岩石的共轭剪裂角与围压大小关系的探讨

在讨论岩石共轭剪裂角大小及其与围压大小关系的基础上,提出了以椭圆曲线近似代替岩石剪切破裂极限应力莫尔圆包络线;以椭圆短轴位置作为岩石脆性状态和韧性状态的界线,推导一组用共轭剪裂角求应力值的计算公式.通过与佩特森,卡门的岩石力学实验曲线相比较,证实椭圆曲线和有关公式可以半定量到定量地估算岩石发生剪切破裂时的瞬时极限应力值.     

IDENTIFICATION OF FINITE IMPULSE RESPONSE MODELS WITH CONTINUUM REGRESSION

The use of continuum regression(CR)for the identification of finite impulse response(FIR)dynamicmodels is investigated.CR encompasses the methods of principal component regression(PCR),partialleast squares(PLS)and multiple linear regression(MLR).PCR and MLR are at the two extremes of thecontinuum.In PCR and PLS,cross-validation is used to determine the optimum number of factors or‘latent variables’to retain in the regression model.CR allows one to vary the method in addition.Cross-validation then determines both the optimum method and the number of latent variables.The CR‘prediction error surface’—a function of the method and number of latent variables—is elucidated.Theoptimal model is defined as the minimum of this surface.Among the cases studied,the optimal modelusually comes from the region of the continuum between PCR and PLS.Few derive from the regionbetween PLS and MLR.It is also demonstrated that FIR models identified by CR have frequency domainproperties similar to those identified by PCR.     

对滇西北地区真实最小水平主应力的讨论与分析

本文对滇西北下关地区的地震地质条件和水压致裂应力测量进行了对比分析。认为二者是矛盾的,其原因可能是最小水平主应力的测值偏大。本文依据测量数据和弹性力学理论对测量结果进行了分析,发现该区浅部,垂向主应力是最小主应力,但其随深度增大而增加的速度大于最小水平主应力,400米以下深度,垂向主应力转变为中间主应力。最小水平主应力的实际值可以写为0.85+0.0227H(Mpα),这里H是深度,单位是米。该分析表明,目前水压致裂测得的最小水平主应力的误差要比预料的大。     

长江带现代地震构造应力场分布特征

根据长江带76个地震震源机制解与17个小震综合断层面解的结果统计分析,得到该带地震应力场主应力方向的优势分布。表明该带处于北东东—南东东向挤压和北北西—近南北向引张的构造应力作用之中。在力的性质上,该带水平张应力高于水平压应力,斜向压应力又高于斜向张应力,与华北地区比较,主应力方向相对向东南方向偏转,该带水平力和斜力所占比例均高于华北地区,同时讨论了该带中三个分区的现代构造应力场分布及它们的力源关系。     

High-resolution spatial assessment of population vulnerability to climate change in Nepal

Current, spatially explicit, and high-resolution assessments of population vulnerability to climate change and variability in developing countries can be difficult to create due to lack of data or financial and technical capacity constraints. We propose a comparative, multiple-approach framework to assess the spatial variation of population vulnerability to climatic changes using several high-resolution variables related to climate, topography, and socioeconomic conditions with an objective to detect the spatial variability of climate vulnerability in Nepal. Nepal is one of the most vulnerable countries to the effects of climate change due to frequent climatic hazards and poor socio-economic capacity. We used a climate vulnerability index (CVI) approach to derive climate vulnerability maps at the one-kilometer resolution and test an additive and a principal components-based composite method of data aggregation. In this work, we attempt to answer three questions. 1) How do different methods of assessment inform the spatial variation of the climate vulnerability in Nepal? 2) How do different variables interact to shape climate vulnerability in Nepal? 3) What proportions of the population in Nepal are vulnerable to climatic disasters and why? Our analysis uncovered significant spatial variations in population vulnerability to climate change across Nepal, with the highest vulnerability being experienced by the High Mountain region followed by the regions in the lower elevations. We find that although the lack of adaptive capacity is the biggest cause of population vulnerability to climate change in Nepal, a resilient community is shaped by both biophysical and socioeconomic characteristics. By performing an iterative sensitivity analysis of our thirteen variables both at the aggregate level (nationally) as well as at the more disaggregated (physiographic region) level, we contribute to identifying important, multi-scalar driving factors for vulnerability that can be employed as leverage points for lowering vulnerability at different scales. After performing analyses at multiple regions, we conclude that region-specific variable selection is needed for more detailed assessments and in order to prioritize adaptation strategies at scales that go beyond the hierarchy of administrative divisions.     

