Minimize eoPortal News

Evaluating the Efficiency of Data Assimilation

07 January 2019

Web Content Image

Information is lost when researchers combine statistical models and remote sensing data, but just how much is often unclear. A new study offers a framework to measure the inefficiency.

The 20th century statistician George Box is widely credited with the remark that "essentially all [statistical] models are wrong, but some are useful." And it's true: As abstractions of the real world, models can only generalize the systems we study. The same holds for remotely sensed data, often collected via satellite or aircraft.

Source: EOS - Earth & Space Science News

Image credit: Dr. Amy McNally (NASA Goddard Space Flight Center) - A member of the SMAP team collecting soil moisture data for calibration and validation in Yanco, Australia.

Related Missions:


Minimize Newsletter Subscribe

It`s one of the most convenient ways to stay up to date with the most important Earth Observation news from around the world.