基于SNA的新型集中社区公共空间网络结构优化

公共空间并非“存在即合理”。公共空间网络结构效率折射出社会网络的重构能力、社会资本的建构强度、社会秩序的重塑能力。新型集中社区作为近年大量涌现的新型居住形态,正面临社会关系重构的巨大压力。本文运用社会学的网络分析法研究公共空间网络,并对苏州新型集中社区D的公共空间网络结构进行实证分析,其结论为：公共空间网络的关联度为0.216、中心势0.358、小世界值1.978,表明空间网络整体关联度不足,呈现出破碎化的特征;商业空间整合效应的发挥受到业态配置的影响;居民社会属性对空间网络结构特征造成一定影响。最后,基于“社会—空间”互动逻辑,以社会网络重构为导向,从集中安置模式、公共空间网络优化2个层面,提出新型集中社区有待进一步研究的方向,以期为当前及未来的集中社区规划建设和公共空间整体优化提供科学合理的依据。     

从海洋内部研究海洋

几百年来,人类总是从海洋外面——在船上或者岸上研究海洋。随着技术的最新发展,人类现在可以从海洋内部来研究海洋。简要讨论了海底观测系统和活动观测平台为各领域的海洋研究提供的空前机遇,并指出中国发展海洋科学必须对这一新趋势给予密切注意。     

中国大陆科学钻探靶区深部温度预测

依据中国大陆科学钻探(CCSD)两口先导孔中地热测量和岩石样品热物性参数,对5000m深钻的可能钻遇温度进行了预测.先导孔中地温梯度介于1-26℃/km;岩石热导率变化为2.64-8.81W/(m@K),平均(3.4±1.26)W/(m@K);实测热流值为76-80mW/m2;30块岩石样品放射性生热率变化为(0.0-2.17)μW/m3,450m深度以上层平均(0.76±0.5)μW/m3,以下层段平均(0.48±0.2)μW/m3,生热率随深度递减,但变化趋势难以明确判定.分别对热流和热导率取上、下限,采用不同的生热率随深度的分布函数,区分考虑或不考虑热导率的温度相关性,分别计算出5000m深度内可能的温度分布剖面.计算结果表明,超深井于5000m垂直深度上的温度将达到110-140℃,2000m深度的探井钻遇温度将介于54-64℃.此外,考虑热导率的温度效应后预测的温度一般高于未考虑热导率温度效应5-8℃.     

庐枞火山盆地深部岩石与成矿过程

黄铁矿-硬石膏-磁铁矿矿石为典型矿石的金属矿床产于长江中下游中生代火山盆地,庐枞火山岩盆地。丰富的铁矿和黄铁矿床,主要分布在火山岩和潜火山岩里,同时也分布于盆地周边。火山岩石主要是钾玄岩-粗安岩-粗面岩组合。在深部,与它们的成分对应的岩浆岩石是碱性辉长岩-辉石二长岩-正长岩组合,如缺口辉长岩,杨山地区的辉石正长岩。火山岩和深部的辉长岩-二长岩-正长岩都经历了多次水热活动。黄铁矿-硬石膏-磁铁矿矿床主要伴随两套蚀变,即,火山岩石的大面积深色蚀变(硬石膏-辉石-长石蚀变岩)和浅色蚀变(硅化泥化)。在二长-正长岩与火山岩石的接触带,有强烈的类云英岩石(电气石-石英-云母组合)。在缺口辉长岩里,曾经发现大量磁铁矿脉(磁铁矿-方柱石-方钠石-石榴石组合)。在杨山和马口地区,正长岩里的铁矿是辉石钾长石磁铁矿组合及阳起石-磷灰石-磁铁矿组合。二长-正长岩体在盆地里广泛分布,在大范围内是几乎是层状的。调查研究表明:火山盆地底部辉长岩-二长岩-正长岩组合与铁矿有关。盆地里深部岩石和成矿作用存在有垂直分布特性。上面是喷发岩石,及潜火山岩石,下面是深部的碱性辉长岩-二长岩-正长岩杂岩体。中间有过渡带,岩墙岩席带。上面是与钾玄岩-粗安岩层和潜火山岩石里赋存的磁铁矿和黄铁矿床,下面有产于碱性辉长岩-二长岩-正长岩里也有铁矿化。蚀变岩石地质年代的初步研究发现:罗河铁矿的深部钠长石化岩石,与马口铁矿附近的正长岩石的地质年代接近(110～119Ma)。事实说明,在火山岩和潜水火山岩石里成矿作用和深部岩浆岩里成矿作用可能是同时发生的。20～435℃条件下正长岩石与水的反应动力学实验表明,在400℃左右时正长岩最容易被溶解。正长岩与水反应后,也会形成一个携带金属的流体。水岩相互作用实验提供了认识深部岩石性质的依据,有利于理解对深部的地球物理探测结果。     

Evaluation of classifiers for processing Hyperion (EO-1) data of tropical vegetation

There is an urgent necessity to monitor changes in the natural surface features of earth. Compared to broadband multispectral data, hyperspectral data provides a better option with high spectral resolution. Classification of vegetation with the use of hyperspectral remote sensing generates a classical problem of high dimensional inputs. Complexity gets compounded as we move from airborne hyperspectral to Spaceborne technology. It is unclear how different classification algorithms will perform on a complex scene of tropical forests collected by spaceborne hyperspectral sensor. The present study was carried out to evaluate the performance of three different classifiers (Artificial Neural Network, Spectral Angle Mapper, Support Vector Machine) over highly diverse tropical forest vegetation utilizing hyperspectral (EO-1) data. Appropriate band selection was done by Stepwise Discriminant Analysis. The Stepwise Discriminant Analysis resulted in identifying 22 best bands to discriminate the eight identified tropical vegetation classes. Maximum numbers of bands came from SWIR region. ANN classifier gave highest OAA values of 81% with the help of 22 selected bands from SDA. The image classified with the help SVM showed OAA of 71%, whereas the SAM showed the lowest OAA of 66%. All the three classifiers were also tested to check their efficiency in classifying spectra coming from 165 processed bands. SVM showed highest OAA of 80%. Classified subset images coming from ANN (from 22 bands) and SVM (from 165 bands) are quite similar in showing the distribution of eight vegetation classes. Both the images appeared close to the actual distribution of vegetation seen in the study area. OAA levels obtained in this study by ANN and SVM classifiers identify the suitability of these classifiers for tropical vegetation discrimination.     

