Soil moisture estimation by using multipolarization SAR image

In the past studies, different soil moisture estimation models were developed for bare soil areas by using remotely-sensed data. However, there are few models that can be used to estimate soil moisture in vegetated areas. Water Cloud Model (WCM) model is a widely used soil moisture estimation model has been developed for vegetated areas. In this study, the WCM model was extended to take soil roughness parameter into consideration. The modeling and its accuracy assessment were done by using multi-polarization Airborne Synthetic Aperture Radar (AIRSAR) images and ground data collected during field Soil Moisture Experiments.     

循环吸湿对炭纤维复合材料界面性能的影响

通过对炭纤维增强复合材料进行70、85、100℃下的循环水浸吸湿试验,研究了复合材料在不同水浸温度下的吸湿-脱湿行为规律。同时,对循环吸湿-脱湿过程中的试样进行层间剪切强度测试和动态力学性能测试,并结合扫描电镜观察循环吸湿各个阶段的纤维基体结合状态。结果表明,水浸温度越高,水分的扩散速率越快,饱和吸湿率越大。经过循环吸湿后复合材料的吸湿行为仍满足Fick第二定律,吸湿后层间剪切强度下降,湿热循环次数越多下降的越明显。脱湿后层间剪切强度有所恢复,水浸温度越高造成的不可逆破坏越大,层间剪切强度恢复的越少。干态时的玻璃化转变温度为231℃,吸湿后下降了37℃。     

SMOS与Aquarius卫星海表盐度测量方法及数据的对比分析

国际上发射的海表盐度遥感卫星主要有2颗:欧洲的SMOS和美国的Aquarius卫星,为给后续海表盐度遥感提供参考借鉴,对比分析了这2颗卫星的遥感器载荷、数据处理算法和盐度数据。遥感器载荷方面,SMOS采用L波段二维综合孔径辐射计,而Aquarius采用L波段实孔径辐射计加散射计;数据处理算法方面,分析了二者在介电常数模型、海面粗糙度校正以及反演算法方面的差异;盐度数据方面,分析了SMOS与Aquarius盐度数据之间的相关程度,并分别与ISAS(In Situ Analysis System)浮标盐度数据作对比,分析了2颗卫星的盐度数据精度。将2颗卫星的盐度遥感数据与ISAS浮标盐度数据对比发现,在全球范围内,Aquarius盐度测量精度优于SMOS;但在开阔海域,SMOS盐度测量精度优于Aquarius;而在近海岸区域,均出现较大的误差,且SMOS数据误差更大。     

负压实型铸造金属基复合材料的成型理论研究

负压实型铸造金属基复合材料的合金液前沿受到气化模气化产生的气体阻力Pc，凝固阻力Pf，毛细作用力Pc，自身重力G，纤维间的摩擦阻力f以及充型时端部紊流引起的非线性力等，其中气体的阻力，凝固阻力，毛细作用力是主要的作用力，文中通过分析影响这些作用力的因素，提出了改善合金液充填的有效途径；严格控制气化模中纤维的分布形态，使得合金液的充填速度均匀，控制浇注过程中的工艺参数，对纤维进行适当的表面处理，改善润湿性能等。     

Soil moisture mapping over the Chinese Loess Plateau using ENVISAT/ASAR data

In this paper, we used the available algorithm for soil moisture estimation over LOPEX05 (the Loess Plateau land surface process Experiment (2005)) area. The available algorithm used ENVISAT/ASAR AP mode VV polarization observational data at a low incidence angle and ground measured soil moistures. The ground measurements were performed in the summer of the 2005 during the LOPEX05 field campaign. The validated results indicate that an average difference between the soil moistures estimated from the microwave remote sensing and ground measurements is less than 0.02 cm³/cm³, with a RMS error of 2.0%, and a maximum less than 0.04 cm³/cm³. The algorithm was applied to the surface soil moisture mapping later. The results show that this algorithm is suitable for monitoring soil moisture information of the agricultural fields over the Chinese Loess Plateau, when ground land cover situation and the resolution of imagery data are taken into account. However, we also find that there are large differences over the steep slope region, the edge of mesa. The results are not acceptable for surface soil moisture estimation in these regions. Thus, the surface soil moisture retrieval in the steep slope region of the Loess Plateau need to be further investigated in the future.     

