; Sanquetta, M.N.I.; Broadbent, E.N. Applying High-Resolution UAV-LiDAR and Quantitative Structure Modelling for Estimating Tree Attributes in a Crop-Livestock-Forest System. Land 2022, 11, 507. https://doi.org/10.3390/land11040507

2021

  1. Silva, C.A., Duncansona, L., Hancockb, S., Neuenshwanderc, A., Thomasd, N., Hofton, M., Fatoyinboa, L., Simardd, M., Armston, J., Dubayah, R. Fusing simulated GEDI, ICESat-2 and NISAR data for regional aboveground biomass mapping. Remote Sensing of Environment. 2021. v253. https://doi.org/10.1016/j.rse.2020.112234
  2. Silva Junior, C.H.L.; Carvalho, N.S.; Pessôa, A.C.M.; Reis, J.; Pontes-Lopes, A.; Doblas, J.; Heinrich, V.; Campanharo, W.; Alencar, A.; Silva, C.; Lapola, D.; Armenteras, D.; Matricardi, E. A. T.; Berenguer, E.; Cassol, H.; Numata, I.; House, J.; Ferreira, J.; Barlow; J.; Gatti, L.; Brando, P.; Fearnside, P.; Saatchi, S.; Silva, S.; Sitch, S.; Aguiar, A.P.; Silva, C. A.; Vancutsem, C.; Achard, F.; Beuchle, R.; Shimabukuro; Y.; Anderson, L.; Aragão, L, E. O. C. Amazonian forest degradation must be incorporated into the COP26 agenda Integrating . Nature Geoscience. 14, 634–635 (2021). https://doi.org/10.1038/s41561-021-00823-z
  3. Russell, M.; Eitel, J.U.H.; Link, T.E.; Silva, C.A. Important Airborne Lidar Metrics of Canopy Structure for Estimating Snow Interception. Remote Sens. 2021, 1, 4188. https://doi.org/10.3390/rs13204188
  4. Santos, L. H. O., Madi, J. P. S., Díaz, L. M. G. R., Ramirez, G. M., Souza, É. C., Nunes, G. M., Corte, A. P. D., Carvalho, M. P. L. C., Silva, C. A., & Carvalho, S. P. C. (2021). Relationship between spectral variables with RapidEye images and dendrometric variables in teak plantations using principal component analysis. Scientia Forestalis, 49(132), e3655. https://doi.org/10.18671/scifor.v49n132.09
  5. Stitt, J. M.; Hudak, A. T.; Silva, C.A.; Vierling, L.; Vierling, K. Characterizing individual tree-level snags using airborne lidar-derived forest canopy gaps within closed-canopy conifer forests. Methods in Ecology and Evolution. 2021;00:1–12. https://doi.org/10.1111/2041-210X.13752
  6. Faria, B. L., Staal, A., Carlos A. Silva, C. A., Martin, P.A., Panday, P.K., Dantas, V. Climate change and deforestation increase the vulnerability of Amazonian forests to post-fire grass invasion. Global Ecology and Biogeography. 00:1–14. https://doi.org/10.1111/geb.13388
  7. d’Oliveira, M. V. N., Figueiredo, E. O., Almeida; D. R. A., Oliveira; L. C., Silva, C. A., Nelson4, B. W., Cunha, R. M., Papa, D. A., Stark, C. C., Valbuena, R. Impacts of selective logging on Amazon forest canopy structure and biomass with a cost-effective LiDAR and photogrammetric survey sequence. Forest Ecology and Management. V 500, 15 Nov 2021, 119648. https://doi.org/10.1016/j.foreco.2021.119648
  8. Cardil, A., Monedero, S., Schag, G., de-Miguel, s., Tapia, M., Stoof, C., Silva, c.A., Mohan, M., Cardil, A., Ramirez, J. Fire behavior modeling for operational decision-making. Current Opinion in Environmental Science & Health. 2021, 23, 100291l https://doi.org/10.1016/j.coesh.2021.100291
  9. Dorado-Roda, I.; Pascual, A.; Godinho, S.; Silva, C.A.; Botequim, B.; Rodríguez-Gonzálvez, P.; González-Ferreiro, E.; Guerra-Hernández, J. Assessing the Accuracy of GEDI Data for Canopy Height and Aboveground Biomass Estimates in Mediterranean Forests. Remote Sens. 2021, 13, 2279. https://doi.org/10.3390/rs13122279
  10. Almeida, D. R. A.,Broadbent, E. N., Ferreira, M.P., Meli, P., Zambrano, A. M. A., Gorgens, E. B., Resende, F. R., Silva, T. S. F., Almeida, C. T., Amaral8, C. H., Corte, A. P. D.,Silva, C. A., et al. Monitoring restored tropical forest diversity and structure through UAV-borne hyperspectral and lidar fusion. Remote Sensing of Environment. 2021, 264, 112582. https://doi.org/10.1016/j.rse.2021.112582
  11. Fatoyinbo, L., Armston, J., Simard, M., Saatchi, S., Denbina, M., Lavalle, M., Hofton, M., Tang, H., Marselis, S., Pinto, N., Hancock, S., Hawkins, B., Duncanson, L., Blair, B., Hansen, C., Lou, Y., Dubayah, R., Hensley, S., Silva, C.A., Poulsen, J,. R., Labrière, N., Barbier, N., Jeffery, K., Kenfack, D., Herve M., Bissengou, P., Alfonso A., Moussavou, G., White, L., Lewis, S., Hibbard, K.The NASA AfriSAR Campaign: Airborne SAR and Lidar Measurements of Tropical Forest Structure and Biomass in Support of Future Space Missions. Remote Sensing of Environment. 2021,264, 112533. https://doi.org/10.1016/j.rse.2021.112533
  12. De Faria, B.L.; Marano, G.; Piponiot, C.; Silva, C.A.; Dantas, V.d.L.; Rattis, L.; Rech, A.R.; Collalti, A. Model-Based Estimation of Amazonian Forests Recovery Time after Drought and Fire Events. Forests 2021, 12, 8. https://doi.org/10.3390/f12010008
  13. Cardil, A.; de-Miguel, S., Silva, C.A; Reich, P. B., Calkin, D.; Brancalion, P. H. S. 9; et al. Recent deforestation drove the spike in Amazonian fires. Environ. Res. Lett. https://doi.org/10.1088/1748-9326/abcac7
  14. Costa, M., Silva, C. A.; Broadbent, E. N. et al. 2021. Beyond trees: mapping total aboveground biomass density in the Brazilian savanna using high-density UAV-lidar data. Forest Ecology and Management. v. 491: https://doi.org/10.1016/j.foreco.2021.119155

