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DETECTING FORESTS DAMAGED BY PINE WILT DISEASE AT THE INDIVIDUAL TREE LEVEL USING AIRBORNE LASER DATA AND WORLDVIEW-2/3 IMAGES OVER TWO SEASONS
http://hdl.handle.net/10091/00022714
http://hdl.handle.net/10091/00022714bdd1ae5a-bc7b-40f1-96bd-fb0fba30efdd
名前 / ファイル | ライセンス | アクション |
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16K18716_05.pdf (724.9 kB)
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Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2021-02-22 | |||||
タイトル | ||||||
言語 | en | |||||
タイトル | DETECTING FORESTS DAMAGED BY PINE WILT DISEASE AT THE INDIVIDUAL TREE LEVEL USING AIRBORNE LASER DATA AND WORLDVIEW-2/3 IMAGES OVER TWO SEASONS | |||||
言語 | ||||||
言語 | eng | |||||
DOI | ||||||
識別子タイプ | DOI | |||||
関連識別子 | https://doi.org/10.5194/isprs-archives-xlii-3-w3-181-2017 | |||||
関連名称 | 10.5194/isprs-archives-xlii-3-w3-181-2017 | |||||
キーワード | ||||||
主題 | Pine wilt disease, Tree mortality, Airborne laser scanning, WorldView-2, WorldView-3 | |||||
資源タイプ | ||||||
資源 | http://purl.org/coar/resource_type/c_6501 | |||||
タイプ | journal article | |||||
著者 |
Takenaka, Y
× Takenaka, Y× Katoh, M× Deng, S× Cheung K |
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信州大学研究者総覧へのリンク | ||||||
氏名 | Deng, Songqiu | |||||
URL | https://soar-rd.shinshu-u.ac.jp/profile/ja.OFfhupyC.html | |||||
出版者 | ||||||
出版者 | Copernicus Publications | |||||
引用 | ||||||
内容記述タイプ | Other | |||||
内容記述 | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences.XLII-3/W3:181-184(2017) | |||||
書誌情報 |
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 巻 XLII-3/W3, p. 181-184, 発行日 2017-10-19 |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | Pine wilt disease is caused by the pine wood nematode (Bursaphelenchus xylophilus) and Japanese pine sawyer (Monochamus alternatus). This study attempted to detect damaged pine trees at different levels using a combination of airborne laser scanning (ALS) data and high-resolution space-borne images. A canopy height model with a resolution of 50 cm derived from the ALS data was used for the delineation of tree crowns using the Individual Tree Detection method. Two pan-sharpened images were established using the ortho-rectified images. Next, we analyzed two kinds of intensity-hue-saturation (IHS) images and 18 remote sensing indices (RSI) derived from the pan-sharpened images. The mean and standard deviation of the 2 IHS images, 18 RSI, and 8 bands of the WV-2 and WV-3 images were extracted for each tree crown and were used to classify tree crowns using a support vector machine classifier. Individual tree crowns were assigned to one of nine classes: bare ground, Larix kaempferi, Cryptomeria japonica, Chamaecyparis obtusa, broadleaved trees, healthy pines, and damaged pines at slight, moderate, and heavy levels. The accuracy of the classifications using the WV-2 images ranged from 76.5 to 99.6 %, with an overall accuracy of 98.5 %. However, the accuracy of the classifications using the WV-3 images ranged from 40.4 to 95.4 %, with an overall accuracy of 72 %, which suggests poorer accuracy compared to those classes derived from the WV-2 images. This is because the WV-3 images were acquired in October 2016 from an area with low sun, at a low altitude. | |||||
資源タイプ(コンテンツの種類) | ||||||
内容記述タイプ | Other | |||||
内容記述 | Article | |||||
ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 1682-1750 | |||||
権利 | ||||||
権利情報 | © Authors 2017. CC BY 4.0 License. | |||||
出版タイプ | ||||||
出版タイプ | VoR | |||||
出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 |