A Framework for Moving Sensor Data Query and Retrieval of Dynamic Atmospheric Events
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 spatiotemporal join q...
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ftciteseerx:oai:CiteSeerX.psu:10.1.1.190.500 2023-05-15T17:32:20+02:00 A Framework for Moving Sensor Data Query and Retrieval of Dynamic Atmospheric Events Shen-shyang Ho Wenqing Tang W. Timothy Liu Markus Schneider The Pennsylvania State University CiteSeerX Archives 2010 application/pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.190.500 http://www.cise.ufl.edu/%7Emschneid/Research/papers/HTLS10SSDBM.pdf en eng Springer http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.190.500 http://www.cise.ufl.edu/%7Emschneid/Research/papers/HTLS10SSDBM.pdf Metadata may be used without restrictions as long as the oai identifier remains attached to it. http://www.cise.ufl.edu/%7Emschneid/Research/papers/HTLS10SSDBM.pdf join text 2010 ftciteseerx 2016-01-07T16:53:44Z 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 spatiotemporal 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. Key words: data retrieval, satellite data, atmospheric events, spatiotemporal Text North Atlantic Unknown Handle The ENVELOPE(161.983,161.983,-78.000,-78.000) |
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join Shen-shyang Ho Wenqing Tang W. Timothy Liu Markus Schneider A Framework for Moving Sensor Data Query and Retrieval of Dynamic Atmospheric Events |
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description |
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 spatiotemporal 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. Key words: data retrieval, satellite data, atmospheric events, spatiotemporal |
author2 |
The Pennsylvania State University CiteSeerX Archives |
format |
Text |
author |
Shen-shyang Ho Wenqing Tang W. Timothy Liu Markus Schneider |
author_facet |
Shen-shyang Ho Wenqing Tang W. Timothy Liu Markus Schneider |
author_sort |
Shen-shyang Ho |
title |
A Framework for Moving Sensor Data Query and Retrieval of Dynamic Atmospheric Events |
title_short |
A Framework for Moving Sensor Data Query and Retrieval of Dynamic Atmospheric Events |
title_full |
A Framework for Moving Sensor Data Query and Retrieval of Dynamic Atmospheric Events |
title_fullStr |
A Framework for Moving Sensor Data Query and Retrieval of Dynamic Atmospheric Events |
title_full_unstemmed |
A Framework for Moving Sensor Data Query and Retrieval of Dynamic Atmospheric Events |
title_sort |
framework for moving sensor data query and retrieval of dynamic atmospheric events |
publisher |
Springer |
publishDate |
2010 |
url |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.190.500 http://www.cise.ufl.edu/%7Emschneid/Research/papers/HTLS10SSDBM.pdf |
long_lat |
ENVELOPE(161.983,161.983,-78.000,-78.000) |
geographic |
Handle The |
geographic_facet |
Handle The |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_source |
http://www.cise.ufl.edu/%7Emschneid/Research/papers/HTLS10SSDBM.pdf |
op_relation |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.190.500 http://www.cise.ufl.edu/%7Emschneid/Research/papers/HTLS10SSDBM.pdf |
op_rights |
Metadata may be used without restrictions as long as the oai identifier remains attached to it. |
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1766130409018490880 |