The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIII-B3-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 597–602, 2022
https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-597-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 597–602, 2022
https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-597-2022
 
30 May 2022
30 May 2022

BUILDING EARTH OBSERVATION DATA CUBES ON AWS

K. R. Ferreira, G. R. Queiroz, R. F. B. Marujo, and R. W. Costa K. R. Ferreira et al.
  • National Institute for Space Research (INPE) Avenida dos Astronaustas, 1758, São José dos Campos, SP, Brazil

Keywords: remote sensing images, big data, Earth observation data cubes, cloud computing, image time series analysis

Abstract. Image time series analysis and machine learning methods have been widely used in recent years to extract information from big data of remote sensing images. To support image time series analysis, remote sensing images have been modeled as Earth observation (EO) data cubes. EO data cubes can be defined as a set of time series associated to spatially aligned pixels ready for analysis. This paper describes an application for building EO data cubes on the Amazon Web Service (AWS) cloud computing environment. The Data Cube Builder on AWS application is based on a serverless approach to produce EO data cubes from remote sensing images stored in AWS buckets. In this work, we present the architecture of this application and its use to produce EO data cubes for Brazil from big data of remote sensing images.