%0 Journal Article
%4 sid.inpe.br/mtc-m21c/2018/08.06.16.46
%2 sid.inpe.br/mtc-m21c/2018/08.06.16.46.23
%@doi 10.1038/sdata.2018.132
%@issn 2052-4436
%T Data Descriptor: FRY, a global database of fire patch functional traits derived from space-borne burned area products
%D 2018
%8 July
%9 journal article
%A Laurent, Pierre,
%A Mouillot, Florent,
%A Yue, Chao,
%A Ciais, Philippe,
%A Moreno, M. Vanesa,
%A Nogueira, Joana Messias Pereira,
%@affiliation Laboratoire des Sciences du Climat et de l'Environnement
%@affiliation Université de Montpellier
%@affiliation Laboratoire des Sciences du Climat et de l'Environnement
%@affiliation Laboratoire des Sciences du Climat et de l'Environnement
%@affiliation Université de Montpellier
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@electronicmailaddress pierre.laurent@lsce.ipsl.fr
%@electronicmailaddress florent.mouillot@cefe.cnrs.fr
%@electronicmailaddress
%@electronicmailaddress
%@electronicmailaddress
%@electronicmailaddress joana.nogueira_funcate@inpe.br
%B Scientific Data
%V 5
%P e180132
%X Vegetation fires are intrinsic ecosystem disturbances of the Earth system. Global burned area products have been delivered from several space-borne instruments, and have recently provided pixel-level information underpinning fire spread processes. Here we present FRY, a global database of fire patches with morphology-based functional traits reconstructed from pixel-based burned areas derived from the MODIS and MERIS imagery using a flood-fill algorithm. Each fire patch is characterized by the geo-location of its center, area, perimeter, the features of the ellipse fitted over its pixel's spatial distribution, and different indices of patch complexity. We obtained a consistent spatial distribution of global fire patch functional traits between the MCD64A1 Collection 6 and the MERIS fire-cci v4.1 datasets during their overlap period (2005-2011), confirming the robustness of the applied algorithm and the consistency between both products. This database is relevant to a broad spectrum of fire-related applications such as local to global functional pyrodiversity, fire emissions quantification, and the benchmarking of fire modules embedded in dynamic global vegetation models.
%@language en
%3 laurent_data.pdf