Spaceborne hyperspectral imagers collect enough information to positively identify materials and substances on the ground. Scientists often use hyperspectral data to investigate land use, mineral deposits, or signs of climate change. The same data is also useful during disasters or other emergencies when detection and mapping of fires, chemical agents, or flooded areas can provide critical information to first responders. The latter application relies on the ability to identify materials quickly and accurately.
The sheer volume of data in the image causes many applications to run slowly and produce poor results, as they search the full image dataset for the information they need. NASA Goddard developed a system that creates reduced datasets tailored for each potential application.
The system can operate on archived hyperspectral imagery from NASA's EO-1 Hyperion instrument or on data from future missions, such as the Hyper-spectral Infrared Imager (HyspIRI), as they become operational. Other agencies with hyperspectral imagers, including the defense and intelligence communities, can also use the system in their applications. Additionally, the system can operate onboard the spacecraft, allowing them to quickly and autonomously analyze the imagery they collect. Spacecraft with this capability could detect emerging situations and then intelligently re-task themselves to collect more data or alert scientists or emergency personnel on the ground.
This innovation includes an algorithm to convert hyperspectral images to a progressive format, along with another algorithm to quickly analyze hyperspectral images in this progressive format and select the most important bands for a given science application.