Pre-processing and classification of airborne hyperspectral data for wetlands mapping

The focus of this study is on information extraction from wetland areas using Pushbroom Hyperspectral Imager (PHI) data in Sungai Kisap, Langkawi. PHI data with high spatial and spectral resolution (2 m spatial and 5 nm spectral resolution) is very sensitive to variations in the reflectance of an ob...

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Main Author:	Lau, Alvin Meng Shin
Format:	Thesis
Language:	English
Published:	2004
Subjects:	TD Environmental technology Sanitary engineering
Online Access:	http://eprints.utm.my/id/eprint/4812/1/AlvinLauMengShinMFKSG2004.pdf
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id	my-utm-ep.4812
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spelling	my-utm-ep.48122018-02-28T06:47:51Z Pre-processing and classification of airborne hyperspectral data for wetlands mapping 2004-05 Lau, Alvin Meng Shin TD Environmental technology. Sanitary engineering The focus of this study is on information extraction from wetland areas using Pushbroom Hyperspectral Imager (PHI) data in Sungai Kisap, Langkawi. PHI data with high spatial and spectral resolution (2 m spatial and 5 nm spectral resolution) is very sensitive to variations in the reflectance of an object's surface. Therefore, hyperspectral data pre-processing (i.e. radiometric conection, geometric correction and data mosaicking, topographic normalization, data masking, spectral data reduction and spatial data reduction) were employed to ensure that data used for wetland information extraction are well corrected. To enable the feature extraction, two sets of spectral libraries (one for land cover classes and another for mangrove classes) were created fiom a field campaign. Feature d o n using a thresholding technique was employed to extract information fiom the PHI data. Two data classification techniques were also used, namely (1) Spectral Angle Mapper, and (2) Binary Encoding. Four land cover classes and four mangrove classes had been successfilly extracted Erom PHI data. A spectral Angle M' classified PHI image with spectral angle 0.3 radian gives the best classification result over 80 % of overall accuracy with Kappa Coefficient of 0.557. Other classifiers tested also give reasonable results (over 70% of overall accuracy). The final outputs of this study are a land cover map and a mangrove classes map of Sungai Kisap area. 2004-05 Thesis http://eprints.utm.my/id/eprint/4812/ http://eprints.utm.my/id/eprint/4812/1/AlvinLauMengShinMFKSG2004.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Geoinformation Science and Engineering Faculty of Geoinformation Science and Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TD Environmental technology Sanitary engineering
spellingShingle	TD Environmental technology Sanitary engineering Lau, Alvin Meng Shin Pre-processing and classification of airborne hyperspectral data for wetlands mapping
description	The focus of this study is on information extraction from wetland areas using Pushbroom Hyperspectral Imager (PHI) data in Sungai Kisap, Langkawi. PHI data with high spatial and spectral resolution (2 m spatial and 5 nm spectral resolution) is very sensitive to variations in the reflectance of an object's surface. Therefore, hyperspectral data pre-processing (i.e. radiometric conection, geometric correction and data mosaicking, topographic normalization, data masking, spectral data reduction and spatial data reduction) were employed to ensure that data used for wetland information extraction are well corrected. To enable the feature extraction, two sets of spectral libraries (one for land cover classes and another for mangrove classes) were created fiom a field campaign. Feature d o n using a thresholding technique was employed to extract information fiom the PHI data. Two data classification techniques were also used, namely (1) Spectral Angle Mapper, and (2) Binary Encoding. Four land cover classes and four mangrove classes had been successfilly extracted Erom PHI data. A spectral Angle M' classified PHI image with spectral angle 0.3 radian gives the best classification result over 80 % of overall accuracy with Kappa Coefficient of 0.557. Other classifiers tested also give reasonable results (over 70% of overall accuracy). The final outputs of this study are a land cover map and a mangrove classes map of Sungai Kisap area.
format	Thesis
qualification_level	Master's degree
author	Lau, Alvin Meng Shin
author_facet	Lau, Alvin Meng Shin
author_sort	Lau, Alvin Meng Shin
title	Pre-processing and classification of airborne hyperspectral data for wetlands mapping
title_short	Pre-processing and classification of airborne hyperspectral data for wetlands mapping
title_full	Pre-processing and classification of airborne hyperspectral data for wetlands mapping
title_fullStr	Pre-processing and classification of airborne hyperspectral data for wetlands mapping
title_full_unstemmed	Pre-processing and classification of airborne hyperspectral data for wetlands mapping
title_sort	pre-processing and classification of airborne hyperspectral data for wetlands mapping
granting_institution	Universiti Teknologi Malaysia, Faculty of Geoinformation Science and Engineering
granting_department	Faculty of Geoinformation Science and Engineering
publishDate	2004
url	http://eprints.utm.my/id/eprint/4812/1/AlvinLauMengShinMFKSG2004.pdf
_version_	1747814548802371584

Pre-processing and classification of airborne hyperspectral data for wetlands mapping

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