Abstract
One challenge in Earth science research is the accurate and efficient ad-hoc query and retrieval of Earth science satellite sensor data based on user-defined criteria to study and analyze atmospheric events such as tropical cyclones. The problem can be formulated as a spatio-temporal join query to identify the spatio-temporal location where moving sensor objects and dynamic atmospheric event objects intersect, either precisely or within a user-defined proximity. In this paper, we describe an efficient query and retrieval framework to handle the problem of identifying the spatio-temporal intersecting positions for satellite sensor data retrieval. We demonstrate the effectiveness of our proposed framework using sensor measurements from QuikSCAT (wind field measurement) and TRMM (precipitation vertical profile measurements) satellites, and the trajectories of the tropical cyclones occurring in the North Atlantic Ocean in 2009.
This work was partially carried out at the Jet Propulsion Laboratory, California Institute of Technology and was funded by the National Aeronautics and Space Adminstration (NASA) Advanced Information Systems Technology (AIST) Program under grant number AIST-08-0081.
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Ho, SS., Tang, W., Liu, W.T., Schneider, M. (2010). A Framework for Moving Sensor Data Query and Retrieval of Dynamic Atmospheric Events. In: Gertz, M., Ludäscher, B. (eds) Scientific and Statistical Database Management. SSDBM 2010. Lecture Notes in Computer Science, vol 6187. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13818-8_9
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DOI: https://doi.org/10.1007/978-3-642-13818-8_9
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