A Framework for Moving Sensor Data Query and Retrieval of Dynamic Atmospheric Events

机译：动态大气事件的移动传感器数据查询和检索框架

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摘要

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.

机译：地球科学研究的挑战之一是基于用户定义的标准来准确，高效地进行查询和检索地球科学卫星传感器数据，以研究和分析诸如热带气旋的大气事件。可以将问题表达为时空联接查询，以识别运动传感器对象和动态大气事件对象精确相交或在用户定义的接近范围内相交的时空位置。在本文中，我们描述了一种有效的查询和检索框架，以解决为卫星传感器数据检索识别时空相交位置的问题。我们使用QuikSCAT（风场测量）和TRMM（降水垂直剖面测量）卫星的传感器测量以及2009年在北大西洋发生的热带气旋的轨迹来证明我们提出的框架的有效性。

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《Scientific and statistical database management》|2010年|p.96-113|共18页
会议地点 Heidelberg(DE);Heidelberg(DE)
作者
Shen-Shyang Ho; Wenqing Tang; W. Timothy Liu; Markus Schneider;
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作者单位

Jet Propulsion Laboratory, California Institute of Technology, Pasadena CA 91109, USA;

Jet Propulsion Laboratory, California Institute of Technology, Pasadena CA 91109, USA;

Jet Propulsion Laboratory, California Institute of Technology, Pasadena CA 91109, USA;

Department of Computer Information Science Engineering, University of Florida, Gainesville, FL 32611, USA;

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原文格式 PDF
正文语种 eng
中图分类 TP311.13;
关键词
data retrieval; satellite data; atmospheric events; spatio- temporal join;

机译：数据检索；卫星数据；大气事件；时空联接;

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专利

1. Querying moving events in wireless sensor networks [J] . Amato Giuseppe, Chessa Stefano, Gennaro Claudio, Pervasive and Mobile Computing . 2015,第Pta1期

机译：查询无线传感器网络中的移动事件
2. SeaCloudDM: a database cluster framework for managing and querying massive heterogeneous sensor sampling data [J] . Zhiming Ding, Jiajie Xu, Qi Yang Journal of supercomputing . 2013,第3期

机译：SeaCloudDM：一个数据库集群框架，用于管理和查询大量的异构传感器采样数据
3. Enhanced Energy in Sensors by Avoiding Voids and Saving Sensitive Data on Cloud Using B+ Tree Index with Retrieval of Query Predicates [J] . Geetha S., Deepalakshmi P. Mobile networks & applications . 2019,第1期

机译：通过使用查询查询谓词的B +树索引避免虚空并在云上保存敏感数据来增强传感器的能量
4. A Framework for Moving Sensor Data Query and Retrieval of Dynamic Atmospheric Events [C] . Shen-Shyang Ho, Wenqing Tang, W. Timothy Liu, International Conference on Scientific and Statistical Database Management . 2010

机译：移动传感器数据查询和检索动态大气事件的框架
5. Use of the Global Environmental Multiscale model for atmospheric retrieval from radio occultation for Canadian events [D] . de Groot, Lance 2008

机译：使用全球环境多尺度模型从加拿大活动的无线电掩星中获取大气
6. On-Demand Information Retrieval in Sensor Networks with Localised Query and Energy-Balanced Data Collection [O] . Rui Teng, Bing Zhang 2011

机译：具有本地化查询和能量平衡数据收集的传感器网络中的按需信息检索
7. A Framework for Moving Sensor Data Query and Retrieval of Dynamic Atmospheric Events [O] . Shen-shyang Ho, Wenqing Tang, W. Timothy Liu, 2010

机译：移动传感器数据查询和动态大气事件检索框架

A Framework for Moving Sensor Data Query and Retrieval of Dynamic Atmospheric Events

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