Initiation of large-volume silicic centers in the Yellowstone hotspot track: insights from H<Subscript>2</Subscript>O- and F-rich quartz-hosted rhyolitic melt inclusions in the Arbon Valley Tuff of the Snake River Plain

During the onset of caldera cluster volcanism at a new location in the Snake River Plain (SRP), there is an increase in basalt fluxing into the crust and diverse silicic volcanic products are generated. The SRP contains abundant and compositionally diverse hot, dry, and often low-δ¹⁸O silicic volcanic rocks produced through time during the formation of individual caldera clusters, but more H₂O-rich eruptive products are rare. We report analyses of quartz-hosted melt inclusions from pumice clasts from the upper and lower Arbon Valley Tuff (AVT) to gain insight into the initiation of caldera cluster volcanism. The AVT, a voluminous, caldera-forming rhyolite, represents the commencement of volcanism (10.44 Ma) at the Picabo volcanic field of the Yellowstone hotspot track. This is a normal δ¹⁸O rhyolite consisting of early and late erupted members (lower and upper AVT, respectively) with extremely radiogenic Sr isotopes and unradiogenic Nd isotopes, requiring that ~50 % of the mass of these elements is derived from melts of Archean upper crust. Our data reveal distinctive features of the early erupted lower AVT melt including: variable F concentrations up to 1.4 wt%, homogenous and low Cl concentrations (~0.08 wt%), H₂O contents ranging from 2.3 to 6.4 wt%, CO₂ contents ranging from 79 to 410 ppm, and enrichment of incompatible elements compared to the late erupted AVT, subsequent Picabo rhyolites, SRP rhyolites, and melt inclusions from other metaluminous rhyolites (e.g., Bishop Tuff, Mesa Falls Tuff). We couple melt inclusion data with Ti measurements and cathodoluminescence (CL) imaging of the host quartz phenocrysts to elucidate the petrogenetic evolution of the AVT rhyolitic magma. We observe complex and multistage CL zoning patterns, the most critical being multiple truncations indicative of several dissolution–reprecipitation episodes with bright CL cores (higher Ti) and occasional bright CL rims (higher Ti). We interpret the high H₂O, F, F/Cl, and incompatible trace element concentrations in the context of a model involving melting of Archean crust and mixing of the crustal melt with basaltic differentiates, followed by multiple stages of fractional crystallization, remelting, and melt extraction. This multistage process, which we refer to as distillation, is further supported by the complex CL zoning patterns in quartz. We interpret new Δ¹⁸O(Qz-Mt) isotope measurements, demonstrating a 0.4 ‰ or ~180 °C temperature difference, and strong Sr isotopic and chemical differences between the upper and lower AVT to represent two separate eruptions. Similarities between the AVT and the first caldera-forming eruptions of other caldera clusters in the SRP (Yellowstone, Heise and Bruneau Jarbidge) suggest that the more evolved, lower-temperature, more H₂O-rich rhyolites of the SRP are important in the initiation of a caldera cluster during the onset of plume impingement.     

遥感数据在线信息分析服务技术研究

遥感数据的在线信息分析服务技术是基于在线处理技术,整合各种遥感信息和技术资源,通过标准Web Service调用方式以按需共享的方式提供遥感应用服务。本文就高分遥感数据产品的在线信息分析技术框架及信息分析结果的在线可视化系统实现展开研究,通过整合遥感数据处理算法及处理工具资源进行系统集成,并利用标准Web Service调用的方式为用户统一提供在线数据分析服务,使用户无须安装复杂处理软件就能在线对数据进行处理分析。试验结果表明,在线信息分析服务系统能稳定高效地为3—5级高分影像数据产品提供在线的数据分析功能,能有效降低行业应用高分遥感影像的难度,进一步增强了对高分遥感影像数据的应用能力。     

利用地形正规化校正反立体现象

影像目视判读常会遇到山脊与沟谷的凹凸感与现实相反的反立体现象。消除反立体现象,能有效提高非专业人员对遥感影像的正确使用。立足于反立体现象的成因,本文采用地形正规化模型来校正影像的反立体现象,推导出Lambertian、Cosine-Civco、c校正、b校正这4种地形正规化模型的反立体校正式;对这4种地形正规化模型的反立体校正效果进行了对比,并且与其他5种校正法也进行了对比。通过3个实验区的校正发现,这4种地形正规化模型均能校正反立体现象,但校正影像存在色调偏差;Lambertian、Cosine-Civco的反立体校正影像立体感较强,但影像色调改变较大,视觉效果偏差;c校正、b校正的校正影像在视觉效果和定量指标上都比较接近,基本保持地物光谱信息,校正效果相对较好。从定量指标来看,b校正的反立体校正影像的各指标值整体最小,一定程度代表b校正能取得相对较好的反立体校正效果。与其他方法的对比表明,c校正和b校正的反立体校正不局限于波段个数,在有效消除反立体现象的同时,能相对较好的保留地物光谱信息,有利于影像的定量应用。     

