GIS叠置图层方差分量的极大似然估计

针对GIS叠置中的同名点,以维希特分布密度为似然函数,提出了各图层方差分量的极大似然估计方法。该方法不依赖残差,不需要迭代就能估计未知参数和方差分量。     

Estimation of covariance matrix from geochemical data with observations below detection limits

Multivariate statistical analyses have been extensively applied to geochemical measurements to analyze and aid interpretation of the data. Estimation of the covariance matrix of multivariate observations is the first task in multivariate analysis. However, geochemical data for the rare elements, especially Ag, Au, and platinum-group elements, usually contain observations the below detection limits. In particular, Instrumental Neutron Activation Analysis (INAA) for the rare elements produces multilevel and possibly extremely high detection limits depending on the sample weight. Traditionally, in applying multivariate analysis to such incomplete data, the observations below detection limits are first substituted, for example, each observation below the detection limit is replaced by a certain percentage of that limit, and then the standard statistical computer packages or techniques are used to obtain the analysis of the data. If a number of samples with observations below detection limits is small, or the detection limits are relatively near zero, the results may be reasonable and most geological interpretations or conclusions are probably valid. In this paper, a new method is proposed to estimate the covariance matrix from a dataset containing observations below multilevel detection limits by using the marginal maximum likelihood estimation (MMLE) method. For each pair of variables, sayY andZ whose observations containing below detection limits, the proposed method consists of three steps: (i) for each variable separately obtaining the marginal MLE for the means and the variances, , , , and forY andZ: (ii) defining new variables by and and lettingA=C+D andB=C–D, and obtaining MLE for variances, and forA andB; (iii) estimating the correlation coefficient _YZ by and the covariance _YZ by . The procedure is illustrated by using a precious metal geochemical data set from the Fox River Sill, Manitoba, Canada.     

Fitting the Linear Model of Coregionalization by Generalized Least Squares

In geostatistical studies, the fitting of the linear model of coregionalization (LMC) to direct and cross experimental semivariograms is usually performed with a weighted least-squares (WLS) procedure based on the number of pairs of observations at each lag. So far, no study has investigated the efficiency of other least-squares procedures, such as ordinary least squares (OLS), generalized least squares (GLS), and WLS with other weighing functions, in the context of the LMC. In this article, we compare the statistical properties of the sill estimators obtained with eight least-squares procedures for fitting the LMC: OLS, four WLS, and three GLS. The WLS procedures are based on approximations of the variance of semivariogram estimates at each distance lag. The GLS procedures use a variance–covariance matrix of semivariogram estimates that is (i) estimated using the fourth-order moments with sill estimates (GLS₁), (ii) calculated using the fourth-order moments with the theoretical sills (GLS₂), and (iii) based on an approximation using the correlation between semivariogram estimates in the case of spatial independence of the observations (GLS₃). The current algorithm for fitting the LMC by WLS while ensuring the positive semidefiniteness of sill matrix estimates is modified to include any least-squares procedure. A Monte Carlo study is performed for 16 scenarios corresponding to different combinations of the number of variables, number of spatial structures, values of ranges, and scale dependence of the correlations among variables. Simulation results show that the mean square error is accounted for mostly by the variance of the sill estimators instead of their squared bias. Overall, the estimated GLS₁ and theoretical GLS₂ are the most efficient, followed by the WLS procedure that is based on the number of pairs of observations and the average distance at each lag. On that basis, GLS₁ can be recommended for future studies using the LMC.     

鲁西北地区土地现实生产力调查与估算

以鲁西北地区县级1∶5万土壤类型图图斑作为基础评价单元,根据农户现有的投入水平,采用“调查法”模拟分析农业土地资源的现实生产力,并与统计资料和“机制法”模型模拟结果进行对比分析。研究结果表明,现实投入水平下鲁西北地区夏玉米单产略高于冬小麦单产,对冬小麦的投入从整体上来看相当于中等投入,但又存在着区域差异。对夏玉米的投入具有南北向的差异,由南到北投入水平逐渐降低。鲁西北地区土地现实生产力以宁津县最高,庆云县最低,与“机制法”模型模拟结果比较,各县市之间土地生产潜力差距较大。由此可以说明,各县市土壤质量本身对土地年生产力的大小起着重要作用,进一步证明“调查法”能充分反映土壤在土地综合性质中的主要作用。     

Some remarks on Q-compensated sparse deconvolution without knowing the quality factor Q

The subsurface media are not perfectly elastic, thus anelastic absorption, attenuation and dispersion (aka Q filtering) effects occur during wave propagation, diminishing seismic resolution. Compensating for anelastic effects is imperative for resolution enhancement. Q values are required for most of conventional Q-compensation methods, and the source wavelet is additionally required for some of them. Based on the previous work of non-stationary sparse reflectivity inversion, we evaluate a series of methods for Q-compensation with/without knowing Q and with/without knowing wavelet. We demonstrate that if Q-compensation takes the wavelet into account, it generates better results for the severely attenuated components, benefiting from the sparsity promotion. We then evaluate a two-phase Q-compensation method in the frequency domain to eliminate Q requirement. In phase 1, the observed seismogram is disintegrated into the least number of Q-filtered wavelets chosen from a dictionary by optimizing a basis pursuit denoising problem, where the dictionary is composed of the known wavelet with different propagation times, each filtered with a range of possible values. The elements of the dictionary are weighted by the infinity norm of the corresponding column and further preconditioned to provide wavelets of different values and different propagation times equal probability to entry into the solution space. In phase 2, we derive analytic solutions for estimates of reflectivity and Q and solve an over-determined equation to obtain the final reflectivity series and Q values, where both the amplitude and phase information are utilized to estimate the Q values. The evaluated inversion-based Q estimation method handles the wave-interference effects better than conventional spectral-ratio-based methods. For Q-compensation, we investigate why sparsity promoting does matter. Numerical and field data experiments indicate the feasibility of the evaluated method of Q-compensation without knowing Q but with wavelet given.     