2020

  1. Silva Junior, C., Aragão, L., Anderson, L., Fonseca, M., Shimabukuro, Y., Krug, T., Vancutsem, C., Frederic, A., Beuchle, R., Saatchi, S., Silva, I., Silva, C.A., Maeda, E., Longo, M., Persistent collapse of biomass in Amazonian forest edges following deforestation leads to unaccounted carbon losses. Science Advances. 2020. Vol. 6, no. 40, doi: 10.1126/sciadv.aaz8360
  2. Valbuen, R., O’Connor, B., Zellweger, F., Simonson, W., Coops, N.C., Morsdorf, F., Vihervaara P., Maltamo, M., Danks, F., Chirici, G., Silva, C. A., Almeida, D., Coomes DA. A framework standardizing disparate sources of 3D remote sensing data which enables monitoring ecosystem morphological traits as Essential Biodiversity Variables. Trends in Ecology & Evolution. 2019.
  3. Duncanson, L., Neuenschwander, A., Hancock, S., Thomas, N., Fatoyinbo, T., Simard, M., Luthcke, S., Silva, C. A., Armston, J., Hofton, M., Dubayah, R. Understanding Biomass Errors from Simulated GEDI, ICESat-2 and NISAR Data Across Environmental Gradients in Sonoma County, California. Remote Sensing of Environment. 2020.
  4. Almeida, D. A.; Almeyda Z. A.; Broadbent, E. N.; Wendt, A. L.; Foster, P. ; Wilkinson, B. E. ; Salk, C.; Papa, D.; Stark, S.; Valbuena, R.; Gorgens, E.; Silva, C.; Brancalion, P.; Fagan, M.; Meli, P.; Chazdon, R. Detecting successional changes in tropical forest structure using GatorEye drone-borne lidar. Biotropica, v. 1, p. 1, 2020. https://doi.org/10.1111/btp.12814
  5. Qu, Y.; Shaker, A.; Korhonen, L.; Silva, C.A.; Jia, K.; Tian, L.; Song, J. Direct Estimation of Forest Leaf Area Index based on Spectrally Corrected Airborne LiDAR Pulse Penetration Ratio. Remote Sens. 2020, 12, 217. https://doi.org/10.3390/rs12020217
  6. Saluma, R.B, Filho, P W., Simard, M., Silva, C.A et al. Improving Mangrove Aboveground Biomass Estimates Using lidar. Estuarine, Coastal and Shelf Science, 236, 2020. https://doi.org/10.1016/j.ecss.2020.106585.
  7. Dalla Corte, A.P.; Rex, F.E.; Almeida, D.R.A.d.; Sanquetta, C.R.; Silva, C.A.; Moura, M.M.; Wilkinson, B.; Zambrano, A.M.A.; Cunha Neto, E.M.d.; Veras, H.F.P.; Moraes, A.d.; Klauberg, C.; Mohan, M.; Cardil, A.; Broadbent, E.N. Measuring Individual Tree Diameter and Height Using GatorEye High-Density UAV-Lidar in an Integrated Crop-Livestock-Forest System. Remote Sens. 2020, 12, 863. https://doi.org/10.3390/rs12050863 .
  8. Silva, V.S.d.; Silva, C.A.; Mohan, M.; Cardil, A.; Rex, F.E.; Loureiro, G.H.; Almeida, D.R.A.d.; Broadbent, E.N.; Gorgens, E.B.; Dalla Corte, A.P.; Silva, E.A.; Valbuena, R.; Klauberg, C. Combined Impact of Sample Size and Modeling Approaches for Predicting Stem Volume in Eucalyptus spp. Forest Plantations Using Field and LiDAR Data. Remote Sens. 2020, 12, 1438. https://doi.org/10.3390/rs12091438
  9. Nicoletti, Marcos Felipe ; Carvalho, Samuel De Pádua Chaves E ; Machado, Sebastião Do Amaral; Costa, Valdeci José ; Silva, Carlos Alberto ; Topanotti, Larissa Regina . Bivariate and generalized models for taper stem representation and assortments production of loblolly pine (Pinus taeda L.). Journal of Environmental Management, v. 270, p. 110865, 2020.
  10. D’Oliveira, M V. N. ; Broadbent, E. N. ; Oliveira, Luis C. ; Silva, C., et al.. 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. Remote Sensing, v. 12, p. 1754, 2020.
  11. Marshak, C. ; Simard, M,; Duncanson, L.; Silva, C. et al. Regional Tropical Aboveground Biomass Mapping with L-Band Repeat-Pass Interferometric Radar, Sparse Lidar, and Multiscale Superpixels. Remote Sensing, v. 12, p. 2048, 2020.
