Sen2Chain: An Open-Source Toolbox for Processing Sentinel-2 Satellite Images and Producing Time-Series of Spectral Indices

Fuente: arXiv
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Autori principali: Revillion, Christophe, Mouquet, Pascal, Commins, Jeremy, Miranville, Juliette, Wolff, Charlotte, Germain, Thomas, Jego, Sylvaine, Longour, Lucas, Girond, Florian, Bouche, Didier, Devillers, Rodolphe, Pennober, Gwenaelle, Herbreteau, Vincent
Natura: Preprint
Pubblicazione: 2024
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author Revillion, Christophe
Mouquet, Pascal
Commins, Jeremy
Miranville, Juliette
Wolff, Charlotte
Germain, Thomas
Jego, Sylvaine
Longour, Lucas
Girond, Florian
Bouche, Didier
Devillers, Rodolphe
Pennober, Gwenaelle
Herbreteau, Vincent
author_facet Revillion, Christophe
Mouquet, Pascal
Commins, Jeremy
Miranville, Juliette
Wolff, Charlotte
Germain, Thomas
Jego, Sylvaine
Longour, Lucas
Girond, Florian
Bouche, Didier
Devillers, Rodolphe
Pennober, Gwenaelle
Herbreteau, Vincent
contents The increasing availability of free high-resolution earth observation data covering any point on the globe every few days led to the emergence of new remote sensing tools that can manipulate the very large volumes of data generated by those satellites. We present Sen2Chain, an open-source Python tool that can automate the processing of large time series of Sentinel-2 images for their use in various fields (e.g., environmental health, natural hazards, ecology). Sen2Chain allows downloading images from various earth observation data suppliers, applying geometric and atmospheric corrections using ESA's Sen2Cor tool, and generating and applying cloud masks. Sen2Chain's ability to extract time series of spectral indices (e.g NDVI, NDWI) provides simplified access to value-added environmental information for a wide range of end-users and applications. Sen2Chain enables all data processing stages to be customized and chained together, with the possibility to automate and parallelize the processing, and optimize data management. Sen2Chain is paving the way for the creation and processing of a large earth observation image database dedicated to users who require time-series and/or perform regular environmental observations. The Web tool Sen2Extract is also presented, which enables end-users with no expertise in remote sensing to easily extract time-series for 11 spectral indices values for specific regions of interest.
format Preprint
id arxiv_https___arxiv_org_abs_2404_04305
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Sen2Chain: An Open-Source Toolbox for Processing Sentinel-2 Satellite Images and Producing Time-Series of Spectral Indices
Revillion, Christophe
Mouquet, Pascal
Commins, Jeremy
Miranville, Juliette
Wolff, Charlotte
Germain, Thomas
Jego, Sylvaine
Longour, Lucas
Girond, Florian
Bouche, Didier
Devillers, Rodolphe
Pennober, Gwenaelle
Herbreteau, Vincent
Geophysics
Instrumentation and Methods for Astrophysics
Data Analysis, Statistics and Probability
The increasing availability of free high-resolution earth observation data covering any point on the globe every few days led to the emergence of new remote sensing tools that can manipulate the very large volumes of data generated by those satellites. We present Sen2Chain, an open-source Python tool that can automate the processing of large time series of Sentinel-2 images for their use in various fields (e.g., environmental health, natural hazards, ecology). Sen2Chain allows downloading images from various earth observation data suppliers, applying geometric and atmospheric corrections using ESA's Sen2Cor tool, and generating and applying cloud masks. Sen2Chain's ability to extract time series of spectral indices (e.g NDVI, NDWI) provides simplified access to value-added environmental information for a wide range of end-users and applications. Sen2Chain enables all data processing stages to be customized and chained together, with the possibility to automate and parallelize the processing, and optimize data management. Sen2Chain is paving the way for the creation and processing of a large earth observation image database dedicated to users who require time-series and/or perform regular environmental observations. The Web tool Sen2Extract is also presented, which enables end-users with no expertise in remote sensing to easily extract time-series for 11 spectral indices values for specific regions of interest.
title Sen2Chain: An Open-Source Toolbox for Processing Sentinel-2 Satellite Images and Producing Time-Series of Spectral Indices
topic Geophysics
Instrumentation and Methods for Astrophysics
Data Analysis, Statistics and Probability
url https://arxiv.org/abs/2404.04305