New Processor and Reference Dataset for Hyperspectral CHRIS-PROBA Images Over Coastal and Inland Waters

LAVIGNE, H.; VANHELLEMONT, Q.; RUDDICK, K.; DOGLIOTTI, A.I.

Simposio; International Geoscience and Remote Sensing Symposium; 2021

Hyperspectral remote sensing is expected to facilitate aquatic applications, such as the monitoring of harmful algal blooms or the determination of suspended sediment properties. However, this requires accurate processing to retrieve water reflectance from top of atmosphere radiance. Here we present a new processor for hyperspectral (mode 1) CHRIS-PROBA images and make available to the public a sample dataset of water reflectance images. Although the CHRIS-PROBA sensor has been operating for about 20 years, only a few images with water targets were acquired with the hyperspectral mode (mode 1) and a dedicated atmospheric correction was needed. The processor presented here includes systematic noise removal, atmospheric correction and georeferencing. Validation of water reflectance products shows generally good consistency between in situ and satellite measurements although an underestimation in the 400 nm – 470 nm range was observed. Finally, it is expected that the sample dataset of hyperspectral water reflectance images will be useful to test new algorithms for water products or to compare processing methods.