  12. Rex, F., Silva, C.A., Corte, A.P., Klauberg, C., Mohan, M., Cardil, A., Hudak, A. Comparison of Statistical Modelling Approaches for Estimating Tropical Forest Aboveground Biomass Stock and Reporting Their Changes in Low-Intensity Logging Areas Using Multi-Temporal LiDAR Data. Remote Sensing. 2020
  13. Leite, R.V.; Silva, C.A.; Mohan, M.; Cardil, A.; Almeida, D.R.A.; Carvalho, S.P.C.; Jaafar, W.S.W.M.; Guerra-Hernández, J.; Weiskittel, A.; Hudak, A.T.; Broadbent, E.N.; Prata, G.; Valbuena, R.; Leite, H.G.; Taquetti, M.F.; Soares, A.A.V.; Scolforo, H.F.; Amaral, C.H.; Dalla Corte, A.P.; Klauberg, C. Individual Tree Attribute Estimation and Uniformity Assessment in Fast-Growing Eucalyptus spp. Forest Plantations Using Lidar and Linear Mixed-Effects Models. Remote Sens. 2020, 12, 3599.
  14. Silva Junior, C. H. L.; Heinrich, V. H. A. ; Freire, A. T. G.; Broggio, I. S. ; Rosan, T. M.; Doblas, J.; Anderson, L. O. ; Rousseau, G. X.; Shimabukuro, Y. E. ; Silva, C. A. ; House, J. I. ; Aragão, L. E. O. C. Benchmark maps of 33 years of secondary forest age for Brazil. Scientific Data, v. 7, p. 1, 2020. https://doi.org/10.6084/m9.figshare.12622025
  15. Brancalion, P. H.S. ; Broadbent, E. N.; De-Miguel, S.; Cardil, A.; Rosa, M. R.; Almeida, C. T. ; Almeida, D. R.A. ; Chakravarty, S.; Zhou, M.; Gamarra, J. G.P. ; Liang, J.; Crouzeilles, R.; Hérault, B.; Aragão, L. E.O.C. ; Silva, C. A.; Almeyda-Zambrano, A. M. Emerging threats linking tropical deforestation and the COVID-19 pandemic. Perspectives in Ecology and Conservation, v. 1, p. 1, 2020.
  16. Rex, F. E. ; Corte, A. P. D. ; Silva, C. A. ; Machado, S. A. ; Sanquetta, C. R. . Dynamics of Above-Ground Biomass in the Brazilian Amazon Using LiDAR Data. Anuário Do Instituto De Geociências (Ufrj. Impresso), V. 43, P. 228-238, 2020.
  17. Corte, A. P. D.; Souza, D. V.; Rex, F. Ed.; Sanquetta, C. R. ; Mohan, M.; Silva, C. A.; Zambrano, A. M. A.; Prata, G.; Almeida, D. R.; Trautenmüller, J. W.; Klauberg, C.; De Moraes, A.; Sanquetta, M. N. ; Wilkinson, B.; Broadbent, E. N.. Forest inventory with high-density UAV-Lidar: Machine learning approaches for predicting individual tree attributes. Computers and Electronics In Agriculture, v. 179, p. 105815, 2020.
  18. Cardil, A.; Rodrigues, M.; Ramirez, J.; De-Miguel, S.; Silva, C. A.; Mariani, M.; Ascoli, D.. Coupled effects of climate teleconnections on drought, Santa Ana winds and wildfires in southern California. Science Of The Total Environment, v. 1, p. 142788, 2020.
  19. Cardil, A.; de-Miguel, S., Silva, C.A; Reich, P. B., Calkin, D.; Brancalion, P. H. S. 9; et al. Recent deforestation drove the spike in Amazonian fires. Environ. Res. Lett in press https://doi.org/10.1088/1748-9326/abcac7
  20. Wan Mohd Jaafar, Wan S.; Said, Nor F.S.; Abdul Maulud, Khairul N.; Uning, Royston; Latif, Mohd T.; Muhmad Kamarulzaman, Aisyah M.; Mohan, Midhun; Pradhan, Biswajeet; Saad, Siti N.M.; Broadbent, Eben N.; Cardil, Adrián; Silva, Carlos A.; Takriff, Mohd S. 2020. "Carbon Emissions from Oil Palm Induced Forest and Peatland Conversion in Sabah and Sarawak, Malaysia" Forests 11, no. 12: 1285. https://doi.org/10.3390/f11121285
  21. Prata, Gabriel A.; Broadbent, Eben N.; de Almeida, Danilo R.A.; St. Peter, Joseph; Drake, Jason; Medley, Paul; Corte, Ana P.D.; Vogel, Jason; Sharma, Ajay; Silva, Carlos A.; Zambrano, Angelica M.A.; Valbuena, Ruben; Wilkinson, Ben. 2020. "Single-Pass UAV-Borne GatorEye LiDAR Sampling as a Rapid Assessment Method for Surveying Forest Structure" Remote Sens. 12, no. 24: 4111. https://doi.org/10.3390/rs12244111

