ArcGIS点符号库向QGIS平台迁移的实现

地图符号在各GIS平台之间存在的差异导致符号交换、共享困难, 本文以点状地图符号为基础, 分析了ArcGIS与QGIS平台中常用地图符号的格式结构差异; 通过Python编程设计符号转换方式, 将TTF转换为SVG图片格式, 使用标记组合的方法完成点符号制作。通过该方法转换的QGIS点状地图符号具备与ArcGIS相同的功能, 转换后的符号能够满足QGIS的制图要求, 实现了由ArcGIS到QGIS平台的点符号完整迁移, 节省了人工制作符号所消耗的时间。本文提出的符号转换方法在实际应用中能够满足地震行业相关业务需求, 在其他行业和GIS制图领域也具有良好的发展前景。     

昭通大山包天文气象条件统计分析

采用云南省昭通市昭阳区气象局1960年到1988年间在大山包实地采集的气象数据资料,并根据优良太阳观测台址所要求的各项参数指标,对大山包29年来的气象资料进行了系统的统计分析,发现该候选址点在干季(10月到次年4月)具有年日照时间增长、云量减少、相对湿度降低、风速较小且风向稳定、气候变化具有明显的周期性等特征。考虑到交通条件便利,初步判定它是一个具有潜力的优良太阳观测候选址点。     

硫化物Rb-Sr同位素定年研究进展

针对金属矿床成矿年代确定混乱的问题,国内外许多矿床学家和同位素地球化学家对金属矿物常规同位素定年方法进行了有益的探索研究,尤其是对于矿石矿物以闪锌矿、方铅矿和黄铁矿为主的铅锌矿床,硫化物矿物Rb-Sr同位素定年方法显示出了其独特的优势。结合近几年开展的工作,总结国内外硫化物Rb-Sr同位素定年研究取得的成果、闪锌矿中Rb、Sr的赋存状态与定年机理以及定年适应性问题。采用闪锌矿Rb-Sr同位素组成数据拟合成等时线源自热液流体与闪锌矿之间Rb和Sr的不同分异作用,但并不是所有的闪锌矿均适合该定年技术。要成功获得年龄,需结合野外地质特征采集代表性的矿石样品,并在镜下鉴定基础上挑选合适的单矿物;在分析测试过程中,需尽可能去除次生包裹体和粘土矿物。     

山西轩岗矿区焦家寨井田构造特征及形成机制

轩岗矿区焦家寨井田位于宁武煤田东北部,构造位置上处在山西块体北部中段、吕梁山凸起和恒山-五台山隆起之间,属于宁（武）-静（乐）向斜组成单元之一,本井田地处该向斜东北仰起端的东南翼上。经地面勘察及井下揭露,井田发育有两组断层,一组与地层及煤层倾向一致,另一组与煤层倾向相反;上、下煤组中的断层产状相近,但互不连通,发育程度也有差异;井田内岩层层面上的滑动痕迹随处可见,层间断层发育,综合评价井田地质构造复杂程度为中等-复杂。由于井田构造断层发育,将成为现代化机械采煤的重大障碍,直接影响矿井生产,因此加强断层预测工作,对矿井建设及生产具有一定指导意义。     

基于FFT分形滤波的地球化学异常信息提取

本文尝试采用多重分形方法分析地球化学数据作快速傅里叶变换后的功率谱数据,确定区域背景和局域背景的截止频率,并使用此频率对原始数据分别做低通滤波处理以提取异常信息.传统统计方法确定的异常范围最大,且在测区东部出现了一条南北走向的异常区,主要原因是前期对原始数据进行了迭代剔除,异常下限的确定并非由全部数据而是由背景数据确定;区域背景提取由于背景值是动态的,可以还原测区地球化学场的空间结构,提取的异常范围更小,浓集趋势更明显;局域背景提取的异常由于受高背景值控制,出现在测区东部的异常消失,异常范围和强度也均不及区域背景提取的异常大.     

