【作者】 郑兴明；

【导师】 赵凯；

【作者基本信息】 中国科学院研究生院(东北地理与农业生态研究所) ， 地图学与地理信息系统， 2012， 博士

【摘要】 地球表层土壤含水量只占全球总水量的很少一部分，但它是联系地表水和地下水的纽带，其变化影响着地表能量分配与蒸散过程，制约着区域水分、能量循环，对于水文气象、生态环境等科学研究有着重要意义。此外，土壤湿度决定农作物的水分盈亏，土壤湿度过低或过高都将影响农作物的正常生长，甚至出现旱涝灾害，因此实现土壤湿度的时空动态监测能为“精准农业”、干旱预警以及作物估产服务。微波具有穿透低矮植被冠层探测浅表层土壤特性的能力，更因复相对介电常数对土壤水分的高敏感性，微波遥感已成为大尺度土壤湿度反演的最有效技术。论文在中国科学院知识创新工程重要方向项目“土壤湿度与积雪参量高精度微波遥感反演机理研究（KZCX2-YW-340）”的支持下开展研究工作。论文详细介绍了国内外被动微波遥感土壤湿度研究进展，凝练了被动微波遥感土壤湿度理论研究方法。在此基础上，根据我国东北地区区域特色，利用电磁波传播理论，结合地基被动微波遥感实验，深入开展了植被覆盖下土壤微波辐射模型的研究，重点开展了东北典型农作物玉米耕地、吉林西部盐碱地土壤湿度的被动微波遥感反演研究工作，取得了如下几方面创新性研究成果：（1）根据空间自相关函数与功率谱密度的傅里叶变换对关系，提出了一种利用笔束天线微波辐射计测量地表功率谱密度，通过傅氏变换得到表面空间自相关函数，最终解得粗糙表面粗糙度参数（表面均方根高度与空间自相关长度）的方法。（2）根据能量守恒定律，通过离散化方法建立了周期性结构表面的微波辐射模型。利用该模型进行表面发射率模拟，揭示出周期性表面微波辐射具有方向性的特点，该表面微波发射率与平坦表面的差异与垄的结构参数（垄高、垄周期）有关。利用多角度亮度温度的土壤湿度反演结果证实了周期性表面对土壤湿度反演精度存在影响这一观点，并且考虑周期性表面模型能够提高土壤湿度反演精度。（3）根据地基长时间系列遥感实验数据，利用零阶微波辐射传输模型进行了不同生长季玉米冠层覆盖下的农田土壤湿度反演研究，通过比较四种反演模式的反演结果，发现即使在植被冠层覆盖下周期性表面模型也能改进土壤湿度反演精度，同时，还发现当植被光学厚度与植被含水量呈二次幂关系时，土壤湿度反演精度能够得到改进。（4）根据盐碱土介电常数的频率响应差异，利用双频地基微波辐射计亮度温度数据实现了盐碱土土壤水分和盐分的提取，土壤湿度反演平均误差约为0.009cm3/cm3，土壤盐分反演绝对误差变化范围为0.5-12g/kg，平均绝对误差为3g/kg，这证实了利用被动微波遥感数据提取盐碱土壤参数的可行性与有效性。（5）结合蒙特卡罗方法和矩量法对农田表面后向散射系数进行模拟，结果表面后向散射系数随着土壤表面土块的增大增多而变大，且角度依赖性变小；利用双层冠层辐射传输模型，模拟了农田作物冠层后向散射系数，发现后向散射系数随着冠层含水量的增加而增大，但随着地表粗糙度的增加而降低。更多还原

【Abstract】 Soil moisture in the surface of earth is only a small part of the world’s totalamount of water, but it is link of surface water and ground water. Its change can affectthe distribution and evaporation process of surface energy, and control regional waterand energy cycle, thus it has great significance for research on hydro-meteorologicaland ecological environment. In addition, soil moisture determines available water ofcrop. Either low or high soil moisture will affect the growth of crops, and evendroughts and floods. So its temporal and spatial dynamic monitoring can serveprecision agriculture, drought early warning and crop yield estimation.Microwave can penetrate low vegetation canopy and detect shallow surface soilproperties. Besides, the complex relative permittivity of soil in the microwave domainhas high sensitivity to its moisture, thus microwave remote sensing has become themost effective technology to large scale soil moisture retrieval. This paper issupported by the CAS Knowledge Innovation Program of “the mechanism researchon soil moisture and snow parameter high-precision inversion from passivemicrowave remote sensing（”KZCX2-YW-340）. In this paper, we details the domesticand foreign progress of soil moisture inversion from passive microwave remotesensing and concises its theoretical approachs. Combined with ground-based passivemicrowave remote sensing experiment and electromagnetic wave propagation theory,we carried out in-depth research on microwave radiation model of soil coverd byvegetation and focused on soil moisture inversion from passive microwave remotesensing in the corn farmland and saline-alkali soil of Northeast China. The innovativeresearch of this paper is in the following aspects:(1) According to the relations of Fourier transform pair between spatialautocorrelation function and power spectral density, a method is proposed for surfacerough parameter estimation using pencil-beam antenna radiometer. The spatial autocorrelation function of rough surface is achieved from surface power spectraldensity measured by pencil-beam radiometer, and roughness parameter (rms heightand autocorrelation length of soil surface) is calculated from surface spatial auto corr-elation function.(2) According to the energy conservation law, microwave radiation model ofperiodic surface is established by the discrete method. The emissivity simulationresult of this model reveals that microwave radiation of periodic surface hasdirectional characteristic and the emissivity difference with a flat surface is relatedwith the ridge structure parameters (ridge height, ridge cycle). Soil moisture inversionresult from grounded and multi-angle brightness temperature confirms that the ridgestructure will affect inversion accuracy, and periodic surface radiation model willimprove soil moisture retrieval accuracy.(3) Soil moisture inversion below the corn canopy is implemented based on thelong-time series grounded remote sensing experimental data and zero-order radiationtransfer model. Compared the accuracy of four different soil moisture inversion mode,found that even in the region covered by vegetation canopy, periodic surface modelcan also improve soil moisture retrieval accuracy, and soil moisture retrieval accuracycan be improved when the relationship between vegetation optical thickness andvegetation water content was the second power function.(4) Followed on the frequency response difference of saline-alkali soil permittivity,soil moisture and salt content of saline-alkali soil are extracted from dual-frequencymicrowave brightness temperature data, the average absolute error of soil moisture isabout0.009cm3/cm3, and the average absolute error of soil salt content is about3g/kg, and the error range about0.5-12g/kg, and this confirms the feasibility andeffectiveness of saline-alkali soil parameter extraction from passive microwaveremote sensing data.(5) Combined with the Monte Carlo method and the method of moments, thesurface backscattering coefficient of cropland is simulated and the result indicates thatsurface backscattering coefficient increases with the number and size of clods, and itsangular dependence is the opposite. Based on double-layer canopy radiation transfermodel, backscattering coefficient of crop canopy is simulated, and found thatbackscattering coefficient increases with the increasing canopy water content, butdecreases with the increase of surface roughness.更多还原