Burn severity evaluation in black pine forests with topographical factors using Sentinel-2 in Kastamonu, Türkiye
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Cerne (Online) |
Texto Completo: | https://cerne.ufla.br/site/index.php/CERNE/article/view/3230 |
Resumo: | Backgroud: Forest fires are one of the most important natural disasters all over the world in terms of the damage they cause to the ecosystem. It is observed that there is a significant increase in the number of forest fires in Türkiye and in the world. This situation jeopardizes the sustainability of forests. It is very important to estimate fire behavior characteristics in order to take pre-fire measures and to take effective interventions in the event of a fire. Obtaining data based on terrestrial measurements to predict fire behavior is both very expensive and very time consuming. At this point, the use of remote sensing technologies is very useful. In this respect, using satellite images to determine the areas destroyed by fire and their burning severity will be faster, more sensitive and economical in terms of fire fighting and precautions to be taken. Results: In this study, the forest fire that occurred in Kastamonu-Taşköprü district was analyzed with remote sensing techniques. First of all, pre-fire and post-fire Sentinel-2 images of fire areas were used to determine the burned area using NBR (Normalized Burn Ratio) and dNBR (Differenced Normalized Burn Ratio) indices. Also, burned area rate and burn severity were evaluated the depending on the altitude, aspect and slope factors. Conclusion: We found that almost 1504.9 ha forest land burned in the study site. Topographical maps showed that the most burned areas were covered by moderate- and high- severity classes. The forest fire was more severe in the altitude range from 1170 to 1370m, at 20-33% slope and northerly aspects in our study site. |
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Burn severity evaluation in black pine forests with topographical factors using Sentinel-2 in Kastamonu, TürkiyeForest fire, Sentinel-2, Burn severity, Topographic factors, Black pine forestsBackgroud: Forest fires are one of the most important natural disasters all over the world in terms of the damage they cause to the ecosystem. It is observed that there is a significant increase in the number of forest fires in Türkiye and in the world. This situation jeopardizes the sustainability of forests. It is very important to estimate fire behavior characteristics in order to take pre-fire measures and to take effective interventions in the event of a fire. Obtaining data based on terrestrial measurements to predict fire behavior is both very expensive and very time consuming. At this point, the use of remote sensing technologies is very useful. In this respect, using satellite images to determine the areas destroyed by fire and their burning severity will be faster, more sensitive and economical in terms of fire fighting and precautions to be taken. Results: In this study, the forest fire that occurred in Kastamonu-Taşköprü district was analyzed with remote sensing techniques. First of all, pre-fire and post-fire Sentinel-2 images of fire areas were used to determine the burned area using NBR (Normalized Burn Ratio) and dNBR (Differenced Normalized Burn Ratio) indices. Also, burned area rate and burn severity were evaluated the depending on the altitude, aspect and slope factors. Conclusion: We found that almost 1504.9 ha forest land burned in the study site. Topographical maps showed that the most burned areas were covered by moderate- and high- severity classes. The forest fire was more severe in the altitude range from 1170 to 1370m, at 20-33% slope and northerly aspects in our study site.CERNECERNE2023-06-21info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://cerne.ufla.br/site/index.php/CERNE/article/view/3230CERNE; Vol. 29 No. 1 (2023); e-103230CERNE; v. 29 n. 1 (2023); e-1032302317-63420104-7760reponame:Cerne (Online)instname:Universidade Federal de Lavras (UFLA)instacron:UFLAenghttps://cerne.ufla.br/site/index.php/CERNE/article/view/3230/1344http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessÖZER GENÇ, CigdemKÜÇÜK, ÖmerÖZDEN KELEŞ, SerayÜNAL, Sabri2023-06-21T12:42:54Zoai:cerne.ufla.br:article/3230Revistahttps://cerne.ufla.br/site/index.php/CERNEPUBhttps://cerne.ufla.br/site/index.php/CERNE/oaicerne@dcf.ufla.br||cerne@dcf.ufla.br2317-63420104-7760opendoar:2023-06-21T12:42:54Cerne (Online) - Universidade Federal de Lavras (UFLA)false |
