Parametric determination of the inclination of Keplerian circumstellar discs from spectropolarimetric profiles of scattered lines

Polarimetric line profiles arising from the Doppler redistribution of monochromatic stellar line radiation, Thomson scattered in a Keplerian rotating circumstellar disc are presented. It is shown that analysis of the scattered line profiles at different wavelengths which, due to Doppler redistribution, sample different disc regions allows the disc inclination to be determined.     

DEPENDENCE BETWEEN FUSION TEMPERATURES AND CHEMICAL COMPONENTS OF A CERTAIN TYPE OF COAL USING CLASSICAL,NON-PARAMETRIC AND BOOTSTRAP TECHNIQUES

A statistical study of the dependence between various critical fusion temperatures of a certain kind ofcoal and its chemical components is carried out.As well as using classical dependence techniques(multiple,stepwise and PLS regression,principal components,canonical correlation,etc.)together withthe corresponding inference on the parameters of interest,non-parametric regression and bootstrapinference are also performed.     

2020年7月12日唐山5.1级地震前高光谱多参数异常特征分析

基于高光谱遥感数据,通过RST算法提取2020年7月12日唐山5.1级地震前不同参数异常信息,发现震前CH₄、CO、H₂O、O₃均出现了高值异常,且异常均位于震中附近,异常幅度高于2倍均方差,CH₄、CO、H₂O异常机理不同于O₃。通过统计2018—2020年CH₄、CO、H₂O三种气体出现频次,发现同步异常具有可靠性,认为高光谱多参数异常出现的同步性,可提高异常性质判定的信度。通过对不同参数进行连续跟踪观测,提取多参数同步异常信息,对地震短临预报具有一定参考意义。     

岩体多尺度异质性及其力学行为

异质性是岩体的重要属性之一,从岩体的物质组成到结构特征,再到微宏观力学行为表现,异质性现象普遍存在。本文在梳理已有研究成果的基础上,从岩体的细微观异质性、结构面异质性和宏观异质性3个不同的尺度,对异质性的产生原因、表现特征、力学效应和时空演化规律等进行阐述,并介绍了相关研究方法以及异质性在不同尺度上的差异表现。岩体异质性的研究,是岩体工程地质力学理论体系的延伸,而多尺度的研究方法也成为全面揭示岩体变形破坏机制的一种有效手段。     

地下浅部异质体对表面波场谱扰动分析

均匀半无限体中表面源激发近表面波场由瑞利波主导,当浅部存在异质体,前行瑞利波发生散射,异质体周围表面波场响应谱发生变化。当异质体长度相对波长较大时,由异质体上方表面质点响应谱提取绕射波频散曲线可分析异质体与周围介质刚度差异对绕射波传播特性的影响。与含软层或硬层半无限体中瑞利波特性比较,可以发现绕射波具有与瑞利波类似的传播特性。异质体上方谱变化特征与异质体和周围介质间刚度差异有关,本研究基于异质体绕射波与入射瑞利波位移结构差异解释谱变化现象。结果表明：异质体上方谱与周围谱明显不同,在偏移距−波长域,相对于前方波场,软质体上方谱密度整体呈减弱趋势,硬质体上方谱密度整体呈增强趋势。根据谱密度变化对应偏移距、波长及谱密度强弱,可以预估异质体在传播方向的位置、埋深,并识别异质体类型。     

3维场景植被冠层多波段模拟研究进展

植被冠层辐射散射信号中蕴含了丰富的植被信息,通过构建植被冠层辐射散射模型,可以实现植被结构等生物物理参数的遥感定量反演。迄今为止,可见光/近红外、热红外、微波波段均已发展了大量的模型,这些模型在参数反演方面各具优势,但不同波段的模型又有其自身的局限性。跨波段的联合模拟可以实现模型间的优势互补,进而提高地表参数的反演精度,近年来已有学者专注于可见光/近红外与热红外模型,热红外与微波模型,主被动微波模型,以及可见光/近红外与微波模型的联合模拟和协同反演,但多是两两联合,且主要是基于经验模型或解析模型。基于3维场景的植被冠层辐射散射特性模拟模型可以细致刻画不同组分的结构和空间分布特征,对于由植被结构引起的多次散射和组分比例变化的考虑具有优势。本文主要介绍了3维模拟模型在可见光/近红外、热红外和微波波段,以及跨波段联合模拟方面的研究进展,从模型机理、场景统一、以及组分理化参数的统一的角度,探讨了构建多波段3维模拟系统的可行性,展望了多波段3维模拟模型的发展趋势。     

Mapping degraded grassland on the Eastern Tibetan Plateau with multi-temporal Landsat 8 data — where do the severely degraded areas occur?

