Title :
Use of Monte Carlo simulation in remote sensing data analysis
Author :
Ebrahimi, Hamideh ; Aslebagh, Shadi ; Jones, Lewis
Author_Institution :
Dept. of EECS, Univ. of Central Florida, Orlando, FL, USA
Abstract :
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.
Keywords :
Monte Carlo methods; brightness; climatology; data analysis; error analysis; ocean temperature; oceanographic techniques; radiometers; random processes; remote sensing; AD 2011; Aquarius earth science satellite; L-band brightness temperature; L-band microwave radiometer; L-band microwave scatterometer; Monte Carlo simulation; SSS measurement; SSS microwave remote sensing; SSS retrieval; earth water cycle; error sources; global climate change; oceanic parameter; rainfall; rainfall effects; random processes theory; remote sensing data analysis; sea surface salinity; Brightness temperature; Ocean temperature; Rain; Sea measurements; Sea surface; Temperature measurement; Monte Carlo simulation; Sea Surface Salinity; multilayer media effect; ocean brightness temperature;
Conference_Titel :
Southeastcon, 2013 Proceedings of IEEE
Conference_Location :
Jacksonville, FL
Print_ISBN :
978-1-4799-0052-7
DOI :
10.1109/SECON.2013.6567506