dc.title.none.fl_str_mv |
Burn severity evaluation in black pine forests with topographical factors using Sentinel-2 in Kastamonu, Türkiye |
title |
Burn severity evaluation in black pine forests with topographical factors using Sentinel-2 in Kastamonu, Türkiye |
spellingShingle |
Burn severity evaluation in black pine forests with topographical factors using Sentinel-2 in Kastamonu, Türkiye ÖZER GENÇ, Cigdem Forest fire, Sentinel-2, Burn severity, Topographic factors, Black pine forests |
title_short |
Burn severity evaluation in black pine forests with topographical factors using Sentinel-2 in Kastamonu, Türkiye |
title_full |
Burn severity evaluation in black pine forests with topographical factors using Sentinel-2 in Kastamonu, Türkiye |
title_fullStr |
Burn severity evaluation in black pine forests with topographical factors using Sentinel-2 in Kastamonu, Türkiye |
title_full_unstemmed |
Burn severity evaluation in black pine forests with topographical factors using Sentinel-2 in Kastamonu, Türkiye |
title_sort |
Burn severity evaluation in black pine forests with topographical factors using Sentinel-2 in Kastamonu, Türkiye |
author |
ÖZER GENÇ, Cigdem |
author_facet |
ÖZER GENÇ, Cigdem KÜÇÜK, Ömer ÖZDEN KELEŞ, Seray ÜNAL, Sabri |
author_role |
author |
author2 |
KÜÇÜK, Ömer ÖZDEN KELEŞ, Seray ÜNAL, Sabri |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
ÖZER GENÇ, Cigdem KÜÇÜK, Ömer ÖZDEN KELEŞ, Seray ÜNAL, Sabri |
dc.subject.por.fl_str_mv |
Forest fire, Sentinel-2, Burn severity, Topographic factors, Black pine forests |
topic |
Forest fire, Sentinel-2, Burn severity, Topographic factors, Black pine forests |
description |
Backgroud: Forest fires are one of the most important natural disasters all over the world in terms of the damage they cause to the ecosystem. It is observed that there is a significant increase in the number of forest fires in Türkiye and in the world. This situation jeopardizes the sustainability of forests. It is very important to estimate fire behavior characteristics in order to take pre-fire measures and to take effective interventions in the event of a fire. Obtaining data based on terrestrial measurements to predict fire behavior is both very expensive and very time consuming. At this point, the use of remote sensing technologies is very useful. In this respect, using satellite images to determine the areas destroyed by fire and their burning severity will be faster, more sensitive and economical in terms of fire fighting and precautions to be taken. Results: In this study, the forest fire that occurred in Kastamonu-Taşköprü district was analyzed with remote sensing techniques. First of all, pre-fire and post-fire Sentinel-2 images of fire areas were used to determine the burned area using NBR (Normalized Burn Ratio) and dNBR (Differenced Normalized Burn Ratio) indices. Also, burned area rate and burn severity were evaluated the depending on the altitude, aspect and slope factors. Conclusion: We found that almost 1504.9 ha forest land burned in the study site. Topographical maps showed that the most burned areas were covered by moderate- and high- severity classes. The forest fire was more severe in the altitude range from 1170 to 1370m, at 20-33% slope and northerly aspects in our study site. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-06-21 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://cerne.ufla.br/site/index.php/CERNE/article/view/3230 |
url |
https://cerne.ufla.br/site/index.php/CERNE/article/view/3230 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://cerne.ufla.br/site/index.php/CERNE/article/view/3230/1344 |
dc.rights.driver.fl_str_mv |
http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by/4.0/ |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
CERNE CERNE |
publisher.none.fl_str_mv |
CERNE CERNE |
dc.source.none.fl_str_mv |
CERNE; Vol. 29 No. 1 (2023); e-103230 CERNE; v. 29 n. 1 (2023); e-103230 2317-6342 0104-7760 reponame:Cerne (Online) instname:Universidade Federal de Lavras (UFLA) instacron:UFLA |
instname_str |
Universidade Federal de Lavras (UFLA) |
instacron_str |
UFLA |
institution |
UFLA |
reponame_str |
Cerne (Online) |
collection |
Cerne (Online) |
repository.name.fl_str_mv |
Cerne (Online) - Universidade Federal de Lavras (UFLA) |
repository.mail.fl_str_mv |
cerne@dcf.ufla.br||cerne@dcf.ufla.br |
_version_ |
1799705358212530176 |