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School of Forest, Fisheries, & Geomatics Sciences

School of Forest, Fisheries, & Geomatics Sciences

Carlos Alberto Silva

Assistant Professor of Quantitative Forest Science

Carlos Alberto Silva is an Assistant Professor of Quantitative Forest Science in the School of Forest, Fisheries, and Geomatics Sciences (FFGS) at the University of Florida (UF) where he directs the Forest Biometrics and Remote Sensing Lab (Silva Lab).

He is interested in understanding how forest ecosystems changes over time due to natural and anthropogenic disturbances and their impact on the carbon cycle. Previously, he has worked as a research scientist at the USDA Forest Service, University of Maryland, NASA Jet Propulsion Laboratory and NASA Goddard Space Flight Center.

His core research consists of developing statistical frameworks and cutting-edge open-source tools, such as rLiDAR, ForestGapR, and rGEDI, for remote sensing data processing and forest resources monitoring. He is particularly interested in using lidar (light detection and ranging) data, from airborne (ALS), terrestrial (TLS), and satellite platforms (e.g. GEDI, ICESat-2), combined with multi- and hyperspectral satellite data (e.g. Landsat 8 OLI and DESIS) and advanced statistical methods (e.g. machine learning) to address ecological questions related to forest ecosystem structure, function, and composition dynamics at a variety of spatial scales.

Courses Taught

IdentifierCourse Name
FOR3430C  Forest Mensuration 
FOR 4934/6934  Topics in Natural Resources 
  • Research Interests

    • Forest biometrics and quantitative ecology
    • Remote sensing of the environment
    • Lidar (light detection and ranging) systems (e.g. ALS, TLS, UAV-lidar, GEDI and ICESat-2)
    • Forest structure, function and composition monitoring from remote sensing technologies
    • Open-source software development (e.g. R packages)
    • Fire ecology and management
    • Terrestrial carbon cycle
    • Tropical forest ecosystems
    • Industrial forest plantations


342 Newins-Ziegler Hall, PO Box 110410
Gainesville, FL 32611-0410
(352) 294-6885

  • Education

    • PhD, Natural Resources, University of Idaho, 2018
    • MS, Forest Resources, University of São Paulo – “Luiz de Queiroz” College of Agriculture –ESALQ, 2013
    • BA, Forest Engineering, University of São Paulo – “Luiz de Queiroz” College of Agriculture –ESALQ, 2011

  • Publications

    • 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. v. 253.
    • 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
    • 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. Standardizing Ecosystem Morphological Traits from 3D Information Sources. Trends in Ecology & Evolution. 2020.
    • Duncanson, L., Neuenschwander, A., Hancock, S., Thomas, N., Fatoyinbo, T., Simard, M.,Luthcke, S., Silva, C. A., Armston, J., Hofton, M., Dubayah, R. Biomass estimation from simulated GEDI, ICESat-2 and NISAR across environmental gradients in Sonoma County, California. Remote Sensing of Environment. 2020.
    • 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.
    • 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.
    • 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.
    • 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.
    • 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.
    • 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.
    • 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.