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Using deep-learning convolutional network for estimating canopy traits from high-resolution imagery

Grant number: 19/09248-1
Support type:Scholarships in Brazil - Technical Training Program - Technical Training
Effective date (Start): August 01, 2019
Effective date (End): November 30, 2021
Field of knowledge:Physical Sciences and Mathematics - Geosciences
Cooperation agreement: NERC, UKRI ; Newton Fund - LATAM ; Newton Fund, with FAPESP as a partner institution in Brazil
Principal researcher:Luiz Eduardo Oliveira e Cruz de Aragão
Grantee:Annia Susin Streher
Home Institution: Instituto Nacional de Pesquisas Espaciais (INPE). Ministério da Ciência, Tecnologia, Inovações e Comunicações (Brasil). São José dos Campos , SP, Brazil
Associated research grant:18/15001-6 - ARBOLES: a trait-based understanding of LATAM forest biodiversity and resilience, AP.R

Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
DALAGNOL, RICARDO; WAGNER, FABIEN H.; GALVAO, LENIO S.; STREHER, ANNIA S.; PHILLIPS, OLIVER L.; GLOOR, EMANUEL; PUGH, THOMAS A. M.; OMETTO, JEAN P. H. B.; ARAGAO, LUIZ E. O. C. Large-scale variations in the dynamics of Amazon forest canopy gaps from airborne lidar data and opportunities for tree mortality estimates. SCIENTIFIC REPORTS, v. 11, n. 1 JAN 14 2021. Web of Science Citations: 0.
WAGNER, FABIEN H.; DALAGNOL, RICARDO; CASAPIA, XIMENA TAGLE; STREHER, ANNIA S.; PHILLIPS, OLIVER L.; GLOOR, EMANUEL; ARAGAO, LUIZ E. O. C. Regional Mapping and Spatial Distribution Analysis of Canopy Palms in an Amazon Forest Using Deep Learning and VHR Images. REMOTE SENSING, v. 12, n. 14 JUL 2020. Web of Science Citations: 0.

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