2019

  1. Gasparini, K. A., Silva Junior, C, Shimabukuro, Y., Silva, C. A., et al. Determining a Threshold to Delimit the Amazonian 3 Forests from Tree Canopy Cover 2000 Data. Sensors. 2019
  2. Silva, C.A., Pinagé,E., Mohan, M., Valbuena, R., Almeida, D., Broadbent,E., Jaafar, W., Papa, D., Cardil, A., Klauberg, C. ForestGapR: An R Package for Airborne Laser Scanning-derived Tropical Forest Gaps Analysis. Methods in Ecology and Evolution. 2019.
  3. Klauberg, C., Hudak, A., Silva, C.A., Lewis, S., Robichaud, P., Jain, T. Characterizing fire effects on conifers at tree level from airborne laser scanning and high-resolution, multispectral satellite data. Ecological Modeling. 2019.
  4. Eitel, J. ; Maguire, A. ; Boelman, N. ; Vierling, L. A. ; Griffin, K. ; Jensen, J. ; Magney, T. ; Mahoney, P. ; Meddens, A. ; Silva, C. A. ; Sonnentag, O. . Proximal remote sensing of tree physiology at northern treeline: Do late-season changes in the photochemical reflectance index (PRI) respond to climate or photoperiod?. Remote Sensing of Environment, v. 221, p. 340-350, 2019.
  5. Ramirez, J., Monedero, S., Silva C.A., Cardil, A. Stochastic decision trigger modelling to assess the probability of wildland fire impact. Science of the Total Environment. 2019.
  6. Cardil, A., Vega-García, C., Ascoli D., Molina-Terrén DM., Silva C.A., Rodrigues, M. How does drought impact burned area in Mediterranean vegetation communities? Science of the Total Environment. 2019.
  7. Mohan, M., Mendonça, B., Silva, C.A., Klauberg, C., Ribeiro, R., Araújo, E., Monte, M., Cardil, Optimizing Individual Tree Detection Accuracy and Measuring Forest Uniformity in Coconut (Cocos nucifera L.) Plantations using Airborne Laser Scanning. Ecological Modeling. 2019.
  8. Almeida, D., Stark, S. C., Schietti, J. Camargo, J. L. C., Amazonas, N. T., Gorgens, E. B., Rosa, D. M.Smith, M. N., Valbuena, R, Saleska, S., Andrade, A., Mesquita, R., Laurance, S. G., Laurance, W. F. h, Lovejoy, T. E d, Broadbent, E., Shimabukuro, Y. E., Parker, G. G., Lefsky, M., Silva, C. A., Brancalion, P. H. Persistent effects of fragmentation on tropical rainforest canopy structure after years of isolation. Ecological Applications. 2019.
  9. Valbuena, R. Hernando, A., Manzaner, J., Görgen, E., Almeida, D., Silva, C.A., García-Abri, A. Evaluating observed versus predicted forest biomass: R-squared, index of agreement or maximal information coefficient?". European Journal of Remote Sensing. 2019.
  10. Almeida, D., Zambrano, A., Wilkinson, B., Silva, C. A., Papa, D., Broadbent, E., Gorgens, E., Ferreira, M., Meli, P., Brancalion, P., Chazdon, R., Valbuena, R., Stark, S. Monitoring the structure of forest restoration plantations with a drone-lidar system. International Journal of Applied Earth Observations and Geoinformation. 2019.