结合像元分解和STARFM模型的遥感数据融合

高空间、时间分辨率遥感数据在监测地表快速变化方面具有重要的作用。然而,对于特定传感器获取的遥感影像在空间分辨率和时间分辨率上存在不可调和的矛盾,遥感数据时空融合技术是解决这一矛盾的有效方法。本文利用像元分解降尺方法(Downscaling mixed pixel)和STARFM模型(Spatial and Temporal Adaptive Reflectance Fusion Model)相结合的CDSTARFM算法(Combination of Downscaling Mixed Pixel Algorithm and Spatial and Temporal Adaptive Reflectance Fusion Model)进行遥感数据融合。首先,利用像元分解降尺度方法对参与融合的MODIS数据进行分解降尺度处理;其次,利用分解降尺度的MODIS数据替代STARFM模型中直接重采样的MODIS数据进行数据融合;最后以Landsat 8和MODIS遥感影像数据对该方法进行了实验。结果表明:(1)CDSTARFM算法比STARFM和像元分解降尺度算法具有更高的融合精度;(2)CDSTARFM能够在较小的窗口下获得更高的融合精度,在相同的窗口下其融合精度也高于STARFM;(3)CDSTARFM融合的影像更接近真实影像,消除了像元分解降尺度影像中的"图斑"和STARFM模型融合影像中的"MODIS像元边界"。     

水质关键因素光谱遥感监测技术分析

针对传统水体水质分析方法过度依赖于实地测量和实验室化学分析,需要耗费大量人力物力且效率不高的问题,从水质遥感监测数据获取手段、典型反演监测模型、不同水体光谱遥感监测应用状况、水质遥感监测技术应用及前景等方面分析归纳了使用遥感技术监测水质的新方法。从可用数据类型、数据特征等方面对水质遥感监测数据获取的3种主要手段进行了比较;从复杂程度、使用场景、优缺点等方面对4种典型的反演模型进行了归纳;对遥感数据和模型在Ⅰ类和Ⅱ类水体应用中的常用组合方式进行了分析总结。     

Recursive algorithm for fast GNSS orbit fitting

Gaussian elimination is an efficient and numerically stable algorithm for estimating parameters and their precision. However, before estimating the parameters, it is often prudent to perform statistical tests to achieve the best fitting model. We use Gaussian elimination to select the best fitting model among candidate models. A succinct relationship between the weighted sum of squared residuals and the previous one is revealed by a volume formula. For quick parameter estimation and determination of weighted sum of squared residuals, a recursive elimination algorithm is proposed in the context of Gaussian elimination. In order to improve the model selection efficiency, the parameter estimation and the determination of the weighted sum of squared residuals are carried out in parallel using the proposed recursive elimination algorithm in which the improvement at each recursive stage is judged by the Bayesian information criterion. Ultimately, the computational complexity and numerical stability of the recursive elimination proposed are briefly discussed, and a GNSS orbit interpolation example is used to verify the results. It shows that the proposed recursive elimination algorithm inherits the numerical stability of the Gaussian elimination, and this algorithm can be used to examine the gain from the newly introduced parameter, dynamically assess the fitting model, and fix the optimal model efficiently. The optimal fitting model with the lowest information is very close to the real situation verified by checkpoints.     

