Accuracy Assessment in 3D Remote Sensing of Japanese Larch Trees using a Small UAV
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- Teng Poching
- The University of Tokyo, Graduate School of Agricultural and Life Sciences
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- Fukumaru Yuuki
- The University of Tokyo, Graduate School of Agricultural and Life Sciences
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- Zhang Yu
- The University of Tokyo, Graduate School of Agricultural and Life Sciences
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- Aono Mitsuko
- National Institute for Environmental Studies
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- Shimizu Yo
- The University of Tokyo, Graduate School of Agricultural and Life Sciences
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- Hosoi Fumiki
- The University of Tokyo, Graduate School of Agricultural and Life Sciences
Bibliographic Information
- Other Title
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- 小型 UAV を用いたカラマツ林の 3 次元リモートセンシングとその精度評価
- コガタ UAV オ モチイタ カラマツリン ノ 3ジゲン リモートセンシング ト ソノ セイド ヒョウカ
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Abstract
Aircraft-borne Lidar has been used for the accurate measurement of 3D canopy structure and tree height. However, the use of Lidar is costly and is not practical for high-frequency monitoring. Unmanned aerial vehicle (UAV) is a reasonable and convenient system for remote sensing applications. In this study, we examined an effective method to reconstruct digital surface model (DSM) of larch canopy and digital terrain model (DTM) of the underlying ground surface in larch canopy from color images measured by a UAV-borne camera with different focal length lenses (28 mm, 35 mm or 50 mm). Structure from motion (SfM) and surface reconstruction methods such as inverse distance weighting (IDW) and polygon methods were used for the DSM and DTM modeling. In addition, the digital canopy height model (DCHM) was generated by subtracting DTM from DSM. It was found that the tree canopy height estimate using the IDW method and the 28 mm lens was the best with a root mean squared error (RMSE) of 0.47 m.
Journal
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- Eco-Engineering
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Eco-Engineering 30 (1), 1-6, 2018
The Society of Eco-Engineering
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Keywords
Details 詳細情報について
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- CRID
- 1390001205190779520
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- NII Article ID
- 40021455449
- 130006327392
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- NII Book ID
- AA12005685
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- ISSN
- 18804500
- 13470485
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- NDL BIB ID
- 028804264
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- CiNii Articles
- KAKEN
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- Abstract License Flag
- Disallowed