Data Assimilation of PROBA-V 100 and 300 m

The project for on-board autonomy-vegetation (PROBA-V) satellite can produce global daily images at 300-m spatial resolution. Three sensors are mounted on the same platform. Two off-nadir-viewing sensors acquire imagery at 300-m spatial resolution, whereas a nadir-viewing sensor acquires imagery at 100-m spatial resolution. The swath of the nadir-viewing sensor is only half of the swath of a single off-nadir-viewing sensor. Using this sensor only, the revisit time is five days. Here, we present a data assimilation method to increase the temporal resolution of the 100-m product. The method implements a Kalman filter recursive algorithm that integrates the images at 100 and 300-m resolution to generate the assimilated imagery at the fine spatial detail (100 m). The proposed method can be applied for global products. In this study, it has been applied to a region in western Europe (Flanders) during the growing season. This region is particularly challenging due to frequent cloud cover (45% cloud cover on average). The assimilated product is a cloud-free time series at the temporal resolution of the 300-m data, while preserving the spatial detail of the 100-m data. Quantitative results show the potential of the method compared to a simple data assimilation and the Savitzky-Golay (SG) filter. The added value of the improved spatial resolution from 300 to 100 m has also been illustrated for monitoring agriculture via remote sensing in this area.