Davos - Gross Primary Production (2020-2023)

DOI - 10.23728/b2share.546045eb82714fad872096e1154d78e1

Handle - http://hdl.handle.net/11304/329430fe-de98-4e1b-9391-c75acf07fc26

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Gross Primary Production (GPP) represents the total amount of carbon fixed by plants through photosynthesis in an ecosystem over a specific period. GPP data products are derived using a data-driven approach that integrates Earth observation data with in-situ carbon flux measurements. Specifically, GPP estimations combine Sentinel-2 multispectral imagery with carbon flux data from eddy covariance towers, employing the XGBoost machine learning algorithm for prediction. The resulting GPP maps are generated at a 10-meter spatial resolution and a temporal frequency up to 5 days, covering the period from March 2017 to December 2023. The temporal resolution is contingent upon 50% free-cloud conditions in the area of interest, with lower frequencies occurring during periods of high cloud coverage. The spatial extent of the GPP maps corresponds to the boundaries of long-term observation sites as recorded in the DEIMS-SDR registry (e.g., https://deims.org/a547dab2-859a-414c-b148-0e7df8de5773). For sites where the boundary area is smaller than 1 km², or if only point coordinates are available in DEIMS-SDR, the maps are constrained to a 1 km x 1 km bounding box.

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