The Earth Observing One (EO-1) mission has been a pathfinder in demonstrating autonomous operations paradigms. In 2010-2012 (and continuing), EO-1 has been supporting sensorweb operations to enable autonomous tracking of flooding in Thailand. In this approach, the Moderate Imaging Spectrometer (MODIS) is used to perform broad-scale monitoring to track flooding at the regional level (500 m/pixel) and EO-1 is autonomously tasked in response to alerts to acquire higher resolution (30 m/pixel) Advanced Land Imager (ALI) data. This data is then automatically processed to derive products such as surface water extent and volumetric water estimates. These products are then automatically pushed to relevant authorities in Thailand for use in damage estimation, relief efforts, and damage mitigation.EO-1 has served as a testbed and pathfinder to this type of sensorweb operations. Beginning with EO-1, these techniques for monitoring are being extended to other space sensors (such as Radarsat-2, Landsat, Worldview-2, TRMM) and integrated with hydrological models, and integration with in-situ sensors.Index Terms-Flooding, hydrological modeling, in-situ sensing, space-based remote sensing.
The bioinformatics research area is now faced with a mountain of ever-increasing and distributed information. For example, finding a single gene of the Oryza sativa (rice) genome one must spend weeks, if not months, wandering through approximately 40 million base pairs. These data are scattered in many data repositories. Thus, not only do we need an efficient tool to visualize and analyze DNA data, but the integration and exchange of information on a particular gene or coding regions from different international collaborative databases needs to be done in a careful, but robust manner as well. This research suggests a feasible means to overcome these problems by employing two main technologies. To support the exchange and communication between several sources of data, the grid database technology will be employed on the fast Internet2 backbone. Then, XML-based DNA data will be transported between collaborative sources for further analysis and representation. A preliminary version of our Web-based viewer for the XML data of the Oryza sativa genome is presented to illustrate the idea.
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