Comparison of supervised classification technique of landuse map using high resolution image / Muhammad Firdaus Mohammad Harun

The land cover relate with physical feature of land surface. Land cover can be categories such as development area, vegetation areas, rural area, urban area and anything rely on the land surface. Remote sensing have been used to detect the changes of the land covers occurs by human activity. In t...

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主要作者: Mohammad Harun, Muhammad Firdaus
格式: Thesis
語言:English
出版: 2019
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在線閱讀:https://ir.uitm.edu.my/id/eprint/22690/1/TD_MUHAMMAD%20FIRDAUS%20MOHAMMAD%20HARUN%20AP%20R%2019.5.PDF
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spelling my-uitm-ir.226902019-01-11T01:49:39Z Comparison of supervised classification technique of landuse map using high resolution image / Muhammad Firdaus Mohammad Harun 2019-01-09 Mohammad Harun, Muhammad Firdaus Remote Sensing Map drawing, modeling, printing, reading, etc Algorithms The land cover relate with physical feature of land surface. Land cover can be categories such as development area, vegetation areas, rural area, urban area and anything rely on the land surface. Remote sensing have been used to detect the changes of the land covers occurs by human activity. In this project, the objective is to generate supervised classification SPOT 7, to determine the accuracy of classification using maximum likelihood, minimum distance, mahalanobis distance and spectral angle algorithm and to produce the land use map. The algorithm were used to perform the supervised classification. The landuse were classified into six classes i.e. shrub, forest, paddy, cropland, build up and water. The accuracy assessment using error matrix method were done. A total of sixty (60) ground data were used to validate the accuracy of the classification. The result shows that maximum likelihood algorithm has the highest value for overall accuracy and overall kappa statistic which is 87% and 84% respectively. The lowest value shows by minimum distance algorithm is 68% and 61% respectively. 2019-01 Thesis https://ir.uitm.edu.my/id/eprint/22690/ https://ir.uitm.edu.my/id/eprint/22690/1/TD_MUHAMMAD%20FIRDAUS%20MOHAMMAD%20HARUN%20AP%20R%2019.5.PDF other en public degree Universiti Teknologi Mara Perlis Faculty of Architecture, Planning and Surveying
institution Universiti Teknologi MARA
collection UiTM Institutional Repository
language English
topic Remote Sensing
Remote Sensing
Algorithms
spellingShingle Remote Sensing
Remote Sensing
Algorithms
Mohammad Harun, Muhammad Firdaus
Comparison of supervised classification technique of landuse map using high resolution image / Muhammad Firdaus Mohammad Harun
description The land cover relate with physical feature of land surface. Land cover can be categories such as development area, vegetation areas, rural area, urban area and anything rely on the land surface. Remote sensing have been used to detect the changes of the land covers occurs by human activity. In this project, the objective is to generate supervised classification SPOT 7, to determine the accuracy of classification using maximum likelihood, minimum distance, mahalanobis distance and spectral angle algorithm and to produce the land use map. The algorithm were used to perform the supervised classification. The landuse were classified into six classes i.e. shrub, forest, paddy, cropland, build up and water. The accuracy assessment using error matrix method were done. A total of sixty (60) ground data were used to validate the accuracy of the classification. The result shows that maximum likelihood algorithm has the highest value for overall accuracy and overall kappa statistic which is 87% and 84% respectively. The lowest value shows by minimum distance algorithm is 68% and 61% respectively.
format Thesis
qualification_level Bachelor degree
author Mohammad Harun, Muhammad Firdaus
author_facet Mohammad Harun, Muhammad Firdaus
author_sort Mohammad Harun, Muhammad Firdaus
title Comparison of supervised classification technique of landuse map using high resolution image / Muhammad Firdaus Mohammad Harun
title_short Comparison of supervised classification technique of landuse map using high resolution image / Muhammad Firdaus Mohammad Harun
title_full Comparison of supervised classification technique of landuse map using high resolution image / Muhammad Firdaus Mohammad Harun
title_fullStr Comparison of supervised classification technique of landuse map using high resolution image / Muhammad Firdaus Mohammad Harun
title_full_unstemmed Comparison of supervised classification technique of landuse map using high resolution image / Muhammad Firdaus Mohammad Harun
title_sort comparison of supervised classification technique of landuse map using high resolution image / muhammad firdaus mohammad harun
granting_institution Universiti Teknologi Mara Perlis
granting_department Faculty of Architecture, Planning and Surveying
publishDate 2019
url https://ir.uitm.edu.my/id/eprint/22690/1/TD_MUHAMMAD%20FIRDAUS%20MOHAMMAD%20HARUN%20AP%20R%2019.5.PDF
_version_ 1783733824082935808