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	基于AMSR2被动微波积雪参量高精度反演方法研究
其他题名	A research on the method of deriving high-precision snow parameters from AMSR2 passive microwave remote sensing data
	沙依然·外力 1; 毛炜峄 2
来源期刊	冰川冻土
ISSN	1000-0240
出版年	2016
卷号	38 期号:1 页码:145-158
中文摘要	以新疆为研究区域建立了被动微波遥感积雪深度高精度反演模型, 采用高空间和时间分辨率AMSR2被动微波遥感数据(2012年11月-2015年3月逐日数据), 结合研究区域海拔高度、坡度、坡向、沙漠, 荒漠和地表粗糙度等地形、地貌特征, 考虑冰川、水体、林地等地表覆盖类型和不同季节的新雪、干雪和湿雪等积雪属性的微波辐射特征, 以决策树阈值法为基础, 通过采集样本分类建立起多种雪深判识阈值, 在此基础上建立AMSR2高精度积雪深度反演综合模型, 分类分析不稳定积雪和冰川信息, 从而实现雪深在60 cm以内的积雪深度AMSR2反演的主要原理、思路及方法, 并对模型的反演结果跟台站实测或者野外观测积雪值以时间和空间角度进行检验. 结果表明: 该综合模型能够定量判识研究区域复杂地形地貌条件下的1~60 cm积雪厚度, 检验的复相关系数为0.74~0.88, 均方根误差为2.92~6.14 cm, 平均绝对偏差指数为3~4 cm, 雪深误差<5 cm的精度为91%~94%, 雪深误差<2.5cm的精度为81%~87%.
英文摘要	This study aims to establish a model of deriving high-precision snow parameters from passive microwave remote sensing data, taken Xinjiang Uygur Autonomous Region as a case. In this paper, firstly high-resolution spatial and temporal data in the research region by means of AMSR2 passive microwave remote sensing were collected from November, 2010 to March, 2015. Then terrain features, such as altitude, slope, aspect, desert and surface roughness, had also been investigated. Other factors, such as variation of surfaces ranging from glacier, paddy field and forest, and microwave radiations of new snow, dry snow and wet snow in various seasons had also been taken into account. After that, a variety of threshold values to assess snow depth were worked out by classifying the collected samples. Finally, a deriving model of snow depth from AMSR2 high-precision sensing data was set up on the basis of decision tree threshold method. The model was then adopted to analyze and classify unstable snow cover and glaciers to establish a deriving method from AMSR2 data targeting at the snow depth of no more than 60 cm. The result of the test was reexamined with those data which were collected from stations or expeditions. The research approves the workability of the new model in identifying the snow depth ranging from 1 to 60 cm in the areas with complicated landforms, with multiple correlation coefficients ranging from 0.74 to 0.88, root mean square error ranging from 2.92 to 6.14 cm, the mean absolute deviation index ranging from 3 to 4 cm. When the snow depth error less than 5 cm, the accuracy of the test ranges from 91% to 94%; when the snow depth error less than 2.5 cm, the accuracy ranges from 81% to 87%.
中文关键词	积雪辐射特性 ; 雪深判识模型 ; 复杂地形地貌
英文关键词	AMSR2 AMSR2 snow radiation snow depth assessing model varied topography
语种	中文
国家	中国
收录类别	CSCD
WOS类目	METEOROLOGY ATMOSPHERIC SCIENCES
WOS研究方向	Meteorology & Atmospheric Sciences
CSCD记录号	CSCD:5736855
来源机构	中国气象局乌鲁木齐沙漠气象研究所
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/233923
作者单位	1.南京信息工程大学应用气象学院, 南京, 江苏 210044, 中国; 2.中国气象局乌鲁木齐沙漠气象研究所, 乌鲁木齐, 新疆 830002, 中国
推荐引用方式 GB/T 7714	沙依然·外力,毛炜峄. 基于AMSR2被动微波积雪参量高精度反演方法研究[J]. 中国气象局乌鲁木齐沙漠气象研究所,2016,38(1):145-158.
APA	沙依然·外力,&毛炜峄.(2016).基于AMSR2被动微波积雪参量高精度反演方法研究.冰川冻土,38(1),145-158.
MLA	沙依然·外力,et al."基于AMSR2被动微波积雪参量高精度反演方法研究".冰川冻土 38.1(2016):145-158.