Use of Monte Carlo simulation in remote sensing data analysis

Hamideh Ebrahimi, Shadi Aslebagh, Linwood Jones

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

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.

Original languageEnglish
Title of host publicationIEEE SoutheastCon 2013
Subtitle of host publicationMoving America into the Future
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781479900527
DOIs
StatePublished - 2013
EventIEEE SoutheastCon 2013: Moving America into the Future - Jacksonville, FL, United States
Duration: Apr 4 2013Apr 7 2013

Publication series

NameConference Proceedings - IEEE SOUTHEASTCON
ISSN (Print)1091-0050
ISSN (Electronic)1558-058X

Conference

ConferenceIEEE SoutheastCon 2013: Moving America into the Future
Country/TerritoryUnited States
CityJacksonville, FL
Period04/4/1304/7/13

Keywords

  • Monte Carlo simulation
  • Sea Surface Salinity
  • multilayer media effect
  • ocean brightness temperature

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