  11. Burattoa, D.A ; Juniora, R ; Timofeiczyk, R. ; Silva, J.C.G.L. ; Fregaa, J.R. ; Wiechetecke, M.S.S.A.; Silva, C. A. Use of Artificial Neural Networks and Arima to Forecasting Consumption Sawnwood of Pinus sp. in Brazil. International Forestry Review, v. 21, p. 51-61, 2019
  12. Cardil, A.; Otsu, K. ; Pla, M. ; Silva, C. A. ; Brotons, L. Quantifying pine processionary moth defoliation in a pine-oak mixed forest using unmanned aerial systems and multispectral imagery. PlosOne, 2019
  13. Cardil, A.; Ramirez, J. ; Monedero, S. ; Silva, C. A. Assessing and reinitializing wildland fire simulations through satellite active fire data. Journal of Environmental Management, v. 231, p. 996-1003, 2019.
  14. Molina-Terren, D. M. ; Xanthopoulos, G. ; Diakakis, M. ; Ribeiro, L. ; Caballero, D. ; Delogu, G. M. ; Viegas, D. X. ; Silva, C. A. ; Cardil, A. . Analysis of forest fire fatalities in Southern Europe: Spain, Portugal, Greece and Sardinia (Italy). International Journal of Wildland Fire, v. 1, p. 1, 2019.
  15. Almeida, D. R. A. ; Stark, S. C. ; Shao, G. ; Schietti, J. ; Nelson, B. W. ; Silva, C.A ; Gorgens, E. ; Valbuena, R. ; Papa, D. A. ; Brancalion, P. H. S. . Optimizing the Remote Detection of Tropical Rainforest Structure with Airborne Lidar: Leaf Area Profile Sensitivity to Pulse Density and Spatial Sampling. Remote Sensing, v. 11, p. 1, 2019.
  16. Cardil, A.; Monedero, S. ; Silva, C. A. ; Ramirez, J. Adjusting the rate of spread of fire simulations in real-time. Ecological Modelling, v. 395, p. 39-44, 2019.
  17. Almeida, D. R. A. ; Stark, S. C. ; Chazdon, R. ; Nelson, B. W. ; Cesar, R. ; Meli, P. ; Gorgens, E. ; Duarte, M. M. ; Valbuena, R. ; Moreno, V. ; Mendes, A. F. ; Amazonas, N. T. ; Goncalves, N. ; Silva, C. A. ; Schietti, J. ; Brancalion, P. H. S. The effectiveness of lidar remote sensing for monitoring forest cover attributes and landscape restoration. Forest Ecology and Management, v. 438, p. 34-43, 2019.
  18. Rex, F. ; Corte, Ana Paula Dalla ; Sanquetta, C. R. ; Machado, S. A. ; Silva, C. A. . Estimativa de Biomassa Aérea de Araucaria angustifolia (Bertol.) Kuntze POR DADOS LiDAR. Floram, 2019.
  19. Guerra-Hernández, J., Cozensa, D., Cardil, A., Silva, C.A., Botequim, B., Soares, P., Silva, M. González-Ferreiro, E. Díaz-Varela, R. A. Predicting Growing Stock Volume of Eucalyptus plantations using 3-D point clouds derived from UAV imagery and ALS data. Forests. 2019.
  20. Papa, D., Almeida, D., Estraviz, L.C., Valbuena. R., Silva, C.A. et al. Characterizing and Stratifying Tropical Forests to Reduce Field Sample Effort From Lidar Data. Forest Ecology and Management. 2019.
  21. Almeida. D., Stark, S., Valbuena, R., Broadbent, E., Silva, T., Resende, A., Ferreira, M., Cardil, A., Silva, C.A., Amazonas, N., Zambranoi, A., Brancalion. P. A new era in forest restoration monitoring. Restoration Ecology. 2019

