Correcting gedi water level estimates for inland waterbodies using machine learning

HIGHLIGHTS

• who: Ibrahim Fayad and collaborators from the University of Montpellier, AgroParisTech, CIRAD, CNRS, INRAE, AgroParisTech, Paris, France have published the paper: Correcting GEDI Water Level Estimates for Inland Waterbodies Using Machine Learning, in the Journal: (JOURNAL) of 14/03/2022
• what: The aim of the CSM product is to distinguish between cloudy (pixel value of 1) and clear pixels (pixel value of 0) in a satellite scene at each GEDI acquisition. To improve the altimetric capabilities of GEDI acquisitions, the authors propose a series of models that estimate the difference between GEDI and in situ . . .
  

   

  

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