In a volcanic emergency, time is of the essence. It is vital to quantify eruption parameters (thermal emission, effusion rate, location of activity) and distribute this information as quickly as possible to decision-makers in order to enable effective evaluation of eruption-related risk and hazard. The goal of this work was to automate and streamline processing of spacecraft hyperspectral data, automate product generation, and automate distribution of products.
The software rapidly processes hyperspectral data, correcting for incident sunlight where necessary, and atmospheric transmission; detects thermally anomalous pixels; fits data with model black-body thermal emission spectra to determine radiant flux; calculates atmospheric convection thermal removal; and then calculates total heat loss. From these results, an estimation of effusion rate is made. Maps are generated of thermal emission and location (see figure). Products are posted online, and relevant parties notified. Effusion rate data are added to historical record and plotted to identify spikes in activity for persistently active eruptions. The entire process from start to end is autonomous.
Future spacecraft, especially those in deep space, can react to detection of transient processes without the need to communicate with Earth, thus increasing science return. Terrestrially, this removes the need for human intervention.
This work was done by Ashley G. Davies, Joshua R. Doubleday, and Steve A. Chien of Caltech for NASA’s Jet Propulsion Laboratory.
This Brief includes a Technical Support Package (TSP).
Automating Hyperspectral Data for Rapid Response in Volcanic Emergencies
(reference NPO-48123) is currently available for download from the TSP library.
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