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  1. 070 農学部, 大学院農学研究科
  2. 0701 学術論文

Improving the Precision of Tree Counting by Combining Tree Detection with Crown Delineation and Classification on Homogeneity Guided Smoothed High Resolution (50 cm) Multispectral Airborne Digital Data

http://hdl.handle.net/10091/17108
http://hdl.handle.net/10091/17108
1d3bb84b-2df1-45e5-a9df-40051c643cd2
名前 / ファイル ライセンス アクション
Improving_Precision_Tree_Counting_Combining_Tree_Detection_Crown_Delineation.pdf Improving_Precision_Tree_Counting_Combining_Tree_Detection_Crown_Delineation.pdf (1.6 MB)
Item type 学術雑誌論文 / Journal Article(1)
公開日 2013-08-27
タイトル
言語 en
タイトル Improving the Precision of Tree Counting by Combining Tree Detection with Crown Delineation and Classification on Homogeneity Guided Smoothed High Resolution (50 cm) Multispectral Airborne Digital Data
言語
言語 eng
キーワード
主題Scheme Other
主題 forest resource management
キーワード
主題Scheme Other
主題 individual tree crown
キーワード
主題Scheme Other
主題 tree counting method
資源タイプ
資源 http://purl.org/coar/resource_type/c_6501
タイプ journal article
著者 Katoh, Masato

× Katoh, Masato

WEKO 32480

Katoh, Masato

Search repository
Gougeon, Francois A.

× Gougeon, Francois A.

WEKO 32481

Gougeon, Francois A.

Search repository
信州大学研究者総覧へのリンク
氏名 Katoh, Masato
URL http://soar-rd.shinshu-u.ac.jp/profile/ja.OhyNPUkh.html
出版者
出版者 MDPI AG
引用
内容記述タイプ Other
内容記述 REMOTE SENSING. 4(5):1411-1424 (2012)
書誌情報 REMOTE SENSING

巻 4, 号 5, p. 1411-1424, 発行日 2013-05
抄録
内容記述タイプ Abstract
内容記述 A method of counting the number of coniferous trees by species within forest compartments was developed by combining an individual tree crown delineation technique with a treetop detection technique, using high spatial resolution optical sensor data. When this method was verified against field data from the Shinshu University Campus Forest composed of various cover types, the accuracy for the total number of trees per stand was higher than 84%. This shows improvements over the individual tree crown delineation technique alone which had accuracies lower than 62%, or the treetop detection technique alone which had accuracies lower than 78%. However, the accuracy of the number of trees classified by species was less than 84%. The total number of trees by species per stand was improved with exclusion of the understory species and ranged from 45.2% to 93.8% for Chamaecyparis obtusa and C. pisifera and from 37.9% to 98.1% for broad-leaved trees because many of these were understory species. The better overall results are attributable primarily to the overestimation of Pinus densiflora, Larix kaempferi and broad-leaved trees compensating for the underestimation of C. obtusa and C. pisifera. Practical forest management can be enhanced by registering the output resulting from this technology in a forest geographical information system database. This approach is mostly useful for conifer plantations containing medium to old age trees, which have a higher timber value.
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 2072-4292
DOI
識別子タイプ DOI
関連識別子 https://doi.org/10.3390/rs4051411
関連名称 10.3390/rs4051411
権利
権利情報 Copyright© 2012 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
出版タイプ
出版タイプ VoR
出版タイプResource http://purl.org/coar/version/c_970fb48d4fbd8a85
WoS
表示名 Web of Science
URL http://gateway.isiknowledge.com/gateway/Gateway.cgi?&GWVersion=2&SrcAuth=ShinshuUniv&SrcApp=ShinshuUniv&DestLinkType=FullRecord&DestApp=WOS&KeyUT=000306757800015
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