Copertina

Sun Induced Fluroscence Downscaling processor using openEO and Copernicus Data Space Ecosystem Infrastructure

Fuente: Zenodo

Salvato in:

Dettagli Bibliografici
Autori principali:	Daniel E. Pabon-Moreno, Qiqi Deng
Natura:	Recurso digital
Lingua:	inglese
Pubblicazione:	Zenodo 2026
Soggetti:	Sun-induced chlorophyll fluorescence SIF openEO CDSE Copernicus Data Space Ecosystem
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

_version_	1866901079056187392
author	Daniel E. Pabon-Moreno Qiqi Deng
author_facet	Daniel E. Pabon-Moreno Qiqi Deng
contents	<div dir="auto"> <h2>Description</h2> </div> <p dir="auto">Sun-induced chlorophyll fluorescence (SIF) is a re-emitted signal directly originating from the photosynthetic system, representing plant fluorescence observed from space. It is therefore considered a direct measure of plant physiological status and responses to environmental changes, while also serving as a potential indicator for estimating global gross primary productivity (GPP). However, the revisit cycles and operational altitudes of existing SIF observation platforms limit their spatio-temporal resolution. This results in decoupling between the linear relationship between global-scale SIF and GPP at finer temporal and spatial scales. The Sentinel-5P TROPOMI sensor, with its daily nadir spatial resolution of 3.5 × 5.5-7 km, enables more detailed observation of SIF/GPP in terrestrial ecosystems. The following example illustrates the downscaling process (i.e., increasing the spatial resolution) for SIF based on an mechanistic model that relates SIF with land-surface temperature, and NIRv (a vegetation index).</p> <div dir="auto"> <h2>Tutorial</h2> </div> <p dir="auto">You can run the processor following the <a href="https://dpabon.github.io/SIF_downscaling_CDSE/" rel="nofollow">tutorial</a> (We recommend <a href="https://positron.posit.co/" rel="nofollow">Positron</a> as it included all the batteries needed)</p> <ul> <li>First you need to install pixi:</li> </ul> <p dir="auto"><a href="https://pixi.sh/latest/" rel="nofollow">https://pixi.sh/latest/</a></p> <ul> <li>In positron set pixi tool path:</li> </ul> <p dir="auto">To check where pixi was installed you can run in a terminal</p> <p dir="auto">Linux and Mac: <code>whereis pixi</code></p> <p dir="auto">Windows: <code>where pixi</code></p> <p dir="auto">and copy paste the path into Positron settings "Python: Pixi Tool Path".</p> <ul> <li>You need to fork this github repository on github (This step is necessary as currently CDSE is not able to perform upsample operations. Then a spatial upsampling needs to run locally, upload to github and load the results in the CDSE again):</li> </ul> <p dir="auto"> </p> <p dir="auto">Then clone the repo into your local machine:</p> <p dir="auto"><code>git clone https://github.com/your_user_name/SIF_downscaling_CDSE</code></p> <ul> <li>Then install the dependencies using pixi:</li> </ul> <p dir="auto"><code>cd SIF_downscaling_CDSE</code></p> <p dir="auto"><code>pixi install</code></p> <p dir="auto">Now you have everything setup to run the <a href="https://dpabon.github.io/SIF_downscaling_CDSE/" rel="nofollow">tutorial</a>, Don't forget to select the pixi python interpreter before running.</p> <ul> <li><code>openEO_sif_downscaling.py</code> contains the active development of the SIF downscaling workflow using openEO.</li> <li><code>udf.py</code> contains the User Defined Function need it for openEO.</li> <li><code>environment.yml</code> contains the conda environment with all the packages need it to reproduce the analysis.</li> <li><code>data</code> contains a COG file and the corresponding geojson STAC.</li> </ul> <div dir="auto"> <h2>FAQ</h2> </div> <ul> <li>Q: Problems to run the tutorial?</li> </ul> <p dir="auto">A: Please open an <a href="https://github.com/dpabon/SIF_downscaling_CDSE/issues/new">issue</a></p> <ul> <li>Q: Can I select a new area to apply the procesor?</li> </ul> <p dir="auto">A: Sure, just change the values in the area of interest cell</p> <ul> <li>Q: Why pixi if everyone is using coda-forge?</li> </ul> <p dir="auto">A: Mainly because of convenience. pixi allows to easily create workspace for multiple platforms (the ones for this project include "linux-64", "win-64", "osx-64", "osx-arm64").</p> <ul> <li>Q: How can I contribute?</li> </ul> <p dir="auto">A: Clone this repository and create pull requests.</p> <div dir="auto"> <h2>Acknowledgement</h2> </div> <p dir="auto">This project has received funding from the <a href="https://earthmonitor.org/" rel="nofollow">Open-Earth-Monitor Cyberinfrastructure</a> project that is part of European Union's Horizon Europe research and innovation programme under grant <a href="https://cordis.europa.eu/project/id/101059548" rel="nofollow">101059548</a>.</p>
format	Recurso digital
