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Comparison of Conventional Change Detection Methodologies Using High-Resolution Imagery to Find Forest Damage Caused by Typhoons
http://hdl.handle.net/10659/00006993
http://hdl.handle.net/10659/0000699379edfbc9-127f-4788-9837-b78eb1d45d75
名前 / ファイル | ライセンス | アクション |
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R-2021-44_kaneko.pdf (8.0 MB)
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Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2022-02-21 | |||||
タイトル | ||||||
タイトル | Comparison of Conventional Change Detection Methodologies Using High-Resolution Imagery to Find Forest Damage Caused by Typhoons | |||||
言語 | ||||||
言語 | eng | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | windthrow | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | landslide | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | remote sensing | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | change detection | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | NDVI filtering | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | SAM | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | SVM | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | planetscope | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | windthrow | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | landslide | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | remote sensing | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | change detection | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | NDVI filtering | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | SAM | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | SVM | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | planetscope | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
資源タイプ | journal article | |||||
著者 |
Furukawa, Flavio
× Furukawa, Flavio× Morimoto, Junko× Yoshimura, Nobuhiko× Kaneko, Masami |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | The number of intense tropical cyclones is expected to increase in the future, causing severe damage to forest ecosystems. Remote sensing plays an important role in detecting changes in land cover caused by these tropical storms. Remote sensing techniques have been widely used in different phases of disaster risk management because they can deliver information rapidly to the concerned parties. Although remote sensing technology is already available, an examination of appropriate methods based on the type of disaster is still missing. Our goal is to compare the suitability of three different conventional classification methods for fast and easy change detection analysis using high-spatial-resolution and high-temporal-resolution remote sensing imagery to identify areas with windthrow and landslides caused by typhoons. In August 2016, four typhoons hit Hokkaido, the northern island of Japan, creating large areas of windthrow and landslides. We compared the normalized difference vegetation index (NDVI) filtering method, the spectral angle mapper (SAM) method, and the support vector machine (SVM) method to identify windthrow and landslides in two different study areas in southwestern Hokkaido. These methodologies were evaluated using PlanetScope data with a resolution of 3 m/px and validated with reference data based on Worldview2 data with a very high resolution of 0.46 m/px. The results showed that all three methods, when applied to high-spatial-resolution imagery, can deliver sufficient results for windthrow and landslide detection. In particular, the SAM method performed better at windthrow detection, and the NDVI filtering method performed better at landslide detection. | |||||
書誌情報 |
Remote Sensing 巻 12, 号 19, p. 3242-1-3242-17, 発行日 2020-10 |
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DOI | ||||||
関連タイプ | isIdenticalTo | |||||
識別子タイプ | DOI | |||||
関連識別子 | https://doi.org/10.3390/rs12193242 | |||||
権利(URI) | ||||||
権利情報 | http://creativecommons.org/licenses/by/4.0/ | http://creativecommons.org/licenses/by/4.0/ | |||||
著者版フラグ | ||||||
出版タイプ | VoR | |||||
出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||
出版者 | ||||||
出版者 | MDPI | |||||
資源タイプ | ||||||
内容記述タイプ | Other | |||||
内容記述 | Article |