对我国西南地区河谷深厚覆盖层成因机理的新认识

近年来,在我国水能资源开发过程中,发现各河流现代河床以下普遍堆积厚达数十米甚至上百米的松散堆积物。河谷深厚覆盖层的存在,不仅严重制约了工程坝址的选择,影响相关流域水电资源的开发利用,也给坝工设计带来巨大的困难。由于深厚覆盖层埋藏于现代河床之下,其形成年代一般先于一二级阶地,有悖于河流发育演化的常理,其成因一直令人费解。首次将河谷深切和深厚堆积事件与全球气候变化、海平面升降运动、地壳运动等有机地联系起来,并提出冰期、间冰期全球海平面大幅度升降,是导致河流深切成谷并形成深厚堆积的主要原因的新观点。在此基础上,引入层序地层学原理,从理论上较好地解释了全球气候变化导致海平面和河流侵蚀基准面大幅变化,并产生河谷深切和深厚堆积的原因和过程。最后,进一步将沿河大型古滑坡的孕育和发生与河谷深切事件相联系,提出沿河大型古滑坡是在河谷深切期因前缘临空较好而形成的新观点,从而对沿河古滑坡前缘剪出口高程往往低于现代河床数十米的原因给出了较合理的解释。     

Structure of residual oil as a function of wettability using pore-network modelling

In the water flooding of mixed-wet porous media, oil may drain down to relatively low residual oil saturations (S_or). Various studies have indicated that such low saturations can only be reached when oil layers in pore corners are included in the pore-scale modelling. These processes within a macroscopic porous medium can be modelled at the pore-scale by incorporating the fundamental physics of capillary dominated displacement within idealised pore network models. Recently, the authors have developed thermodynamic criteria for oil layer existence in pores with non-uniform wettability which takes as input geometrically and topologically representative networks, to calculate realistic S_or values for mixed-wet and oil-wet sandstones [16, 21]. This previous work is developed in this paper to include (i) the visualisation of the 3D structure of this residual oil, and (ii) a statistical analysis of this “residual/remaining” oil. Both the visualisation and the statistical analysis are done under a wide range of wettability conditions, which is reported for the first time in this paper.The structure of residual oil for strongly water wet systems is well known (where residual = remaining oil) and our model agrees with this but this structure changes radically for mixed wet systems (where residual ≠ remaining) and this has not yet been visualised experimentally. We find that for more water-wet systems high final residual oil saturations are reached at relatively small amounts of water injected and this oil is present in the pores as bulk oil. On the other hand, for more oil-wet systems we find a slow decrease of the amount of remaining oil with increasing amounts of injected water. During the process, the remaining connectivity of the oil phase is increasingly provided by oil layers only, hence the slow drainage. The final residual oil saturation, only reached in the theoretical limit of an infinite amount of injected water, is almost entirely contained in large number of (relatively low volume) oil layers, which are present in pores of most radius sizes.     

基于深度学习的天气雷达回波序列外推及效果分析

天气雷达探测资料是进行强对流天气临近预报的主要参考数据。针对传统雷达回波外推方法中存在资料信息利用率不足和外推时效有限的问题,文中利用神经网络进行雷达回波的外推、利用预测神经网络模型进行2 h以内的回波变化预报。回波外推问题的关键是回波时、空序列预测问题,该网络具有解决时间记忆问题的长、短时记忆单元（Long Short-Term Memory,LSTM）和提取空间特征的卷积模块。应用福建、江苏和河南多年的雷达探测资料构造训练和测试数据集。为消除降水的不平衡和提高对强回波的预报准确率,网络采用带权重的损失函数进行训练。对光流法和预测神经网络进行测试集检验以及个例分析,结果表明,在相同外推时效和检验反射率阈值的情况下,预测神经网络的临界成功指数、命中率均高于光流法,虚警率低于光流法。不同类型降水预测神经网络的SSIM值（structural similarity）均高于光流法,且层状云降水的SSIM值比对流云降水的大。因此,预测神经网络对强回波的预报能力高于光流法;在预报时效性上,预测神经网络模型具有一定的优越性;预测神经网络对层状云降水预报的准确率比对流云降水的高。      

浅谈新疆测震台网传输链路的改造

要做到IP到台站有很多种方式可选,根据新疆测震台网各台站的现状列举了7类不同的数据传输方式,这些数据传输方式在新疆测震台网中均得到应用,也都达到IP到台站的目的.分别对这些数据传输链路的原理及优缺点进行阐述,并结合目前各台站具体情况作链路适用性的相关分析,希望能够对其他省局台网的台站通信链路设计、改造起到参考.     

地理信息系统中的网络模型

社会中的很多空间现象,如交通、信息交流和生活消费品的运输等都是线性的。在ARC INFO地理信息系统(GIS)中,这些线性现象经过组织和处理,能够建立成网络及其数据库。从而可用来解决资源的合理分配和流动、交通运输中的最佳路线选择等问题。