青海南山吾口侵入岩体锆石U-Pb年代学、地球化学特征及其地质意义

本文对青海南山吾口正长花岗岩和花岗闪长岩进行了岩石学、岩石地球化学及年代学研究。首次测得吾口侵入岩体正长花岗岩的锆石206Pb/238U年龄为253. 8±3. 3Ma(MSWD=0. 96),形成时代为晚二叠世。岩石中Al_2O_3为(14. 13～16. 51)×10~(-2),K_2O为(1. 66～3. 59)×10~(-2),A/NK=1. 15～2. 35,A/CNK=0. 75～1. 03,TFe O/(TFe O+MgO)=0. 53～0. 81,岩石具偏铝质中-高钾钙碱性花岗岩特征;吾口岩体表现为富集大离子亲石元素Rb、K等,亏损高场强元素Nb、Ta、Ba等;轻重稀土分异较明显,具右倾特征,中等负Eu异常(δEu=0. 44～0. 68),具壳幔岩浆混合特征。吾口岩体代表了阿尼玛卿洋盆向北削减俯冲运动在青海南山构造带与西秦岭造山带和南祁连造山带的构造转换衔接部位的构造演化的地质记录。该侵入岩体形成时代及构造环境的确定,为研究印支早期青海南山构造演化及动力学机制提供重要依据。     

气候学发展历程的回顾与若干启示

在人类对气候的漫长认知过程中,因涉及学科之广、贡献人物之多、关键事件之复杂导致后人试图完整准确地把握其脉络走向的努力极为困难。这就使得梳理古今中外几千年以来气候学的发展进程变得尤为重要,也成为气候学学科建设不可或缺的重要组成部分。本文试图在前人大量研究成果基础上,回顾气候学发展历程中的重要事件和关键人物,以时间脉络为主线,勾画出人类认识气候的基本轮廓,并以此为基础探讨其对当代气候学发展的启示。     

基于变交摄影的隧道3D重建方法

针对传统的正直摄影整体精度低和交向摄影效率差的缺点,该文提出了一种新的摄影方式——变交摄影。采用变交摄影方式对隧道表面信息进行图像采集,利用三维场景结构恢复(SFM)技术理论进行隧道的3D重建。结果表明变交摄影具有高效率、高精度的优点。将变交摄影3D重建结果与Leica激光扫描仪测量结果进行了对比分析,数据表明变交摄影三维重建模型具有较高精度。     

一种基于属性值变化程度定权的聚类算法

针对经典K-means聚类算法以欧氏距离作为相似度判断法则进行聚类划分,而未考虑聚类对象的各属性值对聚类划分的影响程度存在差异的问题,该文提出了一种基于属性值变化程度定权的聚类算法。通过采用Iris dataset数据进行实验,该算法相对于其他聚类算法获得了更好的聚类效果,且该算法适用于生物物种分类、遥感影像识别等工作领域,能提高聚类运算的精准度。     

能源富集区产业结构时空差异及演化

针对能源富集区产业结构时空差异与演化分析不足的问题,该文运用利用HHI指数、空间基尼系数和产业结构差异系数对1995—2014年陕甘宁蒙能源富集区产业结构的时空格局差异及演化特征进行研究。结果表明:1995—2014年能源富集区第二产业比重第三产业比重第一产业比重,表现为"二三一"产业结构模式,是典型的以第二产业为主导的产业结构;1995—2014年陕甘宁蒙能源富集区第一产业集聚程度围绕0.04呈现小幅度变化趋势,第二、三产业的集聚程度下降趋势明显;通过考虑经济总量的分析,发现各次产业相对量仍呈集中态势,得出陕甘宁蒙能源富集区县域三次产业相对集中的结论;能源富集区三次产业结构的空间差异性不显著,年际变化较小,能源富集区需要加快推进产业结构优化升级以带动经济的可持续发展。     

Analysis of estimated satellite clock biases and their effects on precise point positioning

This study provides a systemic analysis to identify the biases in estimated satellite clocks and illustrates their effects in precise point positioning (PPP). First, the precise satellite clock estimation method considering pseudorange and carrier phase hardware delays is derived. Two methods for satellite clock estimation are compared, and their equivalency is discussed. The results show that apart from the well-known constant code hardware biases, the time-variant phase hardware biases are also absorbed by the estimated clocks. Also, the satellite clocks contain biases caused by modeling errors. To analyze the effects of these biases, they are grouped into initial clock biases (ICBs) and time-dependent biases (TDBs). Then, a detailed analysis of the impact of the biases on PPP-based troposphere and coordinate estimates is conducted. The experimental analysis demonstrates that TDBs affect positioning and tropospheric estimates, and their impacts are more significant in the static mode. The ICBs affect coordinate accuracy, zenith total delay mean bias, and its standard deviations only at the millimeter level for kinematic and static PPP, which is negligible. However, the ICBs affect the convergence period for both static and real kinematic PPP, and the magnitude of their impact largely depends on data quality. Note that satellites clocks are generally estimated with the P1/P2 and L1/L2 ionospheric-free combinations, and that hardware-specific parts of ICBs and TDBs cancel if users employ the same type of observables as the clock providers. Otherwise, the effects of biases cannot be ignored, especially for triple-frequency applications. Also, modeling-specific parts of ICBs and TDBs are significant in real-time clocks, which also affect user applications. Our conclusion is applicable for understanding the effects of these biases.     

Mapping fine‐scale urban housing prices by fusing remotely sensed imagery and social media data

The accurate mapping of urban housing prices at a fine scale is essential to policymaking and urban studies, such as adjusting economic factors and determining reasonable levels of residential subsidies. Previous studies focus mainly on housing price analysis at a macro scale, without fine‐scale study due to a lack of available data and effective models. By integrating a convolutional neural network for united mining (UMCNN) and random forest (RF), this study proposes an effective deep‐learning‐based framework for fusing multi‐source geospatial data, including high spatial resolution (HSR) remotely sensed imagery and several types of social media data, and maps urban housing prices at a very fine scale. With the collected housing price data from China's biggest online real estate market, we produced the spatial distribution of housing prices at a spatial resolution of 5 m in Shenzhen, China. By comparing with eight other multi‐source data mining techniques, the UMCNN obtained the highest housing price simulation accuracy (Pearson R = 0.922, OA = 85.82%). The results also demonstrated a complex spatial heterogeneity inside Shenzhen's housing price distribution. In future studies, we will work continuously on housing price policymaking and residential issues by including additional sources of spatial data.     

地理国情普查数据库管理系统设计

针对省级地理国情普查数据库数据海量、种类多样、更新持续、应用广泛等特征,本文提出一种集地理国情普查数据库建库、更新与应用于一体的数据库管理系统设计方案。研究在分析现有地理国情普查数据库特点的基础上,从总体设计思想、系统架构、运行模式、接口设计等几个方面进行探讨,期望为各级地理国情普查数据库管理系统建设提供借鉴。     

河流湖泊湿地边界定位中遥感影像时相选择方法

选择高分遥感影像的时相是利用高分遥感影像精确定位湖泊河流湿地自然边界的关键问题之一。在没有或缺少水文观测数据的情况下,依据河流湖泊湿地的定义,本文提出了一种用于河流湖泊湿地边界定位的高分遥感影像时相快速选择方法,试验结果表明该方法合理、准确、有效。