Computer Science – Learning
Scientific paper
May 2006
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2006agusmin43a..02d&link_type=abstract
American Geophysical Union, Fall Meeting 2007, abstract #IN43A-02
Computer Science
Learning
4540 Ice Mechanics And Air/Sea/Ice Exchange Processes (0700, 0750, 0752, 0754)
Scientific paper
The Autonomous Sciencecraft Experiment (ASE) is operating on-board Earth Observing - 1 (EO-1) with the Hyperion hyper-spectral visible to short-wave infrared spectrometer. ASE science activities include autonomous monitoring of cryospheric changes, triggering the collection of additional data when change is detected and filtering of null data such as no change or cloud cover. A cryosphere classification algorithm, developed with Support Vector Machine (SVM) machine learning techniques [1], replacing a manually derived classifier used in earlier operations [2], has been used in conjunction with on-board autonomous software application to execute over two hundred on-board scenarios in 2005 and early 2006, to detect and autonomously respond to sea ice break-up and formation, lake freeze and thaw, as well as the onset and melting of snow cover on land. This demonstrates an approach which could be applied to the monitoring of cryospheres on Earth and Mars as well as the search for dynamic activity on the icy moons of the outer solar system. [1] Castano et al. (2005) Learning classifiers for event detection in remote sensing imagery, i-SAIRAS, [2] Doggett et al. (2006), Autonomous detection of cryospheric change with Hyperion on-board Earth Observing-1, Rem. Sens. Env. (in press)
Davies Andrew G.
Doggett T. C.
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