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The use of remote sensing in freshwa...
~
Nelson, Stacy Arnold Charles.
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The use of remote sensing in freshwater wetland and lake studies.
Record Type:
Language materials, printed : Monograph/item
Title/Author:
The use of remote sensing in freshwater wetland and lake studies./
Author:
Nelson, Stacy Arnold Charles.
Description:
134 p.
Notes:
Adviser: Patricia A. Soranno.
Contained By:
Dissertation Abstracts International63-12B.
Subject:
Biology, Ecology. -
Online resource:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3075053
ISBN:
0493952136
The use of remote sensing in freshwater wetland and lake studies.
Nelson, Stacy Arnold Charles.
The use of remote sensing in freshwater wetland and lake studies.
- 134 p.
Adviser: Patricia A. Soranno.
Thesis (Ph.D.)--Michigan State University, 2002.
The Barataria Basin, Louisiana, is an extensive wetland and coastal estuary system of great economic and intrinsic value that has experienced high rates of coastal land loss. However, little information exists on whether freshwater wetlands in the upper basin have changed. My objectives in chapter 1 were to: (1) quantify land cover change in the upper basin over twenty years from 1972–1992; and to (2) determine land cover transition rates among land cover types. Using 80-m resolution Landsat MSS data, I found significant changes in land cover occurred within the upper Barataria Basin over the study period with a 21% increase in total wetland area. If present trends in total wetland area continue, bottomland hardwood forests may be eliminated by the year 2025. In Chapter 2, I examined whether Landsat-7 ETM+ could be used to measure water clarity across a large range of lakes. My objectives were to: (1) develop a model to estimate lake water clarity from Landsat data calibrated on 93 lakes in Michigan, and to (2) examine how the distribution of water clarity across the 93 lakes influences the model. My regression model resulted in a much lower r<super>2</super> value than previously published studies. So, to examine the role of the distribution of calibration lake water clarity data to the model, I simulated a calibration dataset with a different water clarity distribution by sub-sampling the original dataset. The subsampled dataset had a much higher percentage of lakes with shallow water clarity. The regression model for the subsampled dataset resulted in a much higher r<super>2</super> value. My results show that the use of Landsat to measure water clarity is sensitive to the distribution of water clarity used in the calibrated dataset. In Chapter 3, I examine the use of Landsat-5 to monitor macrophytes in inland lakes. My objectives were to: (1) determine if different aquatic plant cover types could be detected using Landsat-5; and to (2) determine if I could improve predictions of macrophytes in lakes by including lake characteristics in the models. Using logistic regression models, I found statistically significant relationships between most macrophyte measures in 12 calibration lakes and Landsat-5 spectral values. However, using another lake to validate the model resulted in poor model validation. Thus, it is still unclear exactly how useful Landsat data is for monitoring aquatic plants. Remote sensing provides an effecting monitoring tool for large area studies in historical wetland change. (Abstract shortened by UMI.)
ISBN: 0493952136Subjects--Topical Terms:
1017726
Biology, Ecology.
The use of remote sensing in freshwater wetland and lake studies.
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Thesis (Ph.D.)--Michigan State University, 2002.
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The Barataria Basin, Louisiana, is an extensive wetland and coastal estuary system of great economic and intrinsic value that has experienced high rates of coastal land loss. However, little information exists on whether freshwater wetlands in the upper basin have changed. My objectives in chapter 1 were to: (1) quantify land cover change in the upper basin over twenty years from 1972–1992; and to (2) determine land cover transition rates among land cover types. Using 80-m resolution Landsat MSS data, I found significant changes in land cover occurred within the upper Barataria Basin over the study period with a 21% increase in total wetland area. If present trends in total wetland area continue, bottomland hardwood forests may be eliminated by the year 2025. In Chapter 2, I examined whether Landsat-7 ETM+ could be used to measure water clarity across a large range of lakes. My objectives were to: (1) develop a model to estimate lake water clarity from Landsat data calibrated on 93 lakes in Michigan, and to (2) examine how the distribution of water clarity across the 93 lakes influences the model. My regression model resulted in a much lower r<super>2</super> value than previously published studies. So, to examine the role of the distribution of calibration lake water clarity data to the model, I simulated a calibration dataset with a different water clarity distribution by sub-sampling the original dataset. The subsampled dataset had a much higher percentage of lakes with shallow water clarity. The regression model for the subsampled dataset resulted in a much higher r<super>2</super> value. My results show that the use of Landsat to measure water clarity is sensitive to the distribution of water clarity used in the calibrated dataset. In Chapter 3, I examine the use of Landsat-5 to monitor macrophytes in inland lakes. My objectives were to: (1) determine if different aquatic plant cover types could be detected using Landsat-5; and to (2) determine if I could improve predictions of macrophytes in lakes by including lake characteristics in the models. Using logistic regression models, I found statistically significant relationships between most macrophyte measures in 12 calibration lakes and Landsat-5 spectral values. However, using another lake to validate the model resulted in poor model validation. Thus, it is still unclear exactly how useful Landsat data is for monitoring aquatic plants. Remote sensing provides an effecting monitoring tool for large area studies in historical wetland change. (Abstract shortened by UMI.)
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3075053
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