基于ENVISAT-ASAR图像的土壤含水量反演研究

发布时间：2018-04-20 22:37

本文选题：雷达后向散射系数 + 地表粗糙度　；参考：《兰州大学》2015年硕士论文

【摘要】：地表土壤水分在全球水资源中的所占比重较小,但是它却是非常重要的,它是联系地表水和地下水的纽带,作为陆地水资源循环过程中的一个重要变量,成为众多水文模型、生态模型、气候模型等的一个输入参数。土壤水分的变化会受到土壤特性、气候因子、地形因子的影响,但反过来土壤水分的变化也会影响气候的变化,是一个相互作用的过程。土壤水分传统的测量方法无法再短时间内获取大面积土壤水分变化,微波遥感监测由于微波能够进行全天时、全天候的观测,并对表层土壤水分极其敏感,因而被广泛应用到土壤水分的研究当中。本研究选择白龙江流域武都段作为研究区,在研究雷达数据反演土壤水分原理的基础上,利用C波段Envisat ASAR雷达数据(2009年和2010年)和其他辅助数据,采用变化检测的方法,开展了0-10cm深度土壤水分的反演工作,期望对基于雷达数据以流域尺度的土壤水分反演工作增色,为研究区内生态保持、生态环境恢复等研究提供支持。研究得到的主要结论：(1)根据前人研究的所得到的植被含水量(VWC)与归一化湿度指数(NDMI)之间的转换关系,建立低矮植被的VWC与NDMI之间的多项式关系,即可得到VWC；再利用水云模型进行植被冠层体散射(σ0veg)的估算,发现植被体散射对总散射的贡献可以忽略不计,即本研究不考虑植被的影响。(2)利用改进的积分方程模型AIEM模拟地表粗糙度,发现雷达后向散射系数与土壤水分和地表粗糙度之间表现为一个对数关系；再利用变化检测的方法消除地表粗糙度的影响,建立土壤水分反演的经验模型,并对反演结果做精度验证,得出反演的土壤水分是可靠的,因而该土壤水分的反演模型是适用于本研究区内大面积草地和耕地的土壤水分反演研究的。(3)土壤水分的空间分布规律为：东北方向和西南方向的土壤水分高,沟道两侧坡面的土壤含水量是较低的,土壤水分的空间分布是具有时间稳定性；(4)土壤水分空间分布影响因子分析结果为：土壤的含水量与土壤特性的关系密切,不同土壤质地的土壤含水量不同,一般表现为砂质壤土壤土砂土；坡度与土壤水分是表现为显著的负相关关系,并且不同坡向的土壤水分的差异是非常明显的,一般表现为向阳坡向阴坡,高程与土壤水分呈显著的正相关关系；降雨是影响土壤水分的重要因素之一,与土壤水分表现为正相关。
[Abstract]:Surface soil water accounts for a relatively small proportion of global water resources, but it is very important. It is a link between surface water and groundwater, and as an important variable in the process of terrestrial water circulation, it has become a lot of hydrological models. An input parameter to an ecological model, a climate model, etc. The change of soil moisture will be affected by soil characteristics, climatic factors and topographic factors, but in turn, the change of soil moisture will also affect the climate change, which is an interactive process. The traditional measurement method of soil moisture can not obtain large area soil moisture change in a short time. Microwave remote sensing monitoring is very sensitive to surface soil moisture because it can be observed all day and all weather. Therefore, it is widely used in the study of soil moisture. In this study, Wudu section of the Bailong River Basin was selected as the study area. On the basis of studying the principle of soil moisture retrieval from radar data, the C-band Envisat ASAR radar data (2009 and 2010) and other auxiliary data were used to detect changes. The inversion of 0-10cm depth soil moisture is carried out, which is expected to enhance the retrieval of soil moisture on watershed scale based on radar data, and to provide support for the study of ecological conservation and ecological environment restoration in the study area. The main conclusion of this study is: (1) the polynomial relationship between VWC and NDMI of low vegetation is established according to the transformation relationship between the water content of vegetation and the normalized humidity index obtained by previous studies. Using water cloud model to estimate vegetation canopy scattering (蟽 0veg), it is found that the contribution of vegetation body scattering to total scattering is negligible. That is, this study does not consider the influence of vegetation. (2) the improved integral equation model AIEM is used to simulate the surface roughness, and it is found that the radar backscattering coefficient is logarithmic with soil moisture and surface roughness. Then using the method of change detection to eliminate the influence of surface roughness, the empirical model of soil moisture inversion is established, and the accuracy of the inversion result is verified, and it is concluded that the soil moisture inversion is reliable. Therefore, the inversion model of soil moisture is suitable for the study of soil moisture inversion of large area grassland and cultivated land in this study area. The spatial distribution law of soil moisture is: the soil moisture is high in the northeast direction and the southwest direction. Soil water content on both sides of the gully slope is relatively low, and the spatial distribution of soil moisture is time-stable. The results show that the relationship between soil moisture content and soil characteristics is close. The soil moisture content of different soil texture is different, generally the sandy loam soil sandy soil, the slope and soil moisture are significantly negative correlation, and the difference of soil moisture in different slope direction is very obvious. Rainfall is one of the most important factors affecting soil moisture, and it is positively correlated with soil moisture.
【学位授予单位】：兰州大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：S152.7

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