Mapping Agricultural Frozen Soil on the Watershed Scale Using Remote Sensing Data

Abstract

This paper presents an empirical model for classifying frozen/unfrozen soils in the entire Bras d’Henri River watershed (167 km2) near Quebec City (Quebec, Canada). It was developed to produce frozen soil maps under snow cover using RADARSAT-1 fine mode images and in situ data during three winters. Twelve RADARSAT-1 images were analyzed from fall 2003 to spring 2006 to discern the intra- and interannual variability of frozen soil characteristics. Regression models were developed for each soil group (parent material-drainage-soil type) and land cover to establish a threshold for frozen soil from the backscattering coefficients (HH polarization). Tilled fields showed higher backscattering signal (+3 dB) than the untilled fields. The overall classification accuracy was 87% for frozen soils and 94% for unfrozen soils. With respect to land use, that is, tilled versus untilled fields, an overall accuracy of 89% was obtained for the tilled fields and 92% for the untilled fields. Results show that this new mapping approach using RADARSAT-1 images can provide estimates of surface soil status (frozen/unfrozen) at the watershed scale in agricultural areas.