Discrimination of Agricultural Land Management Practices using Polarimetric Synthetic Aperture RADAR

Abstract

This thesis investigates the sensitivity and separability of post-harvest tillage conditions using polarimetric Synthetic Aperture RADAR in southwestern Ontario. Variables examined include: linear polarizations HH, HV, and VV and polarimetric variables: pedestal height, co-polarized complex correlation coefficient magnitude, left and right co-polarized circular polarizations and co-polarized phase difference. Six fine-quad polarimetric, high incidence angle (49°) RADARSAT-2 images acquired over three dates in fall 2010 were used. Over 100 fields were monitored, coincident with satellite overpasses. OMAFRA’s AgRI, a high-resolution polygon network was used to extract average response from fields. Discrimination between tillage practices was best later in the fall season, due to sample size and low soil moisture conditions. Variables most sensitive to tillage activities include HH and VV polarizations and co-polarized complex correlation coefficient magnitude. A supervised support vector machine (SVM) classifier classified no-till and conventional tillage with 91.5% overall accuracy. These results highlight the potential of RADARSAT-2 for monitoring tillage conditions.