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Measuring and mapping Atlantic Forest canopy foliar traits with hyperspectral images and radiative transfer modeling

Grant number: 16/24977-1
Support type:Scholarships in Brazil - Post-Doctorate
Effective date (Start): June 01, 2017
Effective date (End): August 05, 2018
Field of knowledge:Physical Sciences and Mathematics - Geosciences
Cooperation agreement: Coordination of Improvement of Higher Education Personnel (CAPES)
Principal Investigator:Luiz Eduardo Oliveira e Cruz de Aragão
Grantee:Matheus Pinheiro Ferreira
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:15/50484-0 - Functional diversity of intact and regenerating Amazon, Atlantic, and Cerrado systems using hyperspectral imagery, AP.JP

Abstract

Conservation and management of the Atlantic Forest (AF), one of the most threatened biomes of Brazil, depends on high quality information about its forest resources. Most of our knowledge about the AF comes from field measurements performed at the plot level (d 1ha), but data encompassing broad spatial extents are needed to better understand the structure and function of this important biome. Remote sensing holds great promise to generalize and extrapolate insights emerged from plot-based studies to whole landscapes. Particularly hyperspectral remote sensing has proved to be a pivotal technology to study tropical forests. Hyperspectral sensors are capable of measuring reflected light from the forest canopy over a large number of narrow spectral bands, thus allowing the detection of tree species and estimation of canopy foliar traits related to ecosystem processes. These applications are challenging in tropical environments in which the canopy is spectrally and structurally very complex, but they can be improved by the use of Radiative Transfer Models (RTMs). To fill a major knowledge gap in the retrieval of canopy foliar traits and information regarding biodiversity of tropical forests over landscape scales, the objectives of this project are: (i) to simulate the spectral response of tropical forest canopies with a RTM; (ii) to validate with field data, estimates of canopy functional traits obtained by inversion of our simulations and (iii) to improve tree species discrimination and mapping methods based on hyperspectral remote sensing. This will be achieved by a unique dataset of hyperspectral images and field data of leaf functional traits that will be established by a recently approved NERC-FAPESP cooperation with the project BIO-RED (2015/50484-0). The innovative approach that will be developed in this project will allow chemical characterization of tropical forest canopies over large areas as well as long-term monitoring of tree species. The results will contribute to the currently debate on how tropical ecosystems respond to anthropogenic activities and global change. (AU)

Scientific publications (4)
(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)
WAGNER, FABIEN H.; SANCHEZ, ALBER; TARABALKA, YULIYA; LOTTE, RODOLFO G.; FERREIRA, MATHEUS P.; AIDAR, MARCOS P. M.; GLOOR, EMANUEL; PHILLIPS, OLIVER L.; ARAGAO, LUIZ E. O. C. Using the U-net convolutional network to map forest types and disturbance in the Atlantic rainforest with very high resolution images. REMOTE SENSING IN ECOLOGY AND CONSERVATION, v. 5, n. 4, p. 360-375, DEC 2019. Web of Science Citations: 17.
FERREIRA, MATHEUS PINHEIRO; WAGNER, FABIEN HUBERT; ARAGAO, LUIZ E. O. C.; SHIMABUKURO, YOSIO EDEMIR; DE SOUZA FILHO, CARLOS ROBERTO. Tree species classification in tropical forests using visible to shortwave infrared WorldView-3 images and texture analysis. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, v. 149, p. 119-131, MAR 2019. Web of Science Citations: 7.
WAGNER, FABIEN HUBERT; FERREIRA, MATHEUS PINHEIRO; SANCHEZ, ALBER; HIRYE, MAYUMI C. M.; ZORTEA, MACIEL; GLOOR, EMANUEL; PHILLIPS, OLIVER L.; DE SOUZA FILHO, CARLOS ROBERTO; SHIMABUKURO, YOSIO EDEMIR; ARAGAO, LUIZ E. O. C. Individual tree crown delineation in a highly diverse tropical forest using very high resolution satellite images. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, v. 145, n. B, p. 362-377, NOV 2018. Web of Science Citations: 9.
FERREIRA, MATHEUS PINHEIRO; FERET, JEAN-BAPTISTE; GRAU, ELOI; GASTELLU-ETCHEGORRY, JEAN-PHILIPPE; SHIMABUKURO, YOSIO EDEMIR; DE SOUZA FILHO, CARLOS ROBERTO. Retrieving structural and chemical properties of individual tree crowns in a highly diverse tropical forest with 3D radiative transfer modeling and imaging spectroscopy. REMOTE SENSING OF ENVIRONMENT, v. 211, p. 276-291, JUN 15 2018. Web of Science Citations: 6.

Please report errors in scientific publications list by writing to: cdi@fapesp.br.