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

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)