The Tibetan Plateau in Western China is the world’s largest alpine landscape, sheltering a rich diversity of native flora and fauna. In the past few decades, the Tibetan Plateau was found to suffer from grassland degradation processes. Grassland degradation is assumed to not only endanger biodiversity but also to increase the risk for natural hazards in other parts of the country which are ecologically and hydrologically connected to the area. However, the mechanisms behind the degradation processes remain poorly understood due to scarce baseline data and insufficient scientific research.We argue that remote sensing data can help to better understand degradation processes and patterns by: (1) identifying the distribution of severely degraded areas and (2) comparing the patterns of key spatial attributes of the identified areas (altitude above sea level, aspect, slope, administrative districts) with existing theories on degradation drivers. Therefore, we applied four Landsat 8 images covering large portions of the three counties Jigzhi, Baima and Darlag in the Eastern Tibetan Plateau. The dates of the Landsat scenes were selected to cover differing phenological stages of the ecosystem. Reference data were collected with a remotely piloted aircraft and a standard consumer RGB camera. To exploit the phenological information in the Landsat data as well as deal with the problem of cloud cover in multiple images, we developed a straightforward PCA-based procedure to merge the Landsat scenes. The merged Landsat data served as input to a supervised support vector machine classification which was validated with an iterative bootstrap procedure and an additional independent validation set. The considered classes were “high-cover grassland”, “grassland (including several stages of grassland vitality)”, “(severely) degraded grassland”, “green shrubland”, “grey shrubland”, “urban areas” and “water bodies”. Kappa accuracies ranged between 0.84 and 0.93 in the iterative procedure, while the independent validation led to a kappa accuracy of 0.76. Mean producer’s and user’s accuracies for all classes were higher than 80%, and confusion mainly occurred between the two shrubland classes and between the three grassland classes.Analysis of the slope, aspect and altitude values of the vegetation classes revealed that the degraded areas mostly occurred at the higher altitudes of the study area (4300–4600 m), with no strong connection to any specific slope or aspect. High-cover grassland was mostly located on sunny slopes at lower altitudes (less than 4300 m), while shrubland preferred shady, relatively steep slopes across all altitudes. These observations proved to be stable across the examined counties, while the proportions of land-cover classes differed between the examined regions. Most counties showed 5–7% severely degraded land cover. Darlag, the county located at the edge of the permafrost zone, and featuring the highest average altitude and lowest annual temperature and precipitation, was found to suffer from larger areas of severe degradation (14%).Therefore, our findings support a strong connection between degradation patterns and climatic as well as altitudinal gradients, with an increased degradation risk for high altitude areas and areas in colder and drier climatic zones. This is relevant information for pastoral management to avoid further degradation of high altitude pastures.     

京津冀及周边地区冬季能见度与PM2.5浓度和环境湿度的多元回归分析

2013年至今,中国冬季与雾霾相伴的低能见度事件频发,京津冀及周边地区尤为严重。PM_2.5浓度与环境湿度是导致低能见度的最关键影响因素。为了深入研究PM_2.5浓度与环境湿度对大气能见度的影响,利用2017年1月京津冀及周边地区MICAPS气象数据与PM_2.5观测数据,运用天气学诊断分析方法讨论了不同相对湿度下PM_2.5浓度、环境湿度对冬季能见度变化的相对贡献,按照地理环境与污染程度差异将京津冀及周边地区划分为北京-天津地区与河北-山东地区,建立了PM_2.5浓度与环境湿度（由露点温度、温度代表）对能见度的多元回归方程,并对2015、2016、2018、2019年冬季能见度进行了回算检验。结果显示:相对湿度低于70%、PM_2.5浓度低于75 μg/m3时,北京-天津地区与河北-山东地区能见度多高于10 km,PM_2.5浓度升高是此时能见度迅速降低的主导因素;相对湿度从70%上升至85%和PM_2.5浓度从75 μg/m3升高200 μg/m3的共同作用导致了能见度降低到10 km至5 km;能见度进一步从5 km下降至2 km则更多依赖于相对湿度进一步从85%升高至95%,PM_2.5浓度与此时能见度相关减弱;能见度降低至2 km甚至更低主要是由于水汽近饱和状态下（相对湿度95%以上）的雾滴消光引起,与PM_2.5浓度的变化关系不大。与不分组直接拟合相比,以相对湿度85%为界线,分别拟合能见度能够很大程度优化多元回归模型,相对湿度高于85%时能见度拟合值的均方根误差从9.2和5.2 km下降至0.5和0.7 km,5 km以下拟合能见度的误差大幅度减小。按相对湿度85%将数据分组所得的拟合方程对2015、2016、2018、2019年1月能见度估算结果较好,观测值与拟合值相关系数均高于0.91,为雾-霾数值预报系统提供了新的能见度参数化算法。      

基于MonoRTM模型的微波辐射计反演方法研究

基于辐射传输模型MonoRTM计算天空亮温度,使用多元线性统计回归方法和BP神经网络方法分别对大气温度和水汽密度廓线进行了反演,检验并分析了两种方法的反演精度.结果表明,多元线性回归方法反演的温度偏差总体不大于6K,反演的水汽密度偏差小于4 g/m3;神经网络方法反演的温度偏差小于2K,反演的水汽密度误差总体不大于2 g/m3.与探空数据的对比表明,对于大气温度和水汽密度反演,BP神经网络方法的反演结果都要比多元线性回归方法的反演结果更接近探空资料值.