Land use changes detection using supervised classfication and post classfication method / Nur Liyana Yusof
The purpose of this study was to examine the land use land cover in Klang Selangor by using supervised classification and post classification method. The comparison of time series data between year 2005 to 2010 and 2010 to 2016 have been carried out to identify the changes of land use land cover. Th...
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my-uitm-ir.216882018-09-25T05:11:42Z Land use changes detection using supervised classfication and post classfication method / Nur Liyana Yusof 2018-09-25 Yusof, Nur Liyana Land use Remote sensing The purpose of this study was to examine the land use land cover in Klang Selangor by using supervised classification and post classification method. The comparison of time series data between year 2005 to 2010 and 2010 to 2016 have been carried out to identify the changes of land use land cover. The data use in this study were Landsat Satellite Imagery (TM and Oli-Tirs). Land use have been divided into five main categories representing water body, forest, agriculture, bare soil and built area. The classification of land use land cover using method supervised classification and post classification then make comparison using both method. After that, the relationship between land use land cover with land surface temperature was derived from linear correlation coefficient. Calculate land surface temperature from satellite imagery using a formula. Comparison data from Development Rural and Urban (JPBD) with the data derived from satellite imagery. 2018-09 Thesis https://ir.uitm.edu.my/id/eprint/21688/ https://ir.uitm.edu.my/id/eprint/21688/1/TD_NUR%20LIYANA%20YUSOF%20AP%20R%2018_5.pdf text en public degree Universiti Teknologi Mara Perlis Faculty of architecture, planning and surveying |
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Universiti Teknologi MARA |
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Land use Remote sensing |
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Land use Remote sensing Yusof, Nur Liyana Land use changes detection using supervised classfication and post classfication method / Nur Liyana Yusof |
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The purpose of this study was to examine the land use land cover in Klang Selangor by using supervised classification and post classification method. The comparison of time series data between year 2005 to 2010 and 2010 to 2016 have been carried out to identify the changes of land use land cover. The data use in this study were Landsat Satellite Imagery (TM and Oli-Tirs). Land use have been divided into five main categories representing water body, forest, agriculture, bare soil and built area. The classification of land use land cover using method supervised classification and post classification then make comparison using both method. After that, the relationship between land use land cover with land surface temperature was derived from linear correlation coefficient. Calculate land surface temperature from satellite imagery using a formula. Comparison data from Development Rural and Urban (JPBD) with the data derived from satellite imagery. |
format |
Thesis |
qualification_level |
Bachelor degree |
author |
Yusof, Nur Liyana |
author_facet |
Yusof, Nur Liyana |
author_sort |
Yusof, Nur Liyana |
title |
Land use changes detection using supervised classfication and post classfication method / Nur Liyana Yusof |
title_short |
Land use changes detection using supervised classfication and post classfication method / Nur Liyana Yusof |
title_full |
Land use changes detection using supervised classfication and post classfication method / Nur Liyana Yusof |
title_fullStr |
Land use changes detection using supervised classfication and post classfication method / Nur Liyana Yusof |
title_full_unstemmed |
Land use changes detection using supervised classfication and post classfication method / Nur Liyana Yusof |
title_sort |
land use changes detection using supervised classfication and post classfication method / nur liyana yusof |
granting_institution |
Universiti Teknologi Mara Perlis |
granting_department |
Faculty of architecture, planning and surveying |
publishDate |
2018 |
url |
https://ir.uitm.edu.my/id/eprint/21688/1/TD_NUR%20LIYANA%20YUSOF%20AP%20R%2018_5.pdf |
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1783733770944249856 |