干旱区生态环境知识资源中心(Arid): 干旱区稀疏植被覆盖条件下地表土壤水分微波遥感估算

Arid

	干旱区稀疏植被覆盖条件下地表土壤水分微波遥感估算
其他题名	Evaluation of Soil Moisture Contents Under Sparse Vegetation Coverage Conditions Using Microwave Remote Sensing Technology in Arid Region
	丁建丽; 姚远
来源期刊	地理科学
ISSN	1000-0690
出版年	2013
卷号	33 期号:7 页码:837-843
中文摘要	当前在干旱区土壤水分研究工作中,开展利用微波遥感技术高精度估算稀疏植被覆盖条件下地表粗糙度参数的研究是一项非常有意义的工作。基于微波遥感数据,结合土壤水分实测资料,以IEM模型为基础,分析雷达后向散射系数与土壤含水量、地表粗糙度参数之间的关系,利用最小二乘法和非线性回归的方法,建立光滑地表条件下的土壤含水量模型。结果表明:模型提取的土壤水分与实测值之间有很好的相关性,决定系数达到0.886,所建立的土壤水分信息提取模型在裸土以及稀疏植被覆盖地区能够得到较好的应用效果。
英文摘要	Soil moisture information can be extracted by microwave remote sensing technology; however, the problem is how to eliminate the influence of ground surface roughness and vegetation coverage on the backscattering data. Ground surface roughness is the key factor determining the data accuracy in northwest China where the vegetation coverage is small. Thus, evaluating and modeling the surface roughness parameters with a high precision is an important task for the arid land soil moisture study. Using IEM model, the response relationships between the different types of backscattering coefficient and the radar systematic coefficient and soil surface parameters are simulated. Results show that the backscattering coefficient is different from these parameterschange. Based on these achievements, the best radar parameters which can reflect the soil moisture are put forwarded. The corresponding relationships between the radar backscattering parameters and soil moisture contents, ground surface roughness parameters (such as, mean root height method, persistence length method and combined roughness method) are analyzed, and the experimental model which can reflect the soil moisture of relatively smooth ground surface is developed by using least squares method and non-linear regression method. At last, for a ground truth testing analysis, using the obtained RADAR-SAT2 data, the experimental model is applied in Weigan River and Kuch River delta oasis area. Results show that the data obtained from the experimental model has relatively high corresponding relationship with the soil moisture data collected in situ, and the determination coefficient is up to 0.886, implying the experimental model can be used in relatively wide scale for analyzing and modeling the soil moisture contents of some bare soil surface or the area whose vegetation density is low and vegetation coverage is small.
中文关键词	土壤水分 ; 雷达 ; IEM模型 ; 后向散射系数
英文关键词	soil moisture radar IEM model backscattering coefficient
语种	中文
国家	中国
收录类别	CSCD
WOS类目	REMOTE SENSING
WOS研究方向	Remote Sensing
CSCD记录号	CSCD:4891140
来源机构	新疆大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/229328
作者单位	新疆大学资源与环境科学学院, 绿洲生态教育部重点实验室, 乌鲁木齐, 新疆 830046, 中国
推荐引用方式 GB/T 7714	丁建丽,姚远. 干旱区稀疏植被覆盖条件下地表土壤水分微波遥感估算[J]. 新疆大学,2013,33(7):837-843.
APA	丁建丽,&姚远.(2013).干旱区稀疏植被覆盖条件下地表土壤水分微波遥感估算.地理科学,33(7),837-843.
MLA	丁建丽,et al."干旱区稀疏植被覆盖条件下地表土壤水分微波遥感估算".地理科学 33.7(2013):837-843.