Onboard data handling for remote sensing

Hyperspectral sensors acquire images in many, very narrow, contiguous frequency bands throughout the visible and near-infrared parts of the electromagnetic spectrum. The broadband imaging allows discrimination between features on the Earth's surface that have different light absorption and reflection characteristics. During recent years, hyper spectral imagery has opened groundbreaking perspectives in several applications, including observing climate changes and urban planning.

Even though algorithms processing hyperspectral data map nicely to parallel systems such as clusters of computers, these systems are difficult to adapt for onboard processing. The 'Quick image interpretation system' (QI2S) project was initiated to design such a platform and in which low-weight and low-power components could be integrated with EO satellites' payload. To achieve this ambitious objective, six partners joined their efforts and expertise in the individual components that they have been assigned.

In the first project phase, the QI2Sresearchers have designed a many-core computing engine based on field programmable gate arrays (FPGAs). Besides their low weight and small size, FPGAs provide similar computing performances at lower cost and the appealing possibility of adaptively selecting the data processing algorithm to be applied. The system hardware design embraces software building blocks for hyperspectral data processing and interpretation with high-level command language that allows for their reconfiguration.

The QI2S system is expected to enable dramatic reductions in the delivery of hyper spectral data to end users on the ground. With image interpretation performed onboard, it has been estimated that only a thin slice of the downlink channel's bandwidth will be required (not exceeding a few Mbit/sec). From days and even weeks, end users will be able to receive data requested within just minutes. Such a development paves the way for future exciting applications like early warning systems for natural hazards.