城市化对上海的增温效应

上海城市热岛效应很强, 并对气温增暖产生影响。利用主成份分析法从上海及其从近到远的４ 个郊县的２９ 年月平均温度资料中,提炼出影响上海气温变暖的两个主要因子：城市化影响和区域气候变化, 并从而推算出２９ 年来城市化使上海年平均温度增加约０．２０℃, 若排除郊区城镇化因子的影响后, 该值将更高一些。     

上海水源地毗邻湖库浮游植物群落结构的季节变化及其影响因子

为改善城市水源地及毗邻水域的水质管理,2019年11月至2020年11月分别在青草沙水库中央沙水域和金泽水库南白荡水域开展了4个季度的采样调查.运用综合营养状态指数(TLI(Σ))对水体营养状态等级进行综合评估,并采用主成分分析(PCA)、冗余分析(RDA)和相关性分析等方法研究了浮游植物群落特征与环境因子的关系.结果表明:中央沙和南白荡水域TLI (Σ)范围分别为57.5~59.0、54.1~56.1,2个水体均处于轻度富营养状态;两者分别鉴定出浮游植物7门104属184种、8门96属172种;蓝藻门是中央沙水域全年浮游植物构成的主要门类,其次为硅藻门、绿藻门,而南白荡浮游植物群落结构季节性演替明显,优势门类由硅藻门/隐藻门-蓝藻门-隐藻门/硅藻门变化,浮游植物细胞密度季节平均值变化范围分为3.00×10⁷~1.61×10⁸ cells/L、4.29×10⁶~6.59×10⁷ cells/L;鉴定出2个水体浮游植物的优势类群分别有4门17属、5门13属,中央沙水域全年的主要优势类群为假鱼腥藻属(Pseudanabaena)和长孢藻属(Dolichospermum),而南白荡春冬季的主要优势类群为小环藻属(Cyclotella)、隐藻属(Cryptomonas)和蓝隐藻属(Chroomonas),夏秋季主要优势类群为假鱼腥藻属、平裂藻属(Merismopedia)和微囊藻属(Microcystis);中央沙水域浮游植物群落结构变化主要与总氮、总磷、水温等环境因子有关,而南白荡主要与水温、总溶解性盐等环境因子有关,水体流通性差异对此起关键作用.     

新疆地震活动区的地磁观测与研究

新疆地区是中国最活跃的地震区之一.为了监测新疆地区潜在的强烈地震,2003年在该地区建立了N和S两个地磁测网并进行了地磁三分量测量.在N和S两个测网所选建的51个测点周围环境良好,地磁梯度小,适宜地磁测量.在野外测量中,使用性能稳定可靠的G-856磁力仪、DI磁力仪与GPS仪器,应用GPS测定方位角,DI磁力仪测量地磁偏角D与倾角I,G-856磁力仪测量总强度F.应用新疆地区乌鲁木齐与喀什地磁台站的资料,分别通化了N和S两个测网的地磁测量资料.该地磁通化值的平均标准偏差σ为:F的σf=0.20 nT;D的σd=0.06′;I的σI=0.03′,表明地磁测量资料准确可靠.根据上述地磁测量资料,应用精度高的spline方法,得到了N与S测网地磁场及其异常场的分布.结果表明,该地磁场及其异常场的分布,可以准确地描述N与S测网的地磁场及其地磁异常场.该地磁分布为今后在新疆地区的震磁研究与地震监测提供了良好的地磁参考场.     

Discussion of paper ‘Simulation of floor response spectra in shake table experiments’ by G. Maddaloni,K. P. Ryu and A. M. Reinhorn,Earthquake Engineering and Structural Dynamics 2011; 40(6): 591‐604

Three main topics including the floor motion action mechanism, the test frame design, and the target spectrum simulation presented in the paper are discussed specifically. Floor motion action mechanism is critical in understanding the seismic performance of architectural nonstructural components. Seismic sensitiveness and earthquake response properties of the nonstructural components should be considered in the design of the test frame for the shaking table test. Target spectrum simulation is also a challenging job in the shaking table test, in which dynamic characteristics of the specimen, performance of the shaking table facilities, and the control techniques should be all considered. Copyright © 2011 John Wiley & Sons, Ltd.     

南海东北部表层沉积中生源和矿物碎屑组分分析及其古环境意义

通过对南海东北部128个表层沉积样品的定量研究，揭示隆源和矿物碎屑各组分的分布，也显示了组分分析作为一种简单、快速的研究方法在海洋古环境研究中的潜力，研究区生源碎屑的分布明显受与水深相关的深海溶解作用所控制，水深3500-4000m的现代南海CCD以下，钙质生物的含量急剧减少，而硅质生物的含量急剧增加，研究区表层沉积中的碎屑矿物主要来源于亚洲大陆，吕宋镐的风化产物只起次要作用，且其分布主要受与离岸距离远近和海流相关的搬运作用所控制。