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Comparing salinity models in Whitewater Bay using remote sensing

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Date Issued:
2012
Summary:
This study compared models that used remote sensing to assess salinity in Whitewater Bay. The quantitative techniques in this research allow for a less costly and quicker assessment of salinity values. Field observations and Landsat 5 TM imagery from 2003-2006 were separated into wet and dry seasons and temporally matched. Interpolation models of Inverse Distance Weighting and Kriging were compared to empirical regression models (Ordinary Least Squares and Geographically Weighted Regression - GWR) via their Root Mean Square Error. The results showed that salinity analysis is more accurate in the dry season compared with the wet season. Univariate and multivariate analysis of the Landsat bands revealed the best band combination for salinity analysis in this local area. GWR is the most conducive model for estimating salinity because field observations are not required for future predictions once the local formula is established with available satellite imagery.
Title: Comparing salinity models in Whitewater Bay using remote sensing.
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Name(s): Selch, Donna
Charles E. Schmidt College of Science
Department of Geosciences
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Date Issued: 2012
Publisher: Florida Atlantic University
Physical Form: electronic
Extent: viii, 56 p. : ill. (some col.)
Language(s): English
Summary: This study compared models that used remote sensing to assess salinity in Whitewater Bay. The quantitative techniques in this research allow for a less costly and quicker assessment of salinity values. Field observations and Landsat 5 TM imagery from 2003-2006 were separated into wet and dry seasons and temporally matched. Interpolation models of Inverse Distance Weighting and Kriging were compared to empirical regression models (Ordinary Least Squares and Geographically Weighted Regression - GWR) via their Root Mean Square Error. The results showed that salinity analysis is more accurate in the dry season compared with the wet season. Univariate and multivariate analysis of the Landsat bands revealed the best band combination for salinity analysis in this local area. GWR is the most conducive model for estimating salinity because field observations are not required for future predictions once the local formula is established with available satellite imagery.
Identifier: 821618783 (oclc), 3356015 (digitool), FADT3356015 (IID), fau:3974 (fedora)
Note(s): by Donna Selch.
Thesis (M.A.)--Florida Atlantic University, 2012.
Includes bibliography.
Mode of access: World Wide Web.
System requirements: Adobe Reader.
Subject(s): Water quality -- Florida -- Whitewater Bay -- Measurement
Marine ecology -- Florida -- Whitewater Bay
Remote sensing
Electromagnetic interactions -- Water-supply -- Florida -- Whitewater Bay
Whitewater Bay (Fla.)
Persistent Link to This Record: http://purl.flvc.org/FAU/3356015
Use and Reproduction: http://rightsstatements.org/vocab/InC/1.0/
Owner Institution: FAU