安徽省大气颗粒物污染特征分析

对2016年全年颗粒物监测浓度数据进行统计分析,得到了安徽省颗粒物污染的空间分布、浓度和粒径,以及污染传输特征。结果表明,淮河以北、沿江和江淮之间、长江以南和皖南山区城市颗粒物污染随地理位置不同表现出明显的区域化特征,污染程度由北向南减轻,污染过程明显表现出由北向南逐步扩散传输的规律,污染程度越重,污染深入南方的范围越广,持续时间也越长。冬季污染较重的城市,上午出现明显的高浓度时段,全天变化为"双峰双谷"型。夏、秋季节夜间细颗粒物(PM_2.5)浓度贡献比增加。PM_2.5与PM₁₀(可吸入颗粒物)质量浓度比值冬季最高,春季较低。污染重的城市冬季PM_2.5占比高。     

厘清国土“家底” 优化国土空间——山西国土空间现状分析及进一步优化的思考

十八大报告提出了"优化国土空间开发格局"的战略部署,这无疑也是建设富强美丽三晋的题中之义。优化山西国土空间开发格局,必须首先厘清国土空间的"家底":空间开发格局现状如何?与全国横向比较位次如何?与往年纵向比较变化如何?各区域空间分布如何?人均占有空间如何?开发格局如何进一步优化?本文将从国土总体空间、农用地空间、建设用地空间及生态空间等角度分别对此进行分析。一、国土空间总体情况分析从整体空间情况看,我省在全国及中部地区基本居于下游。资料显示,我省国土空间为1567万公顷,在31个省市中排第20位,约占全国的1.63%;在中部六省中排第5位,低于湖南、湖北、江西及河南,仅     

论山西孝义西河底一带山西式沉积型铁矿地质特征及成矿模式

山西式沉积型铁矿为孝义地区典型铁矿床,赋存于石炭系上统太原组底部,奥陶系中统灰岩侵蚀面之上。本文总结了该类型铁矿床的地质特征,对其成矿模式进行了概略研究。     

基于ORB-SLAM框架的直接法改进与对比

在ORB-SLAM（orientedfastandrotatedbrief-simultaneouslocalizationandmapping）框架的基础上,采用半直接视觉里程计（semi-directvisualodometry,SVO）法和稠密直接法替代特征点法,并利用慕尼黑工业大学SLAM数据集进行测试和对比。结果表明,SVO和ORB-SLAM在单目模式下的平均解算时间分别为31.1ms、20.5ms,RGB-D模式下的平均解算时间分别为39.5ms、32.5ms。某些条件下SVO解算的轨迹精度可以达到甚至高于ORB-SLAM。     

基于多源数据的全特征土地覆盖分类方法研究

以中国甘肃省张掖地区为研究区,获取了2018年3月—10月间该地区的晴天GF-4卫星数据、7月30日的哨兵二号卫星数据以及该地区的SRTMDEM（digitalelevationmodel）数据,研究探讨基于多源数据的全特征土地分类方法。结果表明,全特征的多源数据能够较好地实现土地覆盖分类,本研究区的分类精度达90.22%,并具有较好的可信度。所提出的多源数据的全特征土地分类方法为后续高分系列卫星的综合应用提供了重要的参考价值。     

基于GIS农村贫困人口空间分布及地理特征——以江西为例

当前,揭示农村贫困人口分布及地理特征成为精准扶贫的重要依据.运用人口结构指数,自然间断点分级法,空间自相关分析以及统计分析方法分析江西农村贫困人口分布特征及地理特征.研究表明:江西农村贫困人口变化大,差异大,分布非常广泛,而且极其不均衡;赣州农村贫困最为严重,并呈现高-高集聚特征,南昌农村贫困最轻;地理与江西南部高-高...     

利用多源大数据构建人才住房空间布局决策方法

利用武汉市医保数据和多源网络大数据,构建了同时顾及就业岗位分布、居住小区分布和人才住房选址偏好的城市人才住房布局规划支持方法。利用兴趣点数据和高德地图路径推荐,评价各居住小区对各就业地点和公共服务设施的可达性;根据医保数据中的居住地和就业地字段,估计不同就业群体对通勤时间和公共服务设施可达性的偏好特征;从招聘网站获取各类就业人群的潜在岗位空间分布,进而结合其偏好特征给出对应的推荐居住范围;最终综合各类职位的推荐居住范围信息,得到城市人才住房布局方案。     

Development of Geological Data Warehouse

Data warehouse (DW), a new technology invented in 1990s, is more useful for integrating and analyzing massive data than traditional database. Its application in geology field can be divided into 3 phrases: 1992-1996, commercial data warehouse (CDW) appeared; 1996-1999, geological data warehouse (GDW) appeared and the geologists or geographers realized the importance of DW and began the studies on it, but the practical DW still followed the framework of DB; 2000 to present, geological data warehouse grows, and the theory of geo-spatial data warehouse (GSDW) has been developed but the research in geological area is still deficient except that in geography. Although some developments of GDW have been made, its core still follows the CDW-organizing data by time and brings about 3 problems: difficult to integrate the geological data, for the data feature more space than time; hard to store the massive data in fifferent levels due to the same reason; hardly support the spatial analysis if the data are organized by time as CDW does. So the GDW should be redesigned by organizing data by scale in order to store mass data in different levels and synthesize the data in different granularities, and choosing space control points to replace the former time control points so as to integrate different types of data by the method of storing one type data as one layer and then to superpose the layers. In addition, data cube, a wide used technology in CDW, will be no use in GDW, for the causality among the geological data is not so obvious as commercial data, as the data are the mixed result of many complex rules, and their analysis needs the special geological methods and software; on the other hand, data cube for mass and complex geo-data will devour too much store space to be practical. On this point, the main purpose of GDW may be fit for data integration unlike CDW for data analysis.     

中太平洋海山多金属结壳的成矿特征

根据我国大洋多金属结壳的调查资料并结合其他相关的研究结果,对中太平洋海山区多金属结壳的类型,产状,成分,结构,分布等成矿特征进行了初步的研究,结果表明,中太平洋海山区富钴结壳广泛发育,但成矿特征较大地受地形,水溶,基岩类型等成矿环境因素的影响与制约。     

Geochemical Characteristics of Different Kinds of Crude Oils in the Tarim Basin,Northwest China

Based on the compositions and distributions of biomarkers in thirty-five representative oil samples, