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

fYear

2014

fDate

13-18 July 2014

Firstpage

733

Lastpage

736

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International

Conference_Location

Quebec City, QC

Type

conf

DOI

10.1109/IGARSS.2014.6946528

Filename

6946528