id	zenodo_https___doi_org_10_5281_zenodo_19334966
institution	Zenodo
language	eng
publishDate	2026
publisher	Zenodo
record_format	zenodo
spellingShingle	Sun Induced Fluroscence Downscaling processor using openEO and Copernicus Data Space Ecosystem Infrastructure Daniel E. Pabon-Moreno Qiqi Deng Sun-induced chlorophyll fluorescence SIF openEO CDSE Copernicus Data Space Ecosystem <div dir="auto"> <h2>Description</h2> </div> <p dir="auto">Sun-induced chlorophyll fluorescence (SIF) is a re-emitted signal directly originating from the photosynthetic system, representing plant fluorescence observed from space. It is therefore considered a direct measure of plant physiological status and responses to environmental changes, while also serving as a potential indicator for estimating global gross primary productivity (GPP). However, the revisit cycles and operational altitudes of existing SIF observation platforms limit their spatio-temporal resolution. This results in decoupling between the linear relationship between global-scale SIF and GPP at finer temporal and spatial scales. The Sentinel-5P TROPOMI sensor, with its daily nadir spatial resolution of 3.5 × 5.5-7 km, enables more detailed observation of SIF/GPP in terrestrial ecosystems. The following example illustrates the downscaling process (i.e., increasing the spatial resolution) for SIF based on an mechanistic model that relates SIF with land-surface temperature, and NIRv (a vegetation index).</p> <div dir="auto"> <h2>Tutorial</h2> </div> <p dir="auto">You can run the processor following the <a href="https://dpabon.github.io/SIF_downscaling_CDSE/" rel="nofollow">tutorial</a> (We recommend <a href="https://positron.posit.co/" rel="nofollow">Positron</a> as it included all the batteries needed)</p> <ul> <li>First you need to install pixi:</li> </ul> <p dir="auto"><a href="https://pixi.sh/latest/" rel="nofollow">https://pixi.sh/latest/</a></p> <ul> <li>In positron set pixi tool path:</li> </ul> <p dir="auto">To check where pixi was installed you can run in a terminal</p> <p dir="auto">Linux and Mac: <code>whereis pixi</code></p> <p dir="auto">Windows: <code>where pixi</code></p> <p dir="auto">and copy paste the path into Positron settings "Python: Pixi Tool Path".</p> <ul> <li>You need to fork this github repository on github (This step is necessary as currently CDSE is not able to perform upsample operations. Then a spatial upsampling needs to run locally, upload to github and load the results in the CDSE again):</li> </ul> <p dir="auto"> </p> <p dir="auto">Then clone the repo into your local machine:</p> <p dir="auto"><code>git clone https://github.com/your_user_name/SIF_downscaling_CDSE</code></p> <ul> <li>Then install the dependencies using pixi:</li> </ul> <p dir="auto"><code>cd SIF_downscaling_CDSE</code></p> <p dir="auto"><code>pixi install</code></p> <p dir="auto">Now you have everything setup to run the <a href="https://dpabon.github.io/SIF_downscaling_CDSE/" rel="nofollow">tutorial</a>, Don't forget to select the pixi python interpreter before running.</p> <ul> <li><code>openEO_sif_downscaling.py</code> contains the active development of the SIF downscaling workflow using openEO.</li> <li><code>udf.py</code> contains the User Defined Function need it for openEO.</li> <li><code>environment.yml</code> contains the conda environment with all the packages need it to reproduce the analysis.</li> <li><code>data</code> contains a COG file and the corresponding geojson STAC.</li> </ul> <div dir="auto"> <h2>FAQ</h2> </div> <ul> <li>Q: Problems to run the tutorial?</li> </ul> <p dir="auto">A: Please open an <a href="https://github.com/dpabon/SIF_downscaling_CDSE/issues/new">issue</a></p> <ul> <li>Q: Can I select a new area to apply the procesor?</li> </ul> <p dir="auto">A: Sure, just change the values in the area of interest cell</p> <ul> <li>Q: Why pixi if everyone is using coda-forge?</li> </ul> <p dir="auto">A: Mainly because of convenience. pixi allows to easily create workspace for multiple platforms (the ones for this project include "linux-64", "win-64", "osx-64", "osx-arm64").</p> <ul> <li>Q: How can I contribute?</li> </ul> <p dir="auto">A: Clone this repository and create pull requests.</p> <div dir="auto"> <h2>Acknowledgement</h2> </div> <p dir="auto">This project has received funding from the <a href="https://earthmonitor.org/" rel="nofollow">Open-Earth-Monitor Cyberinfrastructure</a> project that is part of European Union's Horizon Europe research and innovation programme under grant <a href="https://cordis.europa.eu/project/id/101059548" rel="nofollow">101059548</a>.</p>
title	Sun Induced Fluroscence Downscaling processor using openEO and Copernicus Data Space Ecosystem Infrastructure
topic	Sun-induced chlorophyll fluorescence SIF openEO CDSE Copernicus Data Space Ecosystem
url	https://doi.org/10.5281/zenodo.19334966