@Article{GomesQueFerPebBar:2024:ToBiEa,
author = "Gomes, Vitor Conrado F. and Queiroz, Gilberto Ribeiro de and
Ferreira, Karine Reis and Pebesma, Edzer and Barbosa, Cl{\'a}udio
Clemente Faria",
affiliation = "{Instituto de Estudos Avan{\c{c}}ados (IEAv)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)} and {Westfalische Wilhelms University}
and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
title = "Brazil Data Cube Workflow Engine: a tool for big Earth observation
data processing",
journal = "International Journal of Digital Earth",
year = "2024",
volume = "17",
number = "1",
pages = "e2313099",
month = "Dec.",
keywords = "Big data, Earth observation data, spatial data infrastructure,
openEO, workflow orchestration.",
abstract = "Earth Observation (EO) satellites have produced vast image
collections that are freely accessible to society. However,
handling these images often surpasses the capabilities of
traditional hardware and software for EO data storage and
processing, posing challenges for traditional Spatial Data
Infrastructure (SDI). To overcome these challenges, innovative
cloud computing and distributed systems have been developed, such
as matrix databases, MapReduce systems, and web services. These
technologies are now integrated into leading-edge platforms,
forming a new generation of SDI for big EO data. These platforms
have different characteristics in terms of governance,
technologies, data access, infrastructure abstractions, data
processing, and flexibility to extend their functionality. Our
work contributes to the area of SDI for big EO data by proposing a
server-side data-processing tool called Brazil Data Cube Workflow
Engine (BDC-WE), based on workflow orchestration approach. BDC-WE
provides a high-level interface using the openEO API for big EO
data accessing and processing, allowing SDI maintainers to easily
describe sequences of processes and integrate new algorithms. The
architecture proposed in this study was implemented and the
prototype was evaluated in two case studies described in this
paper.",
doi = "10.1080/17538947.2024.2313099",
url = "http://dx.doi.org/10.1080/17538947.2024.2313099",
issn = "1753-8947",
language = "en",
targetfile = "Brazil Data Cube Workflow Engine a tool for big Earth observation
data processing.pdf",
urlaccessdate = "29 jun. 2024"
}