TREETOP DETECTION FOR A RIVERINE BAMBOO FOREST USING UAV IMAGES

Treetop detection was conducted at a dense bamboo (Phyllostachys nigra var. henonis) forest using local maximum filtering (LMF) with a circular window under a high-resolution digital surface model (DSM) via UAV images. Optimal window size (WS) was evaluated based on applications in some WS cases. Tr...

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Veröffentlicht in:Doboku Gakkai Ronbunshu. G, Kankyo = Journal of Japan Society of Civil Engineers. Ser. G, Environmental Research Ser. G (Environmental Research), 2022, Vol.78(6), pp.II_175-II_182
Hauptverfasser: TEZUKA, Togo, MIZOGUCHI, Yuta, NAKAMURA, Keigo
Format: Artikel
Sprache:jpn
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Zusammenfassung:Treetop detection was conducted at a dense bamboo (Phyllostachys nigra var. henonis) forest using local maximum filtering (LMF) with a circular window under a high-resolution digital surface model (DSM) via UAV images. Optimal window size (WS) was evaluated based on applications in some WS cases. Treetop detection results showed that the highest F-value was obtained in 0.5-m WS, with a detection accuracy that was relatively higher than that of a previous study, although in a denser bamboo forest. Thus, high-resolution DSM and an appropriate WS are important factors for accurate treetop detection by LMF.
ISSN:2185-6648
DOI:10.2208/jscejer.78.6_II_175