2018

  1. Silva, C. A.; Saatchi, S. ; Alonso, M. G. ; Labriere, N. ; Klauberg, C. ; Ferraz, A. ; Meyer, V. ; Jeffery, K. J. ; Abernethy, K. ; White, L. ; Zhao, K. ; Lewis, S. L. ; Hudak, A. T. . Comparison of Small- and Large-Footprint Lidar Characterization of Tropical Forest Aboveground Structure and Biomass: A Case Study From Central Gabon. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, p. 1-15, 2018.
  2. Klauberg, C. ; Hudak, A. ; Bright, B. C. ; Boschetti, L. ; Dickinson, M. ; Kremens, R. ; Silva, C. A. . Use of ordinary kriging and Gaussian conditional simulation to interpolate airborne fire radiative energy density estimates. International Journal of Wildland Fire, v. 27, p. 228, 2018.
  3. Hentz, A. M. K. ; Silva, C. A. ; Corte, A. P. D. ; Netto, S. P. ; Strager, M. P. ; Klauberg, C. . Estimating forest uniformity in Eucalyptus spp. and Pinus taeda L. stands using field measurements and structure from motion point clouds generated from unmanned aerial vehicle (UAV) data collection. Forest Systems, v. 27, p. e005, 2018.
  4. Qu, Y. ; Shaker, A. ; Silva, C. A. ; Klauberg, C. ; Pinage, E. R. . Remote Sensing of Leaf Area Index from LiDAR Height Percentile Metrics and Comparison with MODIS Product in a Selectively Logged Tropical Forest Area in Eastern Amazonia. Remote Sensing, v. 10, p. 970, 2018.
  5. Ferraz, A. ; Saatchi, S. ; Xu, L. ; Hagen, S. ; Chave, J. ; Yu, Y. ; Meyer, V. ; Alonso, M. G. ; Silva, C.A ; Roswintiart, O. ; Samboko, A. ; Sist, P. ; Walker, S. ; Pearson, T. ; Wijaya, A. ; Sullivan, F. ; Rutishauser, E. ; Hoekman, D. ; Ganguly, S. . Carbon storage potential in degraded forests of Kalimantan, Indonesia. Environmental Research Letters, v. 1, p. 1, 2018.
  6. Silva, C.A; Klauberg, C. ; Hudak, Andrew T. ; Vierling, L. A. ; Liesenberg, V. ; Bernett, L. G. ; Scheraiber, C. ; Schoeninger, E. . Estimating Stand Height and Tree Density in Pinus taeda plantations using in-situ data, airborne LiDAR and k-Nearest Neighbor Imputation. Anais Da Academia Brasileira de Ciências, v. 90, p. 295-309, 2018.
  7. Huo, L. ; Silva, C. A. ; Klauberg, C. ; Mohan, M. ; Zhao, L. ; Tang, P. ; Hudak, A. T. . Supervised spatial classification of multispectral LiDAR data in urban areas. PLOS One, v. 13, p. e0206185, 2018.
  8. Jaafar, W. S. W. M. ; Woodhouse, I. H. ; Silva, C. A. ; Omar, H. ; Maulud, K. N. A. ; Hudak, Andrew T. ; Klauberg, C. ; Cardil, A. ; Mohan, M. . Improving Individual Tree Crown Delineation and Attributes Estimation of Tropical Forests Using Airborne LiDAR Data. Forests, v. 9, p. 759, 2018.
  9. Silva, C. A.; Klauberg, C. ; Hentz, A. M. K. ; Corte, A. P. D. ; Ribeiro, U. ; Liesenberg, V. . Comparing the Performance of Ground Filtering Algorithms for Terrain Modeling in a Forest Environment Using Airborne LiDAR Data. Floram, v. 25, p. 2-10, 2018.

