Japan Geoscience Union Meeting 2014

Presentation information

Poster

Symbol A (Atmospheric, Ocean, and Environmental Sciences) » A-CG Complex & General

[A-CG36_30PO1] Science in the Arctic Region

Wed. Apr 30, 2014 6:15 PM - 7:30 PM Poster (3F)

Convener:*Saitoh Sei-Ichi(Faculty of Fisheries Sciences, Hokkaido University), Jun Inoue(National Instituteof Polar Resarch), Naomi Harada Naomi(Japan Agency for Marine-Earth Science and Technology), Rikie Suzuki(Research Institute for Global Change, Japan Agency for Marine-Earth Science and Technology)

6:15 PM - 7:30 PM

[ACG36-P04] Spacial distribution of vegetation at taiga-tundra boundary ecosystem in eastern Siberia

*Tomoki MOROZUMI1, Ivan BRAGIN2, Egor STAROSTIN3, Ryo SHINGUBARA1, Shunsuke TEI4, Shinya TAKANO1, Shin MIYAZAKI4, Trofim C. MAXIMOV5, Atsuko SUGIMOTO6 (1.Hokkaido University Graduate School of Environmental Science, 2.Far East Geological Institute, Far Eastern Branch Russian Academy of Science, 3.North-Eastern Federal University, 4.National Institute of Polar Research, Arctic Environment Research Center, 5.Institute for Biological Problems of Cryolithozone, Siberian Branch of Russian Academy of Sciences, 6.Hokkaido University Faculity of Environment Earth Science)

Keywords:Taiga-Tundra boundary, vegetation map, remote sensing, Siberia

Vegetation types, species compositions were observed with physical environment such as micro topography and soil moisture at taiga-tundra boundary ecosystem in lowland of Indigirka river in north eastern Siberia near Chokurdahk village(70oN,148oE)in July 2012 and 2013. There are 4 types of plant communities: driest Tree mound(Larix gmelnii etc.), Shrub(Betula nana etc.), Sphagnum(Sphagnum sp. etc.), wettest Hollow(Eriophorum angustifolium etc.). Large area is also covered by Willow(Salix udensis etc.) along the river. Soil moisture is the most important factor controlling vegetation and other biogeochemical cycles, such as methane emission. Thus, it is necessary to make a vegetation map with a classification as a key for estimating methane emission.The objective of this study is classify land cover vegetation using remote sensing approach on satellite images and photographs. In remote sensing approach we used high resolution satellite multispectral image(GeoEye-1, WorldView-2) and aerial photo by radio-control helicopter. Supervised classification was conducted for spacial distribution of vegetation based on aerial photos. This vegetation map will be used for upscaling of biogeochemical cycle process such as greenhouse gases.