ETL for the integration of remote sensing data

Authors

Keywords:

ETL, Satellite Imagery, Data Processing

Abstract

Modern in-orbit satellites and other available remote sensing tools have generated a huge availability of public data waiting to be exploited in different formats hosted on different servers. In this context, ETL formalism becomes relevant for the integration and analysis of the combined information from all these sources. Throughout this work, we present the theoretical and practical foundations to build a modular analysis infrastructure that allows the creation of ETLs to download, transform and integrate data coming from different instruments in different formats. Part of this work is already implemented in a Python library which is intended to be integrated into already available workflow management tools based on acyclic-directed graphs which also have different adapters to impact the combined data in different warehouses.

Author Biographies

  • Paula Verónica Romero Jure, Universidad Nacional de Córdoba, Argentina

    From Salta, Argentina.

    Degree in Physics from Universidad Nacional de Córdoba.

    I have worked with data from several satellite sensors, mainly applied to the study of clouds and types of clouds.
    I am skilled in quality-assured programming, particularly in Python, and in the usage of machine learning algorithms.

    I am interested in the fields of Earth Observation, Data Processing,  Geospatial Data Analysis, Remote Sensing and Atmospheric Physics and Machine Learning.

  • Juan Bautista Cabral, Instituto de Astronomía Teórica y Experimental, Argentina

    Also, I am a full-stack developer and software engineer with extensive Python, web, and scientific programming experience.

    As community organizer: I have been the chair of PyCon Argentina 2012, the Python Argentina flagship conference, and I was one of the original founders of the Scipy LatAm Community and also i was elected chair of SciPy LatAm 2015

    Professionally, I have worked in businesses of every size, from multinational corporations to startups, primarily small, focused teams.

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Published

2023-07-11

Issue

Vol. 9 No. 12 (2023): SAIV - Argentine Symposium on Images and Vision

Section

SAIV - Simposio Argentino de Imágenes y Visión

License

Copyright (c) 2023 Paula Verónica Romero Jure, Juan Bautista Cabral, Sergio Masuelli

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

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How to Cite

Romero Jure, P. V., Cabral, J. B., & Masuelli, S. (2023). ETL for the integration of remote sensing data. JAIIO, Jornadas Argentinas De Informática, 9(12). https://revistas.unlp.edu.ar/JAIIO/article/view/18246