干旱区生态环境知识资源中心(Arid): REMOTELY SENSED METHOD FOR DETECTION OF SPATIAL DISTRIBUTION PATTERN OF DRYLAND PLANTS IN WATER LIMITED ECOSYSTEM

Arid

DOI	10.1109/IGARSS39084.2020.9324058
	REMOTELY SENSED METHOD FOR DETECTION OF SPATIAL DISTRIBUTION PATTERN OF DRYLAND PLANTS IN WATER LIMITED ECOSYSTEM
	Hoshino, Buho; Tian, Ying; Shima, Keita; Riga, Su; Enkhtuvshin, Zoljarga; McCarthy, Christopher; Purevtseren, Myagmartseren
通讯作者	Hoshino, B (corresponding author), Rakuno Gakuen Univ, Lab Environm Remote Sensing, Ebetsu, Hokkaido 0698501, Japan.
会议名称	IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
会议日期	SEP 26-OCT 02, 2020
会议地点	ELECTR NETWORK
英文摘要	The Gobi Desert in Mongolia is characterized by sparse and patchy vegetation, interspersed with essentially bare areas. The vegetation pattern is typically formed by perennial shrubs, grasses or annually-herbaceous plant overlying a matrix composed of bare soil. Vegetation patterns, most broadly, refer to the spatial organization of vegetation in a landscape. However, since the plants in the Gobi Desert are sparsely distributed over a vast bare field, it is extremely difficult to accurately observe from satellite imagery. This is because reflectance of dry soil is very high and the reflectance of slightly distributed plants is eliminated by soil reflection. This study solves this problem by using field surveys and methods for combining different satellite sensor data and spectral un-mixing analysis. As a result, the pixel NDVI value of desert plants shows a smaller value than the ground measurement. It is shown that the fraction of the vegetation endmember after pixel un-mixing has a remarkably high correlation with the field measured values (where, R2=0.51 between NDVI of Landsat 8 imagery original pixels and un-mixed pixels and R2=0.79 between plants coverage of field measurement and un-mixed pixels percentage of vegetation endmembers).
英文关键词	Spectral un-mixing spatial distribution pattern of dryland plants Landsat field measurement
来源出版物	IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM
出版年	2020
页码	2799-2802
ISBN	978-1-7281-6374-1
出版者	IEEE
类型	Proceedings Paper
语种	英语
收录类别	CPCI-S
WOS记录号	WOS:000664335302202
WOS类目	Computer Science, Artificial Intelligence ; Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Optics
WOS研究方向	Computer Science ; Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Optics
资源类型	会议论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/365553
作者单位	[Hoshino, Buho; Tian, Ying; Shima, Keita; Riga, Su] Rakuno Gakuen Univ, Lab Environm Remote Sensing, Ebetsu, Hokkaido 0698501, Japan; [Enkhtuvshin, Zoljarga] Mongolian Hydrol Meteorol & Environm Ctr Sainshan, Ulaanbaatar, Mongolia; [McCarthy, Christopher] Univ Calif San Diego, 9500 Gilman Dr, La Jolla, CA 92093 USA; [Purevtseren, Myagmartseren] Natl Univ Mongolia, Dept Geog, Ulaanbaatar 14200, Mongolia
推荐引用方式 GB/T 7714	Hoshino, Buho,Tian, Ying,Shima, Keita,et al. REMOTELY SENSED METHOD FOR DETECTION OF SPATIAL DISTRIBUTION PATTERN OF DRYLAND PLANTS IN WATER LIMITED ECOSYSTEM[C]:IEEE,2020:2799-2802.