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Antonio Ferraz
Organization:
Jet Propulsion Laboratory
University of California, Los Angeles
Email:
Business Phone:
Work:
(818) 354-6075
Business Address:
Jet Propulsion Laboratory
4800 Oak Grove Drive M/S 233-300
Pasadena, CA 91109
United StatesFirst Author Publications:
- Ferraz, A., et al. (2020), Tropical tree size–frequency distributions from airborne lidar , Ecological Applications, e02154.
- Ferraz, A., et al. (2018), Fusion of NASA Airborne Snow Observatory (ASO) Lidar Time Series over Mountain Forest Landscapes, Remote Sensing, 10, 1-16, doi:10.3390/rs10020164.
- Ferraz, A., et al. (2018), Carbon Storage Potential in Degraded Forests of Kalimantan, Indonesia. Environmental Research Letters, 13, doi:10.1088/1748-9326/aad782.
- Ferraz, A., et al. (2016), Airborne Lidar Estimation of Aboveground Forest Biomass in the Absence of Field Inventory, Remote Sensing, 8, doi:https://doi.org/10.3390/rs8080653.
- Ferraz, A., et al. (2016), Lidar detection of individual tree size in tropical forests, Remote Sensing of Environment, 183, 318-333, doi:https://doi.org/10.1016/j.rse.2016.05.028.
Co-Authored Publications:
- Longo, M., et al. (2020), Impacts of Degradation on Water, Energy, and Carbon Cycling of the Amazon Tropical Forests, J. Geophys. Res., 22, doi://10.1002/essoar.10502287.1.
- Schneider, F., et al. (2020), Towards mapping the diversity of canopy structure from space with GEDI, Environmental Research Letters, doi:10.1088/1748-9326/ab9e99.
- Aubry-Kientz, M., et al. (2019), A Comparative Assessment of the Performance of Individual Tree Crowns Delineation Algorithms from ALS Data in Tropical Forests, Remote Sensing, 11, doi:10.3390/rs11091086.
- Clark, D. B., et al. (2019), Diversity, distribution and dynamics of large trees across an old-growth lowland tropical rain forest landscape, PLoS ONE, 14, e0224896, doi:10.1371/journal.pone.0224896.
- Meyer, V., et al. (2019), Forest degradation and biomass loss along the Chocó region of Colombia, Carbon Balance Manag., 14, 1-15, doi:10.1186/s13021-019-0117-9.
- Schimel, D., et al. (2019), Flux towers in the sky: global ecology from space, New Phytologist, 224, 570-584, doi:10.1111/nph.15934.
- Bastin, J. F., et al. (2018), Pan-tropical prediction of forest structure from the largest trees, Glob. Ecol. Biogeogr., 27, 1366-1383, doi:10.1111/geb.12803.
- Cawse-Nicholson, K., et al. (2018), Ecosystem responses to elevated CO2 using airborne remote sensing at Mammoth Mountain, California, Biogeosciences, 15, 7403-7418, doi:10.5194/bg-15-7403-2018.
- Labriere, N., et al. (2018), In Situ Reference Datasets from the TropiSAR and AfriSAR Campaigns in Support of Upcoming Spaceborne Biomass Missions IEEE J, Sel. Top. Appl. Earth Obs. Remote Sens., 11, 3617-27-3627, doi:10.1109/JSTARS.2018.2851606.
- Meyer, V., et al. (2018), Canopy area of large trees explains aboveground biomass variations across neotropical forest landscapes, Biogeosciences, 15, 3377-3390, doi:10.5194/bg-15-3377-2018.
- Silva, C. A., et al. (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, 11, 3512-3526, doi:10.1109/JSTARS.2018.2816962.
- Garcia, M., et al. (2017), Impact of data model and point density on aboveground forest biomass estimation from airborne LiDAR, Carbon Balance Management., 12.
- Silva, C., et al. (2017), Impacts of airborne lidar pulse density on estimating biomass stocks and changes in a selectively logged tropical forest, Remote Sensing, 9, 1068, doi:doi:10.3390/f8070254.
- Silva, C., et al. (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, doi:doi:10.3390/f8070254.
- Xu, L., et al. (2017), Spatial Distribution of Carbon Stored in Forests of the Democratic Republic of Congo, Scientific Reports, 7, 1-12, doi:DOI:10.1038/s41598-017-15050-z.