Multitemporal SAR data for crop monitoring – signal modelling and analysis of biophysical variables dynamic

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Context and objectives

The objective was the assessment the ERS-1 SAR data capabilities to retrieve quantitative biophysical and geophysical variables in the perspective of crop monitoring, based on complementary contributions from a theoretical and an empirical approach.

Project outcome

Expected scientific results

The theoretical approach focused on the understanding of the backscattering by row structured crop canopies at early growth stages (e.g. maize, sugar beet, vineyard and sorghum). The research lead to the development of a semi-empirical model accounting for the structure and orientation of the canopy rows and which could be used for the early prediction of crop yield. The empirical study was based on a very intensive ground campaign set up over 550 maize fields. The collected data were put together in a relational database with meteorological data and ERS-1 backscattering coefficients extracted from 12 ERS-1 SAR images acquired over the whole season. The database was built in order to provide sufficient data for the calibration and the validation of the modelling, to allow studying the relationships between the signal and the biophysical and geophysical variables as well as to be used as input for agrometeorological models.
A correlation coefficient of 0.99 between dry matter quantity per ha and the backscattering coefficient was found in fields with a common row orientation. The rows' direction only influenced the ERS-1 signal when the soil was visible. These findings therefore certified the ERS-1 capabilities for crop growth monitoring.
Project leader(s): UCL - Environmental Sciences
Location: Region:
  • Belgium