Hainich - Gross Primary Production (2019-2023)

DOI - 10.23728/b2share.5bc1b1eaaff745328a2132febb68b6b7

Handle - http://hdl.handle.net/11304/8f1980b3-d241-4491-8de3-b909ab9ce402

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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/5b409a72-2a45-4238-a501-e24f1a2900db). 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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