干旱区生态环境知识资源中心(Arid): SOIL MOISTURE ESTIMATION BASED ON LANDSAT-8 AND MODIS IN THE UPSTREAM OF LUAN RIVER BASIN, CHINA

Arid

DOI	10.1109/IGARSS39084.2020.9323459
	SOIL MOISTURE ESTIMATION BASED ON LANDSAT-8 AND MODIS IN THE UPSTREAM OF LUAN RIVER BASIN, CHINA
	Li, Rui; Shi, Jiancheng; Zhao, Tianjie; Wang, Tianxing; Lu, Shanlong
通讯作者	Shi, JC (corresponding author), Chinese Acad Sci, Aerosp Informat Res Inst, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China.
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	Optical and thermal infrared remote sensing images highly integrate spatial heterogeneity information (land surface soil, vegetation and water). This paper evaluated the capacity of Landsat-8 and Moderate-resolution Imaging Spectroradiometer (MODIS) remote sensing indices and empirical relationship models for soil moisture estimations at different depths. The results show that (1) compared with other Landsat-8 indices, shortwave infrared based Surface Water Capacity Index (SWCI) has higher correlation with 10-50 cm depth soil moisture. The comparison based on MODIS daily indices confirms that SWCI can monitor 20 cm soil moisture with more stability; (2) The quadratic polynomial model based on Land Surface Temperature (LST) and SWCI possessed highest accuracy among all empirical models. The average coefficient of determination (R-2) increases to 0.257 from 0.150 based on LST-NDVI linear model and 0.176 based on LST-SWCI linear model. Soil moisture analysis at both 30 m and 1 km spatial scale suggest that optical remote sensing could indirectly reflect soil moisture variation with higher precise and more stability in root layer rather than top-most layer.
英文关键词	Soil moisture Optical remote sensing Quadratic polynomial model Semi-arid region
来源出版物	IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM
出版年	2020
页码	4922-4925
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:000664335304187
WOS关键词	VEGETATION COVER
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/2XILL650/365518
作者单位	[Li, Rui; Shi, Jiancheng; Zhao, Tianjie; Wang, Tianxing] Chinese Acad Sci, Aerosp Informat Res Inst, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China; [Lu, Shanlong] Chinese Acad Sci, Aerosp Informat Res Inst, Key Lab Digital Earth Sci, Beijing 100101, Peoples R China
推荐引用方式 GB/T 7714	Li, Rui,Shi, Jiancheng,Zhao, Tianjie,et al. SOIL MOISTURE ESTIMATION BASED ON LANDSAT-8 AND MODIS IN THE UPSTREAM OF LUAN RIVER BASIN, CHINA[C]:IEEE,2020:4922-4925.