Uncertainties involved in leaf fall phenology detected by digital camera

Shin Nagai*, Tomoharu Inoue, Toshiyuki Ohtsuka, Shinpei Yoshitake, Kenlo Nishida Nasahara, Taku M. Saitoh


研究成果: Article査読

6 被引用数 (Scopus)


We evaluated the uncertainty in the estimation of year-to-year variability in the timing of leaf fall detected by the analysis of red, green and blue (RGB) values extracted from daily phenological images in a deciduous broad-leaved forest in Japan. We examined (1) the spatial distribution of individual tree species within a 1-ha permanent plot and the spatio-temporal variability of leaf litter of various species for 8 years; and (2) the relationship between the year-to-year variability of leaf fall detected by leaf litter and that detected by phenological images of various species. Uncertainties were caused by (1) the heterogeneous distribution of each species within the whole forest community; (2) the year-to-year variability of the timing of leaf fall among species; and (3) differences in leaf colouring and leaf fall patterns among species. Our results indicate the importance of integrating RGB analysis of each species and of the whole canopy on the basis of spatial locations of individuals and proportions of tree species within a forest to reduce uncertainty.

ジャーナルEcological Informatics
出版ステータスPublished - 2015 11月 1

ASJC Scopus subject areas

  • 生態、進化、行動および分類学
  • 生態学
  • モデリングとシミュレーション
  • 生態モデリング
  • コンピュータ サイエンスの応用
  • 計算理論と計算数学
  • 応用数学


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