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Antonio Ferraz

Photo of Antonio Ferraz

Address:

4800 Oak Grove Drive

Pasadena, CA 91109

Curriculum Vitae:

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Member of:

Carbon Cycle And Ecosystems

Biography

Dr. António Ferraz has been developing tools to derive tree level forest inventory from airborne lidar and, to map tropical forest degradation and carbon storage by integrating satellite, airborne and in-situ measurements. Dr. Ferraz is a PI for the NASA GEDI Science Team where he leads a project that models the forest structural diversity-carbon relationship from GEDI measurements to support policy-making on the conservation and restoration of forests. He is a Co-I for the NASA Biodiversity and Ecological Forecasting team focusing on integrating lidar and spectroscopic mapping (GEDI, DESIS and ECOSTRESS) with ICARUS animal movement datasets to understand seed dispersers movements in the Congo rainforest.

Education

  • Ph.D., Geophysics, Paris Institute of Earth Physics, France (2012)
  • M.Sc., Geospatial Engineering, University of Coimbra, Portugal (2007)

Professional Experience

  • Jet Propulsion Laboratory, Pasadena, California
    • Affiliated Researcher Scientist (2017-present)
    • Caltech Postdoctoral Researcher (2016-2017)
    • NASA Postdoctoral Program Fellow (2014-2016)
  • Institute of Environment and Sustainability, University of California, Los Angeles
    • Associate Project Scientist (2018-present)
    • UCLA Postdoctoral scholar (2017-2018)
  • French Mapping Agency, Paris, France
    • Postdoctoral research fellow (2012-2014)

Selected Awards

  • NASA Postdoctoral Fellowship (2014)
  • PhD. Fellowship, Portuguese Foundation for Science and Technology (2007)
  • M.Sc. Fellowship Leonardo da Vinci, European Union (2007)
  • BPI award, top-ranking graduate in Geospatial Engineering (2007)
  • CGD award, Best Honors student in Geospatial Engineering (2006)

