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

Building earth observation data cubes on aws

by K. R. Ferreira¹, G. R. Queiroz¹, R. F. B. Marujo¹, and R. W. Costa¹

1National Institute for Space Research (INPE), Brazil

DOI: https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-597-2022

Publisher: ISPRS | Published: 30 May 2022

© Author(s) 2022. This work is distributed under the Creative Commons Attribution 4.0 License.

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.

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

Share and Cite

Ferreira, K. R., Queiroz, G. R., Marujo, R. F. B., and Costa, R. W.: BUILDING EARTH OBSERVATION DATA CUBES ON AWS, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 597–602, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-597-2022, 2022.

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