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  1. 120 山岳科学総合研究所
  2. 1201 学術論文

TREE SPECIES CLASSIFICATION OF BROADLEAVED FORESTS IN NAGANO, CENTRAL JAPAN, USING AIRBORNE LASER DATA AND MULTISPECTRAL IMAGES

http://hdl.handle.net/10091/00022712
http://hdl.handle.net/10091/00022712
cbbd8af3-87c3-49bc-b349-98c4abe27a06
名前 / ファイル ライセンス アクション
16K18716_03.pdf 16K18716_03.pdf (1.2 MB)
Item type 学術雑誌論文 / Journal Article(1)
公開日 2021-02-22
タイトル
言語 en
タイトル TREE SPECIES CLASSIFICATION OF BROADLEAVED FORESTS IN NAGANO, CENTRAL JAPAN, USING AIRBORNE LASER DATA AND MULTISPECTRAL IMAGES
言語
言語 eng
キーワード
主題Scheme Other
主題 Forest resource measurement
キーワード
主題Scheme Other
主題 Airborne laser scanning
キーワード
主題Scheme Other
主題 Multispectral image
キーワード
主題Scheme Other
主題 Broadleaved tree species classification
キーワード
主題Scheme Other
主題 Support vector machine classifier
キーワード
主題Scheme Other
主題 Neighborhood component analysis
キーワード
主題Scheme Other
主題 Afan Woodland
資源タイプ
資源 http://purl.org/coar/resource_type/c_6501
タイプ journal article
著者 Deng, S

× Deng, S

WEKO 110713

Deng, S

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Katoh, M

× Katoh, M

WEKO 110714

Katoh, M

Search repository
Takenaka, Y

× Takenaka, Y

WEKO 110715

Takenaka, Y

Search repository
Cheung, K

× Cheung, K

WEKO 110716

Cheung, K

Search repository
Ishii, A

× Ishii, A

WEKO 110717

Ishii, A

Search repository
Fujii, N

× Fujii, N

WEKO 110718

Fujii, N

Search repository
Gao, T

× Gao, T

WEKO 110719

Gao, T

Search repository
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/W3:33-38(2017)
書誌情報 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences

巻 XLII-3/W3, p. 33-38, 発行日 2017-10-19
抄録
内容記述タイプ Abstract
内容記述 This study attempted to classify three coniferous and ten broadleaved tree species by combining airborne laser scanning (ALS) data and multispectral images. The study area, located in Nagano, central Japan, is within the broadleaved forests of the Afan Woodland area. A total of 235 trees were surveyed in 2016, and we recorded the species, DBH, and tree height. The geographical position of each tree was collected using a Global Navigation Satellite System (GNSS) device. Tree crowns were manually detected using GNSS position data, field photographs, true-color orthoimages with three bands (red-green-blue, RGB), 3D point clouds, and a canopy height model derived from ALS data. Then a total of 69 features, including 27 image-based and 42 point-based features, were extracted from the RGB images and the ALS data to classify tree species. Finally, the detected tree crowns were classified into two classes for the first level (coniferous and broadleaved trees), four classes for the second level (Pinus densiflora, Larix kaempferi, Cryptomeria japonica, and broadleaved trees), and 13 classes for the third level (three coniferous and ten broadleaved species), using the 27 image-based features, 42 point-based features, all 69 features, and the best combination of features identified using a neighborhood component analysis algorithm, respectively. The overall classification accuracies reached 90 % at the first and second levels but less than 60 % at the third level. The classifications using the best combinations of features had higher accuracies than those using the image-based and point-based features and the combination of all of the 69 features.
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
DOI
識別子タイプ DOI
関連識別子 https://doi.org/10.5194/isprs-archives-xlii-3-w3-33-2017
関連名称 10.5194/isprs-archives-xlii-3-w3-33-2017
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
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