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
Publisher: ISPRS | Published: 30 May 2022
© Author(s) 2022. This work is distributed under the Creative Commons Attribution 4.0 License.
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