Title
Use Of Monte Carlo Simulation In Remote Sensing Data Analysis
Keywords
Monte Carlo simulation; multilayer media effect; ocean brightness temperature; Sea Surface Salinity
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. © 2013 IEEE.
Publication Date
9-4-2013
Publication Title
Conference Proceedings - IEEE SOUTHEASTCON
Number of Pages
-
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/SECON.2013.6567506
Copyright Status
Unknown
Socpus ID
84883215745 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84883215745
STARS Citation
Ebrahimi, Hamideh; Aslebagh, Shadi; and Jones, Linwood, "Use Of Monte Carlo Simulation In Remote Sensing Data Analysis" (2013). Scopus Export 2010-2014. 6215.
https://stars.library.ucf.edu/scopus2010/6215