Journal of the Japanese Society of Revegetation Technology
Online ISSN : 1884-3670
Print ISSN : 0916-7439
ISSN-L : 0916-7439
ORIGINAL ARTICLES
Leaf area measurement of green wall plants using deep learning with terrestrial laser
Akira KATO Jun YAMAGUCHIShoko HIKOSAKAShigeru KURIKIKaori OSHIMARyohei UEYANAGIRyota ASANO
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2022 Volume 48 Issue 1 Pages 9-14

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Abstract

Green wall plants have various functionality such as mitigating heat island, creating green space, and absorbing carbon in an urban area. A method to evaluate the various functionality is needed for construction field. This study focuses on the plant structure and deep learning was introduced to estimate the leaf area and counting leaves automatically. To achieve this, the panorama distant image was created from 3D data acquired by terrestrial laser to prepare for the deep learning model. The model for the presence or absence of leaves had 90% accuracy and the counting leaves had 72% accuracy and leaf area estimated through deep learning had 27% error compared to the destructively sampled data.

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© 2022 Japanese Society of Revegetation Technology
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