I will keep this simple, just one map a week.
The “Landsat Gross Primary Production” will serve as our jumping off point.
The dataset that was used to create the above map was derived from an estimate of gross primary production (GPP) carried out with the use of Landsat Surface Reflectance.
But first, let’s talk about GPP. At the level of an ecosystem, the term “gross primary productivity” (GPP) refers to the total quantity of carbon dioxide that is captured by plants during photosynthesis. or, to put it another way, the quantity of carbon that is extracted from the air. As can be seen in the figure, this varies not just during the course of the year in accordance with the patterns of vegetation (for both annuals and perennials), but also throughout the course of the day, and across areas in response to the different climatic rhythms.
There is no direct method for seeing this mechanism because of the nature of the process itself; nevertheless, models such as the MOD17 algorithm attempt to show this, relying on a combination of meteorological data, land cover classification, leaf area index, and fraction of photosynthetically active radiation. Luckily for all of us, these models help to depict this. The low spatial resolution of this product, despite its widespread use, is a significant drawback.
The product used to create the above map, however, is based on the Landsat mission, resulting in a spatial resolution of 30 meters. Visit this document if you want to grasp the nitty-gritty details of this work.
Bibliography and interesting reads:
Robinson, N.P., B.W. Allred, W.K. Smith, M.O. Jones, A. Moreno, T.A. Erickson, D.E. Naugle, and S.W. Running. 2018. Terrestrial primary production for the conterminous United States derived from Landsat 30 m and MODIS 250 m. Remote Sensing in Ecology and Conservation. doi:10.1002/rse2.74
Marconato, U., Fernández, R. J., & Posse, G. (2022). Cropland Net Ecosystem Exchange Estimation for the Inland Pampas (Argentina) Using EVI, Land Cover Maps, and Eddy Covariance Fluxes. Frontiers in Soil Science, 0, 27. https://doi.org/10.3389/FSOIL.2022.903544
Anav, A., Friedlingstein, P., Beer, C., Ciais, P., Harper, A., Jones, C., Murray-Tortarolo, G., Papale, D., Parazoo, N. C., Peylin, P., Piao, S., Sitch, S., Viovy, N., Wiltshire, A., & Zhao, M. (n.d.). Spatiotemporal patterns of terrestrial gross primary production: A review. https://doi.org/10.1002/2015RG000483
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