侵入带对视电阻率的影响

利用混合法研究了侵入带的三种模式——台阶型、斜坡型、具有低阻环带的侵入带对电位电极系视电阻率的影响。其目的, 一是确定常用的台阶型侵入带引入的误差, 二是研究细致地探测侵入带的方法。研究结果一方面表明了考虑过渡带和低阻环带可以提高测井解释的准确度,另一方面也为用多电极系电阻率测井探测侵入带提供了理论依据。     

Research on scale effect of histogram

To describe the spatial relationship among the earth objects compactly, in this paper, we raised the concept of histo-variogram based on the analysis of the characteristics of other spatial analyzing methods such as variogram, information entropy. And we also raised a new spatial analysis method of histogram decomposition based on the definition of standing pixel and contour pixel. At the end of this paper, we demonstrated the characteristics of histo-variogram by two experiments, one for spatial analysis, the other for image fusion.     

中尺度自动站数据处理系统

为了解决中尺度自动气象站建设后探测数据的应用和共享问题,利用数据库等计算机技术,开发一套自动数据处理系统。实现了数据的处理储存、灾害天气预警和数据在不同部门之间共享。     

GRAPES模式业务运行中出现的问题及成因分析

本文首先简要介绍了成都区域气象中心业务使用的GRAPES模式的运行现状,然后针对模式在业务运行中出现的问题进行了详细分析,指出了导致模式出现异常状况的原因,以及解决问题的几点建议.     

江西银山矿伊利石化过程中围岩化学成分变化及其成矿意义

江西银山热液多金属矿床矿体围岩发生了强烈的伊利石化,研究这些伊利石化是认识本矿床成矿作用的关键之一。通过伊利石的化学成分和矿体围岩蚀变前后的化学成分比较等方面的研究,本文得出以下认识:银山矿矿体围岩千枚岩、英安质流纹岩和中酸性次火山岩都发生了强烈的伊利石化,矿石与蚀变千枚岩中伊利石的化学成分最为相近。银山矿矿体蚀变围岩的化学成分以K2O的含量较高、Na2O和CaO的含量都很低(平均值都在0.11%左右)为特征,矿体围岩在伊利石化过程中Ca和Na被大量带出。综合各方面的证据推测,引起强烈伊利石化的热液是以H2O+CO2为主要组份的氧化性火山-次火山热液。     

新疆哈密大南湖地区层间氧化带特征研究

新疆大南湖地区的层间氧化带发育层位为中侏罗统西山窑组第二、三岩性段砂砾岩,以褐黄色为主;层间氧化带具多层性,埋深31～343 m,厚度2～138 m;层间氧化带分为氧化带、氧化-还原过渡带和原生带;铀矿体主产于氧化-还原过渡带中;新构造运动形成的最终构造格架控制了层间氧化带的发育方向和基本形态,不同粒度且非致密结构的砂砾岩和冲积扇相、辫状河相沉积则决定层间氧化带发育的厚度和规模,由南向北流的承压地下水造成区内层间氧化带前锋线呈向北延伸的趋势.     

压实粉土非线性应力-应变关系的试验研究

对京九线路基粉土用GDS三轴仪进行固结不排水剪试验,研究不同围压、含水量、压实度下压实粉土样的应力-应变关系。结果表明:压实粉土在低围压下为应变软化,高围压下为应变硬化,存在一个屈服应力;含水量和压实度对粉土强度和应力-应变关系影响显著,随着含水量的减小、压实度的增大,压实粉土样强度增大,应力-应变曲线上升。对围压小于屈服应力的应变软化曲线,用常规的土的软化关系式进行拟和;对围压大于屈服应力的应变硬化曲线,用邓肯-张模型进行拟和;这二者的结合能描述压实粉土的应力-应变关系曲线,效果良好。     

我国西部祁连山区的古海洋地壳及其大地构造意义

祁连山是我国西部的重要山系之一。解放后,在伟大领袖毛主席和中国共产党的英明领导下,不仅进行了大量矿产普查、勘探工作,而且广泛开展了区域地质调查,特别是无产阶级文化大革命以来,积累了丰富的实际资料。综合本区历年的地质成果,结合本人近年的实际观察,我们发现祁连山具有典型的古板块构造特点。本文试图从岩石和大地构造学出发,对祁连山古海洋地壳的空间分布和时代及其构造演化作一概略分析,并进而探讨板块构造在祁连山的细部表现。     

Spatial pattern of Abies and Picea surface pollen distribution along the elevation gradient in the Qinghai–Tibetan Plateau and Xinjiang, China

In this study we examine the relationships between Abies and Picea abundance in surface pollen and sub-alpine coniferous forest (SCF) distribution, elevation and climate in the Qinghai–Tibetan Plateau using a large modern pollen data set consisting of 857 samples. Results indicate that Abies and Picea pollen are abundant in the southern and eastern Qinghai–Tibetan Plateau, where SCF dominates the landscape. Pollen percentages of both Abies and Picea show a unimodal pattern with changes in elevation and climate, and their optima occur at elevations from 2500 to 4000 m a.s.l., mean annual temperature from −1 to 10 °C and mean annual precipitation from 450 to 850 mm. The optimal elevation of Abies and Picea pollen distribution decreases with latitude from c . 4000 m in the south (21–32°N) to c . 2500 m in the north (43–49°N). The spatial pattern of Abies and Picea pollen abundance is highly correlated with the modern distribution of these taxa, which is largely controlled by elevation and climate. These relationships could provide a practical reference for interpretation of fossil pollen data in terms of climate and elevation in the Qinghai–Tibetan Plateau.     

Optimizing support vector machine learning for semi-arid vegetation mapping by using clustering analysis

In remote sensing communities, support vector machine (SVM) learning has recently received increasing attention. SVM learning usually requires large memory and enormous amounts of computation time on large training sets. According to SVM algorithms, the SVM classification decision function is fully determined by support vectors, which compose a subset of the training sets. In this regard, a solution to optimize SVM learning is to efficiently reduce training sets. In this paper, a data reduction method based on agglomerative hierarchical clustering is proposed to obtain smaller training sets for SVM learning. Using a multiple angle remote sensing dataset of a semi-arid region, the effectiveness of the proposed method is evaluated by classification experiments with a series of reduced training sets. The experiments show that there is no loss of SVM accuracy when the original training set is reduced to 34% using the proposed approach. Maximum likelihood classification (MLC) also is applied on the reduced training sets. The results show that MLC can also maintain the classification accuracy. This implies that the most informative data instances can be retained by this approach.