Slide 1

Production, visualization and analysis of large volumes of remote sensing images modeled as multidimensional data cubes for the entire Brazilian territory.

Accessing and processing Brazilian earth observation data cubes with the open data cube platform

by V. C. F. Gomes1,2,  F. M. Carlos2,  G. R. Queiroz2,  K. R. Ferreira2 and R. Santos2

1C4ISR Division, Institute for Advanced Studies (IEAv), São José dos Campos, SP 12228-001, Brazil

²National Institute for Space Research (INPE), Brazil


Publisher: ISPRS | Published: 17 Jun 2021

© Author(s) 2021. This work is distributed under the Creative Commons Attribution 4.0 License.


Recently, several technologies have emerged to address the need to process and analyze large volumes of Earth Observations (EO) data. The concept of Earth Observations Data Cubes (EODC) appears, in this context, as the paradigm of technologies that aim to structure and facilitate the way users handle this type of data. Some projects have adopted this concept in developing their technologies, such as the Open Data Cube (ODC) framework and the Brazil Data Cube (BDC) platform, which provide open-source tools capable of managing, processing, analyzing, and disseminating EO data. This work presents an approach to integrate these technologies through the access and processing of data products from the BDC platform in the ODC framework. For this, we developed a tool to automate the process of searching, converting, and indexing data between these two systems. Besides, four ODC functional modules have been customized to work with BDC data. The tool developed and the changes made to the ODC modules expand the potential for other initiatives to take advantage of the features available in the ODC.

Keywords: Spatial Data Infrastructure, Big Earth Observation Data, Data Cube, STAC

Share and Cite

Gomes, V. C. F., Carlos, F. M., Queiroz, G. R., Ferreira, K. R., and Santos, R.: ACCESSING AND PROCESSING BRAZILIAN EARTH OBSERVATION DATA CUBES WITH THE OPEN DATA CUBE PLATFORMISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-4-2021, 153–159, 2021.

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