I'm searching for a remote sensing-based carbon flux model written in python language (open source). Can anyone recommend one, please? Thank you very much!
Yes, there are remote sensing-based carbon flux models that use data from satellites and other remote sensing platforms to estimate the exchange of carbon between the Earth's surface and the atmosphere. These models are based on the principle that changes in vegetation cover and other land use activities can affect the exchange of carbon between the biosphere and the atmosphere, and that these changes can be detected and quantified using remote sensing data.
One example of a remote sensing-based carbon flux model is the Ecosystem Demography model (ED), which uses data from satellite remote sensing, climate models, and ground-based observations to estimate carbon fluxes at regional and global scales. ED is a process-based model that simulates carbon uptake and release by ecosystems based on the physiological responses of different vegetation types to environmental conditions.
Another example is the Carnegie-Ames-Stanford Approach (CASA) model, which uses satellite data to estimate net primary productivity (NPP), the amount of carbon that is fixed by photosynthesis in ecosystems. CASA then uses this estimate to calculate the net ecosystem exchange (NEE) of carbon, which is the difference between carbon uptake by photosynthesis and carbon release by respiration.
Other remote sensing-based carbon flux models include the Simple Biosphere model (SiB), the Terrestrial Ecosystem Model (TEM), and the Biome-BGC model. These models vary in their complexity and the type of remote sensing data they use, but they all use remote sensing as a key input to estimate carbon fluxes at regional and global scales.
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