Crop parameters estimation by fuzzy inference system using X-band scatterometer data

Learning fuzzy rule based systems with microwave remote sensing can lead to very useful applications in solving several problems in the field of agriculture. Fuzzy logic provides a simple way to arrive at a definite conclusion based upon imprecise, ambiguous, vague, noisy or missing input information. In the present paper, a subtractive based fuzzy inference system is introduced to estimate the potato crop parameters like biomass, leaf area index, plant height and soil moisture. Scattering coefficient for HH- and VV-polarizations were used as an input in the Fuzzy network. The plant height, biomass, and leaf area index of potato crop and soil moisture measured at its various growth stages were used as the target variables during the training and validation of the network. The estimated values of crop/soil parameters by this methodology are much closer to the experimental values. The present work confirms the estimation abilities of fuzzy subtractive clustering in potato crop parameters estimation. This technique may be useful for the other crops cultivated over regional or continental level.     

GRACE products and land surface models for estimating the changes in key water storage components in the Nile River Basin

The Nile River Basin (NRB) is facing extreme demand for its water resources due to an alarming increase in population and the changing climate. The NRB is not compatible with ground-based in-situ observations owing to its large basin area size and limited hydrological data access from basin countries. Thus, it lends itself to remotely sensed approaches with high spatial resolution and extended temporal coverage. The Gravity Recovery and Climate Experiment (GRACE) avails a unique opportunity to investigate the changes in key components of terrestrial water storage (TWS). GRACE TWS solutions have specific tuning parameters and processing strategies that result in regionally specific variations and error patterns. We explored the TWS time series spatiotemporal changes, trends, uncertainties, and signal-to-noise ratio among different GRACE TWS data. We had also investigated the key terrestrial water storage components such as surface water, soil moisture, and groundwater storage changes. The results show that GRACE spherical harmonic solutions' uncertainty is higher than the mass concentration (mascon) over the NRB, and the Center for Space Research-mascons had the best performance. The evapotranspiration correlation (R² = 0.85) has the highest correlation with GRACE’s TWS, whereas the normalized difference vegetation index (R² = 0.82) has the second highest correlation. Notably, significant long-term (2003–2017) negative groundwater and soil moisture trends demonstrate a potential depletion of the NRB. Despite an increase in precipitation and the TWS time series, the rate of decline increased rapidly after 2008, thereby indicating the possibility of human-induced change (e.g. for irrigation purposes). Therefore, the results of this study provide a guide for future studies related to hydro-climatic change over the NRB and similar basins.     

活性稀释剂对T700/BMI复合材料湿热性能的影响

采用苯乙烯作二烯丙基双酚A(DABPA)改性双马来酰亚胺(BMI)树脂体系的活性稀释,以减小树脂的粘度。为研究苯乙烯的用量对炭纤维(T700)增强改性BMI树脂基复合材料湿热性能的影响,对T700/BMI复合材料的试样在70℃水中进行吸湿实验,并检测其力学性能。结果表明,随苯乙烯用量的增加,试样的吸湿率降低;其拉伸、弯曲和层间剪切等强度保持率也随之增大;但当苯乙烯在基体树脂中的摩尔百分含量超过20%之后,试样的拉伸强度会下降。     

T700/9916复合材料层合板恒温吸湿行为研究

研究T700/9916碳纤维增强复合材料(CFRP)层合板在湿热环境下的吸湿行为.通过测试CFRP层合板在T=70℃恒温水浴和T=70℃相对湿度为98％,91％和84％的环境下的吸湿性能,获得吸湿曲线.结果表明水浸试样相对质量增量趋于平衡时,其他各组试样的相对质量仍线性增加.使用一维Fick模型对实验结果进行分析,得到材料的理论吸湿数据比实验结果整体偏小.通过实验和有限元模拟相结合的方法计算获得材料的扩散率和溶解度,并对不同条件下的吸湿行为进行模拟,模拟结果与实验结果吻合较好,说明通过模拟能够获得材料的长期吸湿动力学曲线和试样内部的水分分布情况.     

基于GA-SVM的GNSS-IR土壤湿度反演方法

针对提高大范围土壤湿度测量精度的问题,研究了土壤湿度的全球卫星导航系统干涉测量法（GNSS-IR）,提出了一种基于支持向量机（SVM）的土壤湿度反演模型,利用遗传算法（GA）的自动寻优功能寻找SVM的最佳参数。结果表明,GA-SVM模型在测试集上得到的土壤湿度反演值与实测值的平均绝对百分比误差（MAPE）仅为0.69%,最大相对误差（MRE）为1.22%,线性回归方程决定系数达到了0.956 9。进一步与统计回归、粒子群优化的SVM模型（PSO-SVM）及反向传播（BP）神经网络方法进行对比,结果说明:在样本数目有限的情况下,GA-SVM方法更适用于土壤湿度的GNSS-IR技术反演,且反演精度较高,泛化性能良好。