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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| Format: | Thesis |
| Language: | English |
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2018
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| Online Access: | https://ir.uitm.edu.my/id/eprint/21775/1/TD_NUR%20IZZATY%20DALI%20AP%20R%2018_5.pdf |
| _version_ | 1825735630995324928 |
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| author | Dali, Nur Izzaty |
| author_facet | Dali, Nur Izzaty |
| author_sort | Dali, Nur Izzaty |
| collection | UITM |
| 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. |
| first_indexed | 2024-03-06T01:49:58Z |
| format | Thesis |
| id | uitm.eprints-1775 |
| institution | Universiti Teknologi MARA |
| language | English |
| last_indexed | 2024-03-06T01:49:58Z |
| publishDate | 2018 |
| record_format | dspace |
| spelling | uitm.eprints-17752018-10-11T07:52:15Z https://ir.uitm.edu.my/id/eprint/21775/ Fire severity and post-fire generation using : Landsat [NDVI], [NBR] and [SAVI] / Nur Izzaty Dali 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. 2018-10-05 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/21775/1/TD_NUR%20IZZATY%20DALI%20AP%20R%2018_5.pdf Fire severity and post-fire generation using : Landsat [NDVI], [NBR] and [SAVI] / Nur Izzaty Dali. (2018) Degree thesis, thesis, Universiti Teknologi Mara Perlis. |
| 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 |
| title | 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_short | 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 |
| topic | Plant ecology Environmental aspects of forestry Remote sensing |
| url | https://ir.uitm.edu.my/id/eprint/21775/1/TD_NUR%20IZZATY%20DALI%20AP%20R%2018_5.pdf |
| work_keys_str_mv | AT dalinurizzaty fireseverityandpostfiregenerationusinglandsatndvinbrandsavinurizzatydali |