Multivariable integration method for estimating sea surface salinity in coastal waters from in situ data and remotely sensed data using random forest algorithm
The multi-physicochemical parameters as a proxy of salinity were considered to retrieve the SSS. A random forest (RF) model was created to retrieve SSS by integrating in situ and remotely sensed data. A constructed RF model has the capability to estimate SSS in coastal waters, and was used extensively under different periods and could be reproduced.
multivariable integration sea surface salinity remote sensing random forest algorithm