Title :
Developing an operational algorithm based on ANN for the retrieval of SMC from the incoming metop SCA mission
Author :
E. Santi;S. Paloscia;S. Pettinato;C. Notarnicola;F. Greifeneder;S. Hahn;W. Wagner;M. Vreugdenhil;C. Reimer
Author_Institution :
Inst. of Appl. Phys., Florence, Italy
fDate :
7/1/2015 12:00:00 AM
Abstract :
An Artificial Neural Network (ANN) algorithm for the Soil Moisture Content (SMC) retrieval from the C-band EPS-SG SCA scatterometer, which will replace the Metop ASCAT, was implemented and tested with real data and model simulations. The main aim of this activity was in understanding the potential of VH channel, which inclusion on the mid-beam antenna of EPS-SG SCA is currently being considered, for improving the retrieval accuracy respect to the existing SMC product derived from ASCAT.
Keywords :
"Artificial neural networks","Soil moisture","Backscatter","Accuracy","Vegetation mapping","Radar measurements","Data models"
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International
Electronic_ISBN :
2153-7003
DOI :
10.1109/IGARSS.2015.7326196