Study on monitoring freezing disasters in winter wheat by remote sensing and variational techniques

Abstract

This work was based upon the combination of space-and ground-based data. Sensings at 1.1 km × 1.1 km resolution from the polar-orbiting weather satellite were retrieved by a range of split window algorithms to obtain surface temperatures, which were used to construct a regression equation with minimum surface temperatures (MST) measured at a number of meteorological stations, with the retrievals and measurements corrected by a variational scheme to get gridded MST's. After comparison of errors from these algorithms the best one was selected for retrieving. By use of the retrieved temperatures re-corrected by the variational technique, injury indices and wheat conditions during its growth stages, the regional distribution was prepared of varying-degree cold injuries to the crop, with corresponding hit areas statistically calculated, thereby making it possible to sensings monitor the injuries and precisely determine areas hit by the varying-degree droughts.