著者

小熊 宏之 井手 玲子 雨谷 教弘 浜田 崇

出版者

公益社団法人 東京地学協会

雑誌

地学雑誌 (ISSN:0022135X)

巻号頁・発行日

vol.128, no.1, pp.93-104, 2019-02-25 (Released:2019-04-03)

参考文献数

18

被引用文献数

5 5

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The vulnerability of alpine ecosystems to climate change, as pointed out by the Intergovernmental Panel on Climate Change (IPCC), and the necessity to monitor alpine zones have been recognized globally. The Japanese alpine zone is characterized by extreme snowfall, and snowmelt time is a key factor in the growth of alpine vegetation. Therefore, in 2011, the National Institute for Environmental Studies (NIES), Japan, initiated long-term monitoring of snowmelt time and ecosystems in the Japanese alpine zone using automated digital time-lapse cameras. Twenty-nine monitoring sites are currently in operation. In this study, images from the cameras installed at mountain lodges in Nagano Prefecture and around Mt. Rishiri in Hokkaido are used. In addition, live camera images are obtained from cameras already operated by local governments in the Tohoku area and near Mt. Fuji. Red, green, and blue (RGB) digital numbers are derived from each pixel within the images. Snow-cover and snow-free pixels are classified automatically using a statistical discriminate analysis. Snowmelt time shows site-specific characteristics and yearly variations. It also reflects the local microtopography and differs among the habitats of various functional types of vegetation. The vegetation phenology is quantified using a vegetation index (green ratio) calculated from the RGB digital numbers. By analyzing temporal variations of the green ratio, local distributions of start and end dates and length of growing period are illustrated on a pixel base. The start of the green leaf period corresponds strongly to the snowmelt gradient, and the end of the green leaf period to vegetation type and elevation. The results suggest that the length of the green leaf period mainly corresponds to the snowmelt gradient in relation to local microtopography.