基于主成分分析的极限学习机方法开展杂卤石识别

川中地区岩性复杂,杂卤石周围广泛发育硬石膏、岩盐和其它非钾盐矿物,常规测井解释方法很难准确识别杂卤石。以极限学习机理论、主成分分析方法和测井解释为基础,把主成分分析得到的影响杂卤石识别的主变量(测井曲线)作为输入,建立极限学习机(PCA-ELM)杂卤石的精确识别模型,对比川中地区录井结果,PCA-ELM的杂卤石识别正确率达到90.74%;再以不同岩石在测井曲线上的响应特征为基础,建立杂卤石分类识别模型,分类识别正确率达到89.56%。与常规测井解释方法相比,具有速度快、操作简单、准确率高等特点。结果表明,在四川盆地钾盐勘探中PCA-ELM法是一种值得推广使用的方法。     

SHORT COMMUNICATION PLS FITS CLOSER THAN PCR

PLS1 regression is generally viewed as lying in between PCR and OLS regression.Proof is given thatthe coefficient of determination,R~2,for a PLS multivariate calibration model is at least as high as thatfor a PCR model with the same number of components.It appears that PLS can be linked to acorrelation-weighted polynomial regression of a constant response on the eigenvalues of the covariancematrix of the predictor variables.     

Field hyperspectral data analysis for discriminating spectral behavior of tea plantations under various management practices

The quality and yield of tea depends upon management of tea plantations, which takes into account the factors like type, age of plantation, growth stage, pruning status, light conditions, and disease incidence. Recognizing the importance of hyperspectral data in detecting minute spectral variations in vegetation, the present study was conducted to explore applicability of such data in evaluating these factors. Also stepwise discriminant analysis and principal component analysis were conducted to identify the appropriate bands for accessing the above mentioned factors. The Green region followed by NIR region was found as most appropriate best band for discriminating different types of tea plants, and the tea in sunlit and shade condition. For discriminating age of plantation, growth stage of tea, and diseased and healthy bush, Blue region was most appropriate. The Red and NIR regions were best bands to discriminate pruned and unpruned tea. The study concluded that field hyperspectral data can be efficiently used to know the plantation that need special care and may be an indicator of tea productivity. The spectral signature of these characteristics of tea plantations may also be used to classify the hyperspectral satellite data to derive these parameters at regional scale.     

Individual tree crown segmentation in tropical peat swamp forest using airborne hyperspectral data

Abstract

Individual tree crown segmentation is important step for deriving various information for fine-scale analysis of ecological process. However, only several studies have applied tree crown segmentation in tropical forest ecosystems, especially in mixed peat swamp forests. In this study, hyperspectral data were used to detect changes in the biochemical and biophysical characteristics, which are important factors for tree crown segmentation. Principal Component Analysis method was performed to investigate its influence on crown segmentation. Visually Selected PCs, 160 PCs and 160 Spectral Bands image were used and two segmentation techniques; Watershed Transformation and Region Growing segmentation were applied on those images. The highest accuracy was achieved for the crown segmentation is using Region Growing segmentation, based on 1:1 measurement, D value and RMSE value. The results obtained from 160 PCs image using region growing algorithm shows better accuracy with D value of 0.2 (80% accuracy, 20% error) and RMSE of 9.9 m².     

利用GPS观测资料研究山西断陷带的应变特征

利用美国麻省理工学院的GAMIT／GLOBK数据处理软件,计算获得了山西GPS观测网2001—2003年观测点在ITRF2000框架下的运动速率,并扣除了欧亚板块的整体运动。在此基础上,根据距离加权的最小二乘估计法计算了该区在2001-2003年的水平主应变,有效地避免了三角均匀应变场计算方法易受点位分布及划分网格形式的影响。得到的应变率结果显示,在山西断陷带内部,大同和运城盆地拉张较为明显,太原一临汾盆地之间呈现出一定的挤压特征,表明了山西各盆地内部区域应力场的差异以及整体构造的不连续性。