2017

  1. Ruza, M. S. ; Corte, A. P. D. ; Hentz, A. M. K. ; Sanquetta, C. R. ; Silva, C. A. ; Schoeninger, E. R. Inventário de Sobrevivência de povoamento de Eucalyptus com uso de Redes Neurais Artificiais em Fotografias obtidas por VANTs. Advances in Forestry Science, v. 4, p. 83-88, 2017.
  2. Alonso, M. G. ; Saatchi, S. ; Ferraz, A. ; Silva, C. A. ; Ustin, S. ; Koltunov, A. ; Balzter, H. . Impact of data model and point density on aboveground forest biomass estimation from airborne LiDAR. Carbon Balance and Management, v. 12, p. 4, 2017.
  3. Jaafar, W. S. W. M. ; Woodhouse, I. H. ; Silva, C. A. ; Omar, H. . Modelling individual tree aboveground biomass using discrete return LiDAR in lowland dipterocarp forest of Malaysia. Journal of Tropical Forest Science, v. 29, p. 465-484, 2017.
  4. Silva, L. G. ; Silva, C. A. ; Klauberg, C. ; Mello, J. M. . Detecção de árvores individuais em área florestal mista de coníferas por meio de dados LiDAR aerotransportando. Advances in Forestry Science, v. 4, p. 1, 2017.
  5. Silva, C. A.; Carine Klauberg ; Hudak, Andrew T. ; Vierling, Lee A. ; Fennema, S. ; Corte, A. P. D. . Modeling and mapping basal area of Pinus taeda L. plantation using airborne LiDAR data. Anais da Academia Brasileira de Ciências, v. 89, p. 1895-1905, 2017.
  6. Madi, J. P. S. ; Vendruscolo, D. G. S. ; Silva, C. A. ; Lima, M. P. ; Carvalho, S. P. C. . Univariate models to represent the diametric distribution of thinned stand of Tectona grandis Linn.F. Advances in Forestry Science, v. 4, p. 119-123, 2017.
  7. Silva, C. A.; Klauberg, C. ; Hudak, Andrew T. ; Vierling, L. A. ; Jaafar, W. S. W. M. ; Mohan, M. ; Alonso, M. G. ; Ferraz, A. ; Saatchi, S. ; Cardil, A. . Predicting Stem Total and Assortment Volumes in an Industrial Pinus taeda L. Forest Plantation Using Airborne Laser Scanning Data and Random Forest. Forests, v. 8, p. 254-271, 2017.
  8. Klauberg, C. ; Vidal. E. J ; Silva, C. A. ; Hudak, Andrew T. ; Oliveira, M. ; Higuchi, P. . Short-Term Effects of Reduced-Impact Logging on Copaifera spp. (Fabaceae) Regeneration in Eastern Amazon. Forests, v. 8, p. 257-270, 2017.
  9. Mohan, M. ; Silva, C. A. ; Klauberg, C. ; Jat, P. ; Catts, G. ; Cardil, A. ; Hudak, A. . Individual Tree Detection from Unmanned Aerial Vehicle (UAV) Derived Canopy Height Model in an Open Canopy Mixed Conifer Forest. Forests, v. 8, p. 340-357, 2017.
  10. Silva, C. A.; Hudak, Andrew T. ; Vierling, L. A. ; Klauberg, C. ; Alonso, M. G. ; Ferraz, A. ; Keller, M. ; Eitel, J. ; Saatchi, S. . Impacts of Airborne Lidar Pulse Density on Estimating Biomass Stocks and Changes in a Selectively Logged Tropical Forest. Remote Sensing, v. 9, p. 1068-1087, 2017.
  11. Silva, C.A; Klauberg, C; Hentz, Â; Carvalho, S; Corte, A. Predição da biomassa aérea em plantações de Pinus taeda L. por meio de dados LiDAR aerotransportado. Scientia Forestalis, v. 45, p. 527-539, 2017.
  12. Silva, C. A.; Klauberg, Carine ; Mendonça, Bruno Araujo Furtado De ; Carvalho, Samuel Padua Chaves E . Efeito da densidade de pontos LiDAR na predição da altura em plantações de Pinus taeda L.. Scientia Forestalis, v. 45, p. 481-492, 2017.
  13. Silva, C. A.; Hudak, A. ; Klauberg, C. ; Vierling, L. A. ; Gonzalez-Benecke, C. A. ; Carvalho, S. P. C. ; Rodriguez, L. C. E. ; Cardil, A. . Combined effect of pulse density and grid cell size on predicting and mapping aboveground carbon in fast-growing Eucalyptus forest plantation using airborne LiDAR data. Carbon Balance and Management, v. 12, p. 2-16, 2017.