Selected Publications

  1. Schneider, F. D., Dean, M., Ordway, E. M., Libalah, M. B., & Ferraz, A. (2026) Mapping the structural diversity of Central and Western US forests usign GEDI. Remote Sensing of Environement, 334, 115215.
  2. Oliver, R. and 62 co-authors (2026) Seven reasons why we need movment-based indicators in global policy. Nature Reviews Biodiversity.
  3. Han, T., Ferraz, A., Fang, D., Zheng, T., Ankori-Karlinsky, R., Arellano, G., Morton, D., Zimmerman, J. K., Keller, M., Uriarte, M., & Xu, X. (2026). Taller trees experienced less crown dammage during a severe hurricane in a tropical forest. Global Change Biology. 32, no. 1: e70709.
  4. Braghiere, R. K., Wang, Y., Liu, K., Chadwick, K. D., Brodrick, P. B., Shiklomanov, A. N., Schneider, F. D., Ferraz, A., Zheng, T., Queally, N., Townsend, P. A., Schimel, D., Frankenberg, C. (2026) Shifting from Plant Functional Types to Traits: Enhancing Biodiversity Representation in Earth System Models. Ecosphere
  5. Turner, A. A., Clark, M. L., Salas, L., Seymour, C., Snyder, R. L., Lee, A. T. K., Ferraz, A., Schneider, F., Measey, J., Huisamen, J., Cloete, D., Hofmeyr, S. D., Hagen, C., Leland, D. F., Schackwitz, W., Adegbola, F., Hahndiek, E., Joseph, G. S., Van Rooi, J., Fuchs, M., Thomas, S., Madlala, S., Spiby, J., & Taljaard, P. (2025). BioSoundsSCape : A bioacoustic dataset fro the Fynbos Biome. Scientific Data, 12, 1432.
  6. Longo, M., Keller, M., Kueppers, L. M., Bowman, K., Csillik, O., Ferraz, A., Moorcroft, P. R., Ometto, J. P., Soares-Filho, B. S., Xu, X., de Assis, M. L. F., Görgens, E. B., Larson, E. J. L., Needham, J. F., Ordway, E. M., Pereira, F. R. S., Pinagé, E. R., Sato, L., Xu, L., & Saatchi, S. (2025). Degradation and Deforestation Increase the Sensitivity of the Amazon Forest to Climate Extremes. Environmental Research Letters, 20 054024.
  7. Antoine T.S.A., Russo N.J., Bonaventure S., Deblauwe V., Nshom, D.L., Barbier, N., Ferraz A., Saatchi, S., Wikelski, M., Ordway, E.M., Smith, T. B. (in press). Habitat Selection and Seed Dispersal by the Great Blue Turaco (Corythaeola cristata) in the Rainforests of southern Cameroon. Biotropica. 58, no. 1: e70153
  8. Nicholas J. Russo, N., Takuo, J.M., Tegebong, V., LeBreton, M., Dean, M., Ferraz, A., Barbier, N., Wikelski, M., Ordway, E.M., Saatchi, S., Smith T.B. (2025). Spaceborne LiDAR revels hammer-headed bat preference for intermediate canopy height and diverse strcucture in a Central Africa rainforest. Movement Ecology 13, 30
  9. Teitelbaum C. S., Ferraz, A., De la Cruz, S.E.W., Gilmour, M., Brosnan, I., G. (2024). The potential of remote sensing for improved infectious disease ecology research and practice, Proceedings B 291. 2037.
  10. Russo, N., Nshom D., Ferraz A., Barbier, B., Wikelski M., Noonan M., Ordway, E., Saatchi, S., Smith, T., (2024) Three-dimensional vegetation structure drives patterns of seed dispersal by African hornbills, Journal of Animal Ecology, 93, 1935-1946.
  11. Csillik, O., Keller, M., Longo, M., Ferraz, A., Rangel Pinagé, E., Görgens, E., Pierre Ometto, J., Silgueiro, V., Saatchi, s. (2024). A large net carbon loss attributed to anthropogenic and natural disturbances in the Amazon Arc of Deforestation. Proceedings of the National Academy of Sciences (PNAS), 121 (3).
  12. Dehaudt, B., Bruce, T., Deblauwe, V., Ferraz, A., Gardner, B., Bibila, T., LeBreton, M., Mempong, G., Njabo, K., Nkengbeza, S., Ordway, E., Pavan, L., Russo, N., Smith, T., Luskin, M., (2024). Divergent seed dispersal outcomes: interactions between seed, disperser, and forest traits. Ecology. 105 (10)
  13. Duncanson , L. and 107 co-authors (2022). Development of Abovegroung Biomass Density Models for the Global Ecosystem Dynamics Investigation (GEDI) Lidar Misson. Remote Sensing of Enviroment, 270.
