| アイテムタイプ |
学術雑誌論文 / Journal Article(1) |
| 公開日 |
2025-06-12 |
| タイトル |
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タイトル |
Application of a tuning?free burned area detection algorithm to the Chornobyl wildfires in 2022 |
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言語 |
en |
| 言語 |
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言語 |
eng |
| 資源タイプ |
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資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
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資源タイプ |
journal article |
| 著者 |
Hu Jun
Igarashi Yasunori
Kotsuki Shunji
Yang Ziping
Talerko Mykola
Landin Volodymyr
Tyshchenko Olha
Zheleznyak Mark
Protsak Valentyn
Kirieiev Serhii
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| 抄録 |
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内容記述タイプ |
Abstract |
|
内容記述 |
The wildfires in the Chornobyl Exclusion Zone (ChEZ) have caused widespread public concern about the potential risk of radiation exposure from radionuclides resuspended and redistributed due to the fires in 2020. The wildfires were also confirmed in ChEZ in the spring of 2022, and its impact needed to be estimated accurately and rapidly. In this study, we developed a tuning-free burned area detection algorithm (TuFda) to perform rapid detection of burned areas for the purpose of immediate post-fire assessment. We applied TuFda to detect burned areas in the ChEZ during the spring of 2022. The size of the burned areas in February and March was estimated as 0.4 km2 and 70 km2, respectively. We also applied the algorithm to other areas outside the boundaries of the ChEZ and detected land surface changes totaling 553 km2 in northern Ukraine between February and March 2022. These changes may have occurred as a result of the Russian invasion. This study is the first to identify areas in northern Ukraine impacted by both wildfires and the Russian invasion of Ukraine in 2022. Our algorithm facilitates the rapid provision of accurate information on significant land surface changes whether caused by wildfires, military action, or any other factor. |
| 書誌情報 |
scientific reports
巻 13,
p. 5236,
発行日 2023-03
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| 出版者 |
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出版者 |
Springer Nature |
| ISSN |
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収録物識別子タイプ |
ISSN |
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収録物識別子 |
2045-2322 |
| DOI |
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識別子タイプ |
DOI |
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関連識別子 |
10.1038/s41598-023-32300-5 |
