Evaluation of the potentiality of polarimetric C- and L-SAR time-series images for the identification of winter land-use

Land cover and land use monitoring, particularly during winter season, is still a major environmental challenge. Indeed, the presence of a vegetation cover, the dates of sowing, the length of the intercrop period, and land use types have an impact on pollutant transport to water bodies. The objective of this study was to evaluate the potentiality of polarimetric C- and L-SAR time-series to improve the identification and characterization of vegetation cover during winter season in a 130 km
²
area. Alos-2, Radarsat-2 and Sentinel-1 time-series were classified using RF algorithm. The best results were obtained from Radarsat-2 polarimetric images acquired between August 2016 and May 2017, with an overall accuracy of ~ 80%.