  14. Leitold, V., Morton, D., Martinuzzi, S., Paynter, I., Uriarte, M., Keller, M., Ferraz, A., Cook, B., Lawrence, C., González, G. (2021). Tracking the rates and mechanisms of canopy damage and recovery following Hurricane Maria using multitemporal lidar data. Ecosystems.
  15. Longo, M., Saatchi, S., Keller, K., Bowman, K., Ferraz, A., Moorcroft, P. R., Morton, D. C., Bonal, D., Brando, P., Derroire, G., dos-Santos, M., N, Meyer, V., Saleska, S., Vincent, G., Xu, X. (2020). Impacts of degradation on water, evergy, and carbon cycling of the Amazon tropical forests. Global Biogeochemical Cycles, 125.
  16. Schneider, F., Ferraz, A., Hancock, S., Duncanson, L., Dubayah, R., Pavlick, R., Schimel, D. (2020). Towards mapping the diveristy of canopy structure from space with GEDI. Environmental Research Letters, 15, 115006
  17. Ferraz, A., Saatchi, S., Longo, M., Clark, D. (2020). Tropical tree size-frequency distributions from airborne lidar. Ecological Applications 30(7):e02154.
  18. Clark, D. B., Ferraz, A., Clark, D. A., Kellner, J. R., Letcher, S. G., Saatchi, S. (2020). Diversity, distribution and dynamics of large tropical trees across an old-growth lowland tropical rain forest landscape. PloS ONE 14(11) e0224896.
  19. Schneider, F., Ferraz, A., Schimel, D. (2019). Watching Earth’s Interconnected Systems at Work. EOS, 100, https://doi.org/10.1029/2019EO136205.
  20. Schimel, D., Schneider, F., Bloom, A., Bowman, K., Cawse -Nicholson, K., Elder, C., Ferraz, A., Fisher, J., Hulley, G., Liu, J., Magney, T., Meyer, V., Miller, C., Parazoo. N., Pavlick, R., Podest, E., Saatchi, S., Stavros, N., Keller, M., Townsend, P., Zheng, T., JPL Carbon and Ecosystems Participants (2019). Flux towers in the sky: Global ecology from space. (Tansley Review) New Phytologist.
  21. Aubry-Kientz, M., Dutrieux, R., Ferraz, A., Saatchi, S., Hamraz, H., Williams, J., Coomes, D., Piboule, A., Vincent, G., (2019). A Comparative Assessment of the Performance of Individual Tree Crowns Delineation Algorithms from ALS Data in Tropical Forests. Remote Sens. 11.
  22. Meyer, V., Saatchi, S., Ferraz, A., Xu, A., Duque, A., Alonso, M., Chave, J. (2019). Forest degradation and biomass loss along the Chocó region of Colombia. Carbon balance and management, 14:2.
  23. Cawse-Nicholson, K., Fisher, J. B., Famiglietti, C. A., Braverman, A., Schwandner, F. M., Lewicki, J. L., Townsend, P. A., Schimel, D. S., Pavlick, R., Bormann, K. J., Ferraz, A., Kang, E. L., Ma, P., Bogue, R. R., Youmans, T., and Pieri, D. C. (2018). Ecosystem responses to elevated CO2 using airborne remote sensing at Mammoth Mountain, California, Biogeosciences, 15, 7403-7418.
  24. Ferraz, A., Saatchi, S., Xu, L., Hagen ,S., Chave, J., Yu. Y, Meyer, V., Garcia, M., Silva, C, Roswintiart, O., Samboko, A., Sist P., Walker, S., Pearson T. R.H., Wijaya, A., Sullivan, F.,Rutishauser, E., Hoekman D., Ganguly, S. (2018). Carbon Storage Potential in Degraded Forests of Kalimantan, Indonesia. Environmental Research Letters, 13 (9).
  25. Bastin, J-F. and 135 more (2018). Pan-tropical prediction of forest structure from the largest trees. Global Ecology and Biogeography.
  26. Labrière, N., Tao, S., Chave, J., Scipal, K., Toan, T, Abernethy, K., Alonso, A., Barbier, N., Bissiengou, P., Casal, T., Davies, S.J., Ferraz, A., Hérault, B., Jaouen, G., Jeffery, K. J., Kenfack, D., Korte, L., Lewis, S.L, Malhi, Y., Memiaghe, H.R., Poulsen, J.R., Réjou-Méchain, M., Villard, L., Vincent, G., White L. J. T., Sassan S. (2018), In situ reference datasets from the TropiSAR and AfriSAR campaigns in support of upcoming spaceborne biomass missions. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 99, 1-11.
  27. Meyer, V., Saatchi, S., Clark, D., Keller, M., Vincent, G., Ferraz, A., Espirito-Santo, F., d’Oliveira, M., Kaki, D., Chave, J. (2018). Canopy area of large trees explains aboveground biomass variations across neotropical forest landscapes. Biogeosciences, 15, 3377-3390.