Verification of a 3-D LiDAR Viewer for Discontinuity Orientations

Light detection and ranging (LiDAR) scanners are increasingly being used to measure discontinuity orientations on rock cuts to eliminate the bias and hazards of manual measurements which are also time consuming and somewhat subjective. Typically LiDAR data sets (point clouds) are analyzed by sophisticated algorithms that break down when conditions are not ideal, for example when some of the discontinuities are obscured by vegetation, or when significant portions of the rock face are composed of fractured facets, weathering generated surfaces, or anything that should not be identified as a discontinuity for the purposes of slope stability analysis. This paper presents a simple LiDAR point cloud viewer that allows the user to view the point cloud, identify discontinuities, pick three points on the surface (plane) of each discontinuity, and generate discontinuity orientations using the three-point method. Additionally, a test of our 3-D LiDAR viewer for discontinuity orientations on rock cuts in the United States of America and Canada is presented.     

2020年中国大陆地震灾害损失述评

本文在统计分析2020年中国5.0级以上地震目录的基础上,结合有关省（自治区、直辖市）地震局地震灾害损失评估资料,总结2020年中国大陆地震灾害情况和主要特点。总体全年地震灾害程度较轻,但小震致灾致亡的现象突出。将1991—2020年中国大陆地震灾害相应数据和特性进行比较,得到中国大陆致灾地震频次、伤亡情况和经济损失变化趋势。     

The role of nonlinearities associated with air-sea coupling processes in El Nino’s peak-phase locking

We use conditional nonlinear optimal perturbation(CNOP)to investigate the optimal precursory disturbances in the ZebiakCane El Nino-Southern Oscillation(ENSO)model.The conditions of the CNOP-type precursors are highly likely to evolve into El Nino events in the Zebiak-Cane model.By exploring the dynamic behaviors of these nonlinear El Nino events caused by the CNOP-type precursors,we find that they,as expected,tend to phase-lock to the annual cycles in the Zebiak-Cane model,with the SSTA peak at the end of a calendar year.However,El Nino events with CNOPs as initial anomalies in the linearized Zebiak-Cane model are inclined to phase-lock earlier than nonlinear El Nino events despite the existence of annual cycles in the model.It is clear that nonlinearities play an important role in El Nino’s phase-locking.In particular,nonlinear temperature advection increases anomalous zonal SST differences and anomalous westerlies,which weakens anomalous upwelling and acts on the increasing anomalous vertical temperature difference and,as a result,enhances El Nino and then delays the peak SSTA.Finally,we demonstrate that nonlinear temperature advection,together with the effect of the annual cycle,causes El Nino events to peak at the end of the calendar year.     

An event-based spatiotemporal data model (ESTDM) for temporal analysis of geographical data

Abstract

Representations historically used within GIS assume a world that exists only in the present. Information contained within a spatial database may be added-to or modified over time, but a sense of change or dynamics through time is not maintained. This limitation of current GIS capabilities has recently received substantial attention, given the increasingly urgent need to better understand geographical processes and the cause-and-effect interrelationships between human activities and the environment. Models proposed so-far for the representation of spatiotemporal data are extensions of traditional raster and vector representations that can be seen as location- or feature-based, respectively, and are therefore best organized for performing either location-based or feature-based queries. Neither form is as well-suited for analysing overall temporal relationships of events and patterns of events throughout a geographical area as a temporally-based representation.

In the current paper, a new spatio-temporal data model is proposed that is based on time as its organizational basis, and is thereby intended to facilitate analysis of temporal relationships and patterns of change through time. This model is named the Event-based Spatio Temporal Data Model (ESTDM). It is shown that temporally-based queries relating to locations can be implemented in an efficient and conceptually straightforward manner using ESTDM by describing algorithms for three fundamental temporally-based retrieval tasks based on this model: (1) retrieving location(s) that changed to a given value at a given time, (2) retrieving location(s) that changed to a given value over a given temporal interval, and (3) calculation of the total area that has changed to a given value over a given temporal interval. An empirical comparison of the space efficiency of ESTDM and compressed and uncompressed forms of the ‘snapshot’ model is also given, showing that ESTDM is also a compact representation of spatio-temporal information.