[M-IS11] Mountain Science

[MIS11-P10] Utilizing time-lapse cameras for tracking distribution changes of dwarf bamboo and dwarf pine on the west slope of Mt. Tateyama

*Ryotaro Okamoto^1,2, Hiroyuki Oguma², Reiko Ide² (1.University of Tsukuba, 2.National Institute for Environmental Studies)

Keywords:Alpine vegetation, Time-lapse camera, Deep learning, Climate change

Alpine vegetation is vulnerable to climate change, and in Japan, the expansion of dwarf bamboo and the elongation of dwarf pine have been reported in response to early snowmelt and rising temperatures. Especially in the case of dwarf bamboo, which is problematic for invading snowbed vegetation, regular dwarf bamboo cutting is effective for the conservation of alpine plants. Monitoring vegetation changes is urgent for such measures. We have developed a method for creating a classification map of alpine vegetation using time-lapse cameras that can capture high-frequency images with very low cost. Time-lapse cameras cover a wide range at a lower cost compared to on-site vegetation surveys, and they excel in being less affected by weather conditions and having a higher shooting frequency compared to satellite images or aerial photographs. In this study, we used nine years' worth of time-lapse camera photos capturing the western slope of Mt. tateyama at the Japanese Northern Alps to track the annual distribution changes of dwarf bamboo and dwarf pine. In the presentation, we will also discusses the impact of climate conditions and snowmelt timing on distribution changes.