Fire severity and post-fire generation using : Landsat [NDVI], [NBR] and [SAVI] / Nur Izzaty Dali

Regrowth of vegetation is important to maintain ecosystems. With remote sensing technology, regrowth of vegetation due to fire severity can be predicted. The aim of this study is to determine the changes of forest distribution due to forest fire episodes between 2013 until 2015 using Normalized Diff...

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Main Author:	Dali, Nur Izzaty
Format:	Thesis
Language:	English
Published:	2018
Subjects:	Plant ecology Environmental aspects of forestry Remote sensing
Online Access:	https://ir.uitm.edu.my/id/eprint/21775/1/TD_NUR%20IZZATY%20DALI%20AP%20R%2018_5.pdf
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spelling	my-uitm-ir.217752018-10-11T07:52:15Z Fire severity and post-fire generation using : Landsat [NDVI], [NBR] and [SAVI] / Nur Izzaty Dali 2018-10-05 Dali, Nur Izzaty Plant ecology Environmental aspects of forestry Remote sensing Regrowth of vegetation is important to maintain ecosystems. With remote sensing technology, regrowth of vegetation due to fire severity can be predicted. The aim of this study is to determine the changes of forest distribution due to forest fire episodes between 2013 until 2015 using Normalized Difference Vegetation Index (NDVI), Normalized Burn Ratio (NBR) and Soil Adjusted Vegetation Index (SAVI) of Landsat images at Chuping, Perlis. Pre-fire and post-fire of Landsat 7 ETM+ images were obtained to identify the fire severity using Normalized Burn Ratio algorithms. The objectives of this study are (1) to produce Normalized Difference Vegetation Index (NDVI), Normalized Burn Ratio (NBR), and Soil Adjusted Vegetation Index (SAVI) and (2) to determine the changes of forest distribution based on NDVI, NBR and SAVI changes. The results show the changes of forest distribution based on NDVI, NBR and SAVI. The result of percentage of NDVI area for pre-fire and post-fire in 2013 until 2015 the dense vegetation more decreasing number of vegetation in that area it show based on percentage of pre-fire more than from result of post-fire. After that that, the percentage of NBR for pre-fire and post-fire is moderate high severity burn show the more increase value of percentage for post-fire result. Percentage of SAVI for pre-fire and post-fire is more decreasing value of percentage for high cover green vegetation from 2013 until 2015. The result show of difference NDVI, NBR and SAVI changes is increasing value from 2013 until 2015. The result for Normalized Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) were used to determine vegetation generation between years 2013 to 2015. Result showed that NDVI and SAVI values distinctly declined post-fire and began to increase in the coming years. Mean NDVI value of burned area changes from 0.12 to 0.01 due to forest fire, mean SAVI value changed from 0.13 to 0.02. Regrowth rates calculated for NDVI and SAVI 70% and 73% respectively. Based on that result the study is identify for fire severity and vegetation generation in forest fire management systems. 2018-10 Thesis https://ir.uitm.edu.my/id/eprint/21775/ https://ir.uitm.edu.my/id/eprint/21775/1/TD_NUR%20IZZATY%20DALI%20AP%20R%2018_5.pdf text en public degree Universiti Teknologi Mara Perlis Faculty of Architecture, Planning and Surveying
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
topic	Plant ecology Environmental aspects of forestry Remote sensing
spellingShingle	Plant ecology Environmental aspects of forestry Remote sensing Dali, Nur Izzaty Fire severity and post-fire generation using : Landsat [NDVI], [NBR] and [SAVI] / Nur Izzaty Dali
description	Regrowth of vegetation is important to maintain ecosystems. With remote sensing technology, regrowth of vegetation due to fire severity can be predicted. The aim of this study is to determine the changes of forest distribution due to forest fire episodes between 2013 until 2015 using Normalized Difference Vegetation Index (NDVI), Normalized Burn Ratio (NBR) and Soil Adjusted Vegetation Index (SAVI) of Landsat images at Chuping, Perlis. Pre-fire and post-fire of Landsat 7 ETM+ images were obtained to identify the fire severity using Normalized Burn Ratio algorithms. The objectives of this study are (1) to produce Normalized Difference Vegetation Index (NDVI), Normalized Burn Ratio (NBR), and Soil Adjusted Vegetation Index (SAVI) and (2) to determine the changes of forest distribution based on NDVI, NBR and SAVI changes. The results show the changes of forest distribution based on NDVI, NBR and SAVI. The result of percentage of NDVI area for pre-fire and post-fire in 2013 until 2015 the dense vegetation more decreasing number of vegetation in that area it show based on percentage of pre-fire more than from result of post-fire. After that that, the percentage of NBR for pre-fire and post-fire is moderate high severity burn show the more increase value of percentage for post-fire result. Percentage of SAVI for pre-fire and post-fire is more decreasing value of percentage for high cover green vegetation from 2013 until 2015. The result show of difference NDVI, NBR and SAVI changes is increasing value from 2013 until 2015. The result for Normalized Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) were used to determine vegetation generation between years 2013 to 2015. Result showed that NDVI and SAVI values distinctly declined post-fire and began to increase in the coming years. Mean NDVI value of burned area changes from 0.12 to 0.01 due to forest fire, mean SAVI value changed from 0.13 to 0.02. Regrowth rates calculated for NDVI and SAVI 70% and 73% respectively. Based on that result the study is identify for fire severity and vegetation generation in forest fire management systems.
format	Thesis
qualification_level	Bachelor degree
author	Dali, Nur Izzaty
author_facet	Dali, Nur Izzaty
author_sort	Dali, Nur Izzaty
title	Fire severity and post-fire generation using : Landsat [NDVI], [NBR] and [SAVI] / Nur Izzaty Dali
title_short	Fire severity and post-fire generation using : Landsat [NDVI], [NBR] and [SAVI] / Nur Izzaty Dali
title_full	Fire severity and post-fire generation using : Landsat [NDVI], [NBR] and [SAVI] / Nur Izzaty Dali
title_fullStr	Fire severity and post-fire generation using : Landsat [NDVI], [NBR] and [SAVI] / Nur Izzaty Dali
title_full_unstemmed	Fire severity and post-fire generation using : Landsat [NDVI], [NBR] and [SAVI] / Nur Izzaty Dali
title_sort	fire severity and post-fire generation using : landsat [ndvi], [nbr] and [savi] / nur izzaty dali
granting_institution	Universiti Teknologi Mara Perlis
granting_department	Faculty of Architecture, Planning and Surveying
publishDate	2018
url	https://ir.uitm.edu.my/id/eprint/21775/1/TD_NUR%20IZZATY%20DALI%20AP%20R%2018_5.pdf
_version_	1783733772940738560

Fire severity and post-fire generation using : Landsat [NDVI], [NBR] and [SAVI] / Nur Izzaty Dali

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