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.
CATARSI - Cap and trade assessment by remote sensing investigation: An algorithm for crop and forest biomass estimate
Santi Emanuele;Pettinato Simone;Paloscia Simonetta;
2014
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