  28. Silva, C.A., Saatchi, S.S., Garcia M., Labriere, N., Klauberg, C., Ferraz, A., Meyer, V, Jeffery, K.J., Abernethy, K., White, L., Zhao, K., Lewis, S., Hudak A.T. (2018) 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, 99, 1-15.
  29. Ferraz, A., Saatchi, S., Bormann, K.J., Painter, T.H. (2018). Fusion of NASA Airborne Snow Observatory (ASO) Lidar Time Series over Mountain Forest Landscapes. Remote Sensing, 10, 164.
  30. Xu, L., Saatchi, S., Shapiro, A., Meyer, V., Ferraz, A., Yang, Y., Bastin, J.-F., Banks, N., Boeckx, P., Verbeeck, H., Lewis, S.L., Muanza, E.T., Bongwele, E., Kayembe, F., Mbenza, D., Kalau, La., Mukendi, F., Ilunga, F., Ebuta, D. (2017). Spatial distribution of carbon stored in forests of the Democratic Republic of Congo. Sci. Rep. 1–12.
  31. Silva, C., Hudak, T., Vierling, L., Klauberg, C., Garcia, M., Ferraz, A., Keller, M., Eitel, J., Saatchi, S. (2017). Impacts of airborne lidar pulse density on estimating biomass stocks and changes in a selectively logged tropical forest. Remote Sensing, 9 (10), 1068.
  32. Silva, C., Klauberg, C., Hudak, A., Vierling, A., Jaafar, W., Mohan, M., Garcia, M., Ferraz, A., Saatchi, S., Cardil, A. (2017). Predicting Stem Total and Assortment Volumes in an Industrial Pinus taeda L. Forest Plantation using Airborne Laser Scanning Data and Random Forest. Forests (8) 254.
  33. Garcia, M., Saatchi, S., Ferraz, A., Silva, C., Ustin, S., Koltunov, A., Balzter, H. (2017). Impact of data model and point density on aboveground forest biomass estimation from airborne lidar. Carbon Balance and Management, 12 (4).
  34. Ferraz, A., Saatchi, S., Mallet, C., Jacquemoud, S., Gonçalves, G., Silva, C., Soares, P., Tomé, M., Pereira, L. (2016). Airborne Lidar Estimation of Aboveground Forest Biomass in the Absence of Field Inventory. Remote Sensing, 8(8), 653.
  35. Ferraz, A., Saatchi, S., Mallet, C., Meyer, V. (2016). Lidar detection of individual tree size in tropical forests. Remote Sensing of Environment, 183, 318-333.
  36. Ferraz, A., Mallet, C., Chehata, N. (2016). Détection à haute résolution spatiale de la desserte forestière en milieux montagneux. Revue Française de Photogrammétrie et de Télédétection, 211-212, pp. 103-117.
  37. Wang, Y., Hyyppä, J., Liang, X., Kaartinen, H., Yu, X., Lindberg, E., Holmgren, J., Qin, Y., Mallet, C., Ferraz, A., Torabzadeh, H., Morsdorf, F., Lingli, Z., Lui, J., Alho, P. (2016). International benchmarking of the individual tree detection methods for modeling 3D canopy structure for silviculture and forest ecology using airborne laser scanning. IEEE Transactions on Geoscience and Remote Sensing, 54 (9), 5011-5026.
  38. Ferraz, A., Mallet, C., Chehata, N. (2016). Large scale road detection in forested mountainous areas using airborne topographic lidar data. ISPRS Journal of Photogrammetry and Remote Sensing, 112, 23-36.
  39. Ferraz, A., Mallet, C., Jacquemoud, S., Gonçalves, G., Soares, P., Pereira, L., Tomé, M., Bretar, F. (2015). Canopy density model: a new ALS-derived product to generate multi-layer crown cover maps. IEEE Transactions on Geoscience and Remote Sensing, 53,6776-6790.
  40. Ferraz, A., Mallet, C., Jacquemoud, S., Gonçalves, G., Soares, P., Pereira, L., Tomé, M. (2014). Estimation de la biomass aerienne a partir de donnees lidar aeroportees. Revue Francaise de Photogrammetrie et teledetection, 205, 59-68.
  41. Smeeckaert, J., Mallet, C., David, N., Chehata, N., Ferraz, A. (2013). Large-scale classification of water areas using airborne topographic lidar data. Remote Sensing of Environment, 138, 134-148.
  42. Ferraz, A., Bretar, F., Jacquemoud, S., Gonçalves, G., Pereira, L., Tomé, M., Soares, P. (2012). 3-D mapping of a multi-layered Mediterranean forest using ALS data. Remote Sensing of Environment, 121, 210-223.