Mapping Cerrado woody plant traits with spaceborne hyperspectral data

(Oral)

Pedro J. Leitão

p.leitao@tu-bs.de

Department Landscape Ecology and Environmental System Analysis, Technische Universität Braunschweig, Germany Geography Department, Humboldt-Universität zu Berlin, Germany, Germany

,

Marcel Schwieder

Geography Department, Humboldt-Universität zu Berlin, Germany, Germany

,

Fernando Pedroni

Instituto de Ciências Biológicas e da Saúde, Universidade Federal de Mato Grosso, Brazil, Brazil

,

Maryland Sanchez

Instituto de Ciências Biológicas e da Saúde, Universidade Federal de Mato Grosso, Brazil Brazil, Brazil

,

José R. Pinto

Departmento de Engenharia Florestal, Universidade de Brasília, Brazil, Brazil

,

Leandro Maracahipes

Instituto de Pesquisa Ambiental da Amazônia, Brazil, Brazil

,

Mercedes Bustamante

Departmento de Ecologia, Universidade de Brasília, Brazil, Brazil

,

Patrick Hostert

Geography Department, Humboldt Universität zu Berlin, Germany Integrated Research Institute on Transformations of Human-Environment Systems (IRI THESys), Humboldt Universität zu Berlin, Germany, Germany

,

Boris Schröder

Department Landscape Ecology and Environmental System Analysis, Technische Universität Braunschweig, Braunschweig, Germany, Germany

The Cerrado (Brazilian savannah), is the most diverse of all of the world's savannahs. While holding a high diversity and endemism of species, this biome is mostly unprotected and understudied. Also, recent studies have given focus on the importance of species traits, and on the need to incorporate them into biodiversity monitoring and conservation. In this paper, we used woody plant inventory data, plant trait data, and spaceborne hyperspectral (Hyperion) data to map woody plant traits in two study sites in the Cerrado. To this aim, we applied a Sparse Generalized Dissimilarity Modelling (SGDM) approach for modelling the species turnover on each site. Matrix calculations were applied to assign the sampled species to the derived turnover axes, and their specific traits. Furthermore, a knn-imputation applied to these axes allowed us to map the spatial patterns of the woody plant traits over our study sites.

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