A new method for specular and diffuse pseudorange multipath error extraction using wavelet analysis

Multipath remains one of the major challenges in Global Navigation Satellite System (GNSS) positioning because it is considered the dominant source of ranging errors, which can be classified into specular and diffuse types. We present a new method using wavelets to extract the pseudorange multipath in the time domain and breaking it down into the two components. The main idea is an analysis-reconstruction approach based on application of both continuous wavelet transform (CWT) and discrete wavelet transform (DWT). The proposed procedure involves the use of L1 code-minus-carrier (CMC) observable where higher-frequency terms are isolated as residuals. CMC residuals are analyzed by applying the CWT, and we propose the scalogram as a technique for discerning time–frequency variations of the multipath signal. Unlike Fourier transform, the potential of the CWT scalogram for examining the non-stationary and multifrequency nature of the multipath is confirmed as it simultaneously allows fine detection and time localization of the most representative frequencies of the signal. This interpretation of the CWT scalogram is relevant when choosing the levels of reconstruction with DWT, allowing accurate time domain extraction of both the specular and diffuse multipath. The performance and robustness of the method and its boundary applicability are assessed. The experiment was carried out using a receiver of Campania GNSS Network. The results are given in which specular multipath error is achieved using DWT level 7 approximation component and diffuse multipath error is achieved using DWT level 6 denoised detail component.     

Optimization and Parametrical Investigation to Assess the Reconstitution of Different Types of Indian Sand Using Portable Travelling Pluviator

By using the air pluviation technique, it is aimed to achieve the desired relative density with uniform void ratio throughout the specimen in order to maintain the homogeneity and to avoid the spatial variability. Further, in order to achieve the maximum deposition intensity, a systematic optimization study has been carried out rigorously in a test tank to determine the diameter of the orifice to be employed for the sieve plates of different porosity and the number of sieve plates to be installed in the diffuser sieve sets. The study has been conducted with four different patterns of sieves with different porosity to achieve a wide range of relative densities for four different uniformly graded Indian sands. The dynamic penetrometer which is considered to be one of the cost effective instruments has been efficiently used to determine the soil resistance at various locations of the test tank for every given height of fall in order to check the uniformity of placement density throughout the sand bed. The study reveals that the sand beds of different relative densities could be achieved using different patterns of diffuser sieves at optimum sand flow rate without compromising the uniformity. The effect of height of fall as well as porosity of diffuser sieves on the relative density of different sands has been studied in detail. The deposition intensity and the relative density obtained from the present study are compared with the values available in the literature.     

Assessment and Prediction of Liquefaction Potential Using Different Artificial Neural Network Models: A Case Study

Soil liquefaction as a transformation of granular material from solid to liquid state is a type of ground failure commonly associated with moderate to large earthquakes and refers to the loss of strength in saturated, cohesionless soils due to the build-up of pore water pressures and reduction of the effective stress during dynamic loading. In this paper, assessment and prediction of liquefaction potential of soils subjected to earthquake using two different artificial neural network models based on mechanical and geotechnical related parameters (model A) and earthquake related parameters (model B) have been proposed. In model A the depth, unit weight, SPT-N value, shear wave velocity, soil type and fine contents and in model B the depth, stress reduction factor, cyclic stress ratio, cyclic resistance ratio, pore pressure, total and effective vertical stress were considered as network inputs. Among the numerous tested models, the 6-4-4-2-1 structure correspond to model A and 7-5-4-6-1 for model B due to minimum network root mean square errors were selected as optimized network architecture models in this study. The performance of the network models were controlled approved and evaluated using several statistical criteria, regression analysis as well as detailed comparison with known accepted procedures. The results represented that the model A satisfied almost all the employed criteria and showed better performance than model B. The sensitivity analysis in this study showed that depth, shear wave velocity and SPT-N value for model A and cyclic resistance ratio, cyclic stress ratio and effective vertical stress for model B are the three most effective parameters on liquefaction potential analysis. Moreover, the calculated absolute error for model A represented better performance than model B. The reasonable agreement of network output in comparison with the results from previously accepted methods indicate satisfactory network performance for prediction of liquefaction potential analysis.     

姚家岭锌金多金属矿床围岩蚀变三维空间定量分析研究

姚家岭锌金多金属矿床是近年来在长江中下游成矿带铜陵矿集区新发现的大型多金属矿床。姚家岭锌金多金属矿床的成矿作用具有多阶段性的特点,矿床范围内围岩蚀变强烈,蚀变类型复杂多样。三维地质信息技术及三维空间分析方法为定量化分析围岩蚀变的空间分布以及与矿化之间的相关关系提供了有利工具。本文基于上述方法,有效地对姚家岭锌金多金属矿床的围岩蚀变的分带性及其与不同矿化之间的关联性行了定量分析。较之于传统研究方法,不仅能快速地对蚀变与矿化的分布特征进行分析,还能从定量的角度获取不同信息之间的规律性和相关性。本文采用的相关方法不但有助于更准确的判定蚀变分带及规律,还可为矿床的成矿模式及找矿模型的建立提供定量化的数据支持。