Title :
CATARSI — Cap and trade assessment by remote sensing investigation: An algorithm for crop and forest biomass estimate
Author :
Santi, E. ; Pettinato, S. ; Paloscia, S. ; Castracane, P. ; Di Giammatteo, U.
Author_Institution :
IFAC, Florence, Italy
Abstract :
In this paper the results obtained during the CATARSI project have been shown. The aim was to implement an algorithm capable to extract soil moisture and vegetation biomass from SAR data at both L and X bands. An algorithm based on Artificial Neural Networks was tested on SAR images collected in 2010 during the BioSAR (L-band) campaign in Sweden for the retrieval of forest biomass and in 2010-2012 in Italy by using COSMO-SkyMed (X-band) data for the retrieval of agricultural crop biomass. The results obtained demonstrated a clear sensitivity of backscattering at these frequencies to the biomass of both agricultural crops and forests. The retrieval algorithm was able to identify different levels of biomass with a notable accuracy.
Keywords :
geophysical image processing; image retrieval; neural nets; radar imaging; remote sensing by radar; soil; synthetic aperture radar; vegetation mapping; AD 2010 to 2012; BioSAR; CATARSI project; COSMO-SkyMed data; L bands; SAR data; Sweden; X bands; agricultural crop biomass; agricultural forests; artificial neural networks; backscattering sensitivity; biomass frequencies; biomass levels; crop biomass estimate; forest biomass estimate; remote sensing investigation; soil moisture; trade assessment; vegetation biomass; Accuracy; Agriculture; Artificial neural networks; Backscatter; Biomass; Synthetic aperture radar; Vegetation mapping; SAR; forest biomass; plant water content; soil moisture;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
Conference_Location :
Quebec City, QC
DOI :
10.1109/IGARSS.2014.6946528