This paper describes an algorithm for retrieving the snow depth from the data acquired by the microwave radiometers operating from space. The algorithm is based on Artificial Neural Network techniques and has been developed and tested using a large dataset of AMSR-E acquisitions and corresponding direct measurements of snow depth and air temperature collected over Siberia within the framework of the GCOM/AMSR2 mission. The algorithm has been subsequently applied to the AMSR-E acquisitions collected during the winter seasons between 2002 and 2011 on Alpine regions, setting up a procedure for evaluating and correcting the effects of the orography and the forest coverage. © 2012 IEEE.
Monitoring of snow cover on Italian Alps using AMSR-E and artificial neural Networks
Santi E;Fontanelli G;Pettinato S;
2012
Abstract
This paper describes an algorithm for retrieving the snow depth from the data acquired by the microwave radiometers operating from space. The algorithm is based on Artificial Neural Network techniques and has been developed and tested using a large dataset of AMSR-E acquisitions and corresponding direct measurements of snow depth and air temperature collected over Siberia within the framework of the GCOM/AMSR2 mission. The algorithm has been subsequently applied to the AMSR-E acquisitions collected during the winter seasons between 2002 and 2011 on Alpine regions, setting up a procedure for evaluating and correcting the effects of the orography and the forest coverage. © 2012 IEEE.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
