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Prediction of Total Suspended Sediments in Penang Waters Using Remote Sensing

Total suspended sediments (TSS) are one of the main causes of pollution in the country’s coastal areas. Land-based loaded and seabed resuspension are two main sources of TSS in coastal and estuary areas. In this study, remote sensing techniques were used to predict TSS concentrations. Landsat-5...

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Main Author: Tan, Sek Aun
Format: Thesis
Language:English
English
Published: 2004
Online Access:http://psasir.upm.edu.my/id/eprint/231/1/549517_FK_2004_77.pdf
http://psasir.upm.edu.my/id/eprint/231/
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spelling my.upm.eprints.2312013-05-27T06:46:47Z http://psasir.upm.edu.my/id/eprint/231/ Prediction of Total Suspended Sediments in Penang Waters Using Remote Sensing Tan, Sek Aun Total suspended sediments (TSS) are one of the main causes of pollution in the country’s coastal areas. Land-based loaded and seabed resuspension are two main sources of TSS in coastal and estuary areas. In this study, remote sensing techniques were used to predict TSS concentrations. Landsat-5 TM satellite imagery was used simultaneously with groundtruth data collected on 27th May 2000 in the Penang Straits. Various image processing steps such as geometric correction, radiometric correction and atmospheric correction were carried out in this study. Initially, digital number (DN) of imagery was corrected and converted into reflectance values for algorithm development. Subsequently combinations of various radiometric correction methods were used in this study to reduce the errors from various sources prior to statistical analysis. Data generated from corrected satellite imagery and TSS concentrations measured from field sampling were compared and tested using statistical analysis. Only the best-fit algorithm developed in this study was selected to predict the TSS concentrations from satellite imagery. Out of the six algorithms derived, Algorithm 6 showed the best correlation with the ground-truth data (R2 value of 0.9755 and RMSE value of 4.0107). The developed algorithm was then applied to predict the TSS concentrations on historical Landsat imagery acquired on 1st February 1993. The historical satellite image was normalized and converted to reflectance for the biophysical study. Besides the derived algorithm, models suggested by other researchers were tested in this study. However, the Algorithm 6 showed the best results in predicting TSS concentration for the Penang waters. The predicted TSS concentrations distribution maps were generated and compared with the GIS platform. 2004-07 Thesis NonPeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/231/1/549517_FK_2004_77.pdf Tan, Sek Aun (2004) Prediction of Total Suspended Sediments in Penang Waters Using Remote Sensing. Masters thesis, Universiti Putra Malaysia. English
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
English
description Total suspended sediments (TSS) are one of the main causes of pollution in the country’s coastal areas. Land-based loaded and seabed resuspension are two main sources of TSS in coastal and estuary areas. In this study, remote sensing techniques were used to predict TSS concentrations. Landsat-5 TM satellite imagery was used simultaneously with groundtruth data collected on 27th May 2000 in the Penang Straits. Various image processing steps such as geometric correction, radiometric correction and atmospheric correction were carried out in this study. Initially, digital number (DN) of imagery was corrected and converted into reflectance values for algorithm development. Subsequently combinations of various radiometric correction methods were used in this study to reduce the errors from various sources prior to statistical analysis. Data generated from corrected satellite imagery and TSS concentrations measured from field sampling were compared and tested using statistical analysis. Only the best-fit algorithm developed in this study was selected to predict the TSS concentrations from satellite imagery. Out of the six algorithms derived, Algorithm 6 showed the best correlation with the ground-truth data (R2 value of 0.9755 and RMSE value of 4.0107). The developed algorithm was then applied to predict the TSS concentrations on historical Landsat imagery acquired on 1st February 1993. The historical satellite image was normalized and converted to reflectance for the biophysical study. Besides the derived algorithm, models suggested by other researchers were tested in this study. However, the Algorithm 6 showed the best results in predicting TSS concentration for the Penang waters. The predicted TSS concentrations distribution maps were generated and compared with the GIS platform.
format Thesis
author Tan, Sek Aun
spellingShingle Tan, Sek Aun
Prediction of Total Suspended Sediments in Penang Waters Using Remote Sensing
author_facet Tan, Sek Aun
author_sort Tan, Sek Aun
title Prediction of Total Suspended Sediments in Penang Waters Using Remote Sensing
title_short Prediction of Total Suspended Sediments in Penang Waters Using Remote Sensing
title_full Prediction of Total Suspended Sediments in Penang Waters Using Remote Sensing
title_fullStr Prediction of Total Suspended Sediments in Penang Waters Using Remote Sensing
title_full_unstemmed Prediction of Total Suspended Sediments in Penang Waters Using Remote Sensing
title_sort prediction of total suspended sediments in penang waters using remote sensing
publishDate 2004
url http://psasir.upm.edu.my/id/eprint/231/1/549517_FK_2004_77.pdf
http://psasir.upm.edu.my/id/eprint/231/
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score 13.211869

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