Use of Monte Carlo Simulation in Remote Sensing Data Analysis

被引：0
|
作者：
Ebrahimi, Hamideh [1 ]
Aslebagh, Shadi [1 ]
Jones, Linwood [1 ]
机构：
[1] Univ Cent Florida, Dept EECS, Cent Florida Remote Sensing Lab, Orlando, FL 32816 USA
来源：
2013 PROCEEDINGS OF IEEE SOUTHEASTCON | 2013年
关键词：
Monte Carlo simulation; Sea Surface Salinity; multilayer media effect; ocean brightness temperature;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In the summer of 2011, the Aquarius earth science satellite was launched to measure Sea Surface Salinity (SSS) using a L-band microwave radiometer/scatterometer. This is an important oceanic parameter for monitoring the earth's water cycle over oceans and for modeling global climate change. The microwave remote sensing of SSS is a challenging objective. The SSS signal is weak and there are many interfering error sources that must be corrected to achieve an accurate SSS measurement. This paper deals with the use of random processes theory for assessing the effects of rainfall on the retrieved SSS. In this paper we use the Monte Carlo method that is one of the best methods for analysis of random processes, to investigate the multilayer effect caused by rainfall on the L-band brightness temperature and the resulting SSS retrieval.
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页数：4
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