干旱区生态环境知识资源中心(Arid): A NEW INDEX FOR SANDY LAND DETECTION BASED ON THERMAL INFRARED EMISSIVITY DATA

Arid

	A NEW INDEX FOR SANDY LAND DETECTION BASED ON THERMAL INFRARED EMISSIVITY DATA
	Chen, Shanshan; Ren, Huazhong; Tao, Yunzhu; Zheng, Yitong; Sun, Yuanheng; Nie, Jing; Guo, Jinxin; Liu, Rongyuan; Fan, Wenjie
通讯作者	Ren, HZ (corresponding author), Peking Univ, Inst Remote & Geog Informat Syst, Sch Earth & Space Sci, Beijing 100871, Peoples R China.
会议名称	IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
会议日期	JUL 28-AUG 02, 2019
会议地点	Yokohama, JAPAN
英文摘要	Spatial distribution and disappearance of sandy land is important for ecosystem management of desert regions and provides highly valuable information on desertification and climate change studies in arid environments. Based on the field measurement in the Gurbantonggut Desert, Xinjiang, China and the analysis of the spectral features of sandy land, a new sand differential emissivity index (SDEI) was proposed first for sandy land detection. Compared with the previous vegetation index, which can only distinguish green plants from bare land, SDEI can make a distinction well between sandy land and dry vegetation. For large regional mapping of sandy land, SDEI was applied on the ASTER Global Emissivity Dataset based on the Google Earth Engine platform. And then, four emissivity simulation schemes of different mixed pixels were conducted to determine the best threshold of sandy land mapping. The results show that when the threshold value is larger than 0.041, the sand distribution can be well extracted. Finally, the sandy land area of China extracted by SDEI is 160.67 x10(4) km(2) for year 2008, which is close to the data released by the China's State Forestry Administration. These experimental results indicated that SDEI is applicable to identification of sandy land, and therefore satellite remotely-sensed thermal infrared observations have good potential in sandy land detection.
英文关键词	sandy land detection remote sensing ASTER GED emissivity index SDEI
来源出版物	2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019)
ISSN	2153-6996
出版年	2019
页码	1402-1405
ISBN	978-1-5386-9154-0
出版者	IEEE
类型	Proceedings Paper
语种	英语
收录类别	CPCI-S
WOS记录号	WOS:000519270601161
WOS类目	Geosciences, Multidisciplinary ; Remote Sensing
WOS研究方向	Geology ; Remote Sensing
资源类型	会议论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/370098
作者单位	[Chen, Shanshan; Ren, Huazhong; Tao, Yunzhu; Zheng, Yitong; Sun, Yuanheng; Nie, Jing; Guo, Jinxin; Fan, Wenjie] Peking Univ, Inst Remote & Geog Informat Syst, Sch Earth & Space Sci, Beijing 100871, Peoples R China; [Liu, Rongyuan] China Aero Geophys Survey, Beijing 100083, Peoples R China; [Liu, Rongyuan] Remote Sensing Ctr Nat Resources, Beijing 100083, Peoples R China
推荐引用方式 GB/T 7714	Chen, Shanshan,Ren, Huazhong,Tao, Yunzhu,et al. A NEW INDEX FOR SANDY LAND DETECTION BASED ON THERMAL INFRARED EMISSIVITY DATA[C]:IEEE,2019:1402-1405.