2016

  1. Silva, C. A.; Klauberg, Carine ; Hudak, Andrew T. ; Vierling, Lee A. ; Liesenberg, Veraldo ; Carvalho, Samuel P. C. E ; Rodriguez, Luiz C. E. . A principal component approach for predicting the stem volume in Eucalyptus plantations in Brazil using airborne LiDAR data. Forestry, v. 89, p. cpw016, 2016.
  2. Silva, C. A.; Hudak, A. ; Vierling, L. A. ; Loudermilk, L. ; O'brien, J. J. ; Hiers, J. ; Jack, S. B. ; Gonzalez-Benecke, C. A. ; Lee, H. ; Falkowski, M. J. ; Khosravipour, A. . Imputation of Individual Longleaf Pine ( Mill.) Tree Attributes from Field and LiDAR Data. Canadian Journal of Remote Sensing, p. 00-15, 2016.
  3. Klauberg, C. ; Vidal. E. J ; Silva, C.A ; Bentes, M. M. ; Hudak, A. . Sampling methods for titica vine (Heteropsis spp.) inventory in a tropical forest. Annals of Forest Science, v. 4, p. 1-8, 2016.
  4. Klauberg, C. ; Silva, C.A ; Lima, M. P. ; Carvalho, S. P. C. . Panorama mundial sobre publicações técnico-científicas abordando Produtos Florestais Não Madeireiros nas duas últimas décadas. Advances in Forestry Science, v. 3, p. 29-37, 2016.
  5. Hudak, A. ; Bright, B. C. ; Pokswinski, S. M. ; Loudermilk, E. L. ; O?Brien, J. J. ; Hornsby, B. S. ; Klauberg, C. ; Silva, C.A . Mapping Forest Structure and Composition from Low-Density LiDAR for Informed Forest, Fuel, and Fire Management at Eglin Air Force Base, Florida, USA. Canadian Journal of Remote Sensing, v. 42, p. 411-427, 2016.
  6. Ferraz, A. ; Saatch, S. ; Mallet, C. ; Jacquemoud, S. ; Goncalves, G. ; Silva, C.A ; Soares, P. ; Tome, M. ; Pereira, L. . Airborne Lidar Estimation of Aboveground Forest Biomass in the Absence of Field Inventory. Remote Sensing, v. 8, p. 653, 2016.

2015

  1. Silva, C.A; Klauberg, C. ; Carvalho, S. P. C. ; Piccolo, M. C. ; Rodriguez, L. C. E. . Estoque de carbono na biomassa área florestal em plantações comerciais de Eucalyptus spp. Scientia Forestalis, v. 43, p. 301-309, 2015.
  2. Gorgens, E. ; Rodriguez, L. C. E. ; Silva, A. G. P. ; Silva, C.A . Identificação De Árvores Individuais A Partir De Levantamentos Laser Aerotransportado Por Meio De Janela Inversa. Cerne, v. 21, p. 91-96, 2015.
  3. Carvalho, S. P. C. ; Rodriguez, L.C.E. ; Silva, L.D. ; Carvalho, L.M.T. ; Calegario, N. ; Lima, M. P. ; Silva, C.A ; Mendonca, A. R. ; Nicoletti, M. F. . Predição do volume de árvores integrando Lidar e Geoestatística. Scientia Forestalis, v. 43, p. 627-637, 2015.

2014

  1. Silva, C. A.; Klauberg, C. ; Carvalho, S. P. C. ; Hudak, A. ; Rodriguez, L. C. E. . Mapping aboveground carbon stocks using LiDAR data in Eucalyptus spp. plantations in the state of São Paulo, Brazil. Scientia Forestalis, v. 42, p. 591-604, 2014.
  2. Carvalho, S. P. C. ; Rodriguez, L. C. E. ; Calegario, N. ; Savian, T. V. ; Lima, M. P. ; Silva, C. A. ; Mendonca, A. R. ; Nicoletti, M. F. . Modelagem não linear mista para descrever o afilamento de árvores clonais de Eucalyptus sp. Scientia Forestalis, v. 42, p. 605, 2014.
Forest structure visualized with lidar
Pine canopy viewed from below
Preparing a drone for forest research
Field research in a pine forest
Forest research fieldwork
Forest monitoring and remote sensing
Forest landscape
Forest science in the field
Forest research landscape