This is an attempt to simulate a scenario where the user has some field data that they want to integrate into WaPOR's standardized protocol for land and water productivity analyses using WaPOR remote sensing model's calculations. By preparing the field or local data through converting them into different shapes and types to be compatible with the WaPOR model, we can overcome some of the limitations associated with open-source remote sensing data, such as land surface temperature, land cover noise, the number of cloud-free RS images, the time of day when the images are taken, and the angle of image capture and its correction function. This allows us to obtain more accurate results and maximum benefit from WaPOR model data and calculations.
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original WaPOR script (to get more information about the script, what it does, how it works and the used packages):
https://github.com/wateraccounting/WAPORWP -
I commented with three hashes "###"
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A pref introduction about WaPOR (you well find the rest in the original script):
FAO’s portal to monitor Water Productivity through Open-access of Remotely sensed derived (WaPOR) was “created to provide relevant and specific information on water and biomass status to develop solutions to sustainably increase agricultural land and water productivity”. For more: https://www.fao.org/in-action/remote-sensing-for-water-productivity/wlpa-introduction/introduction/en/ -
Where I got the limitations: https://doi.org/10.5194/hess-2021-409
Email: mohammedalmak98@gmail.com
LinkedIn: https://www.linkedin.com/in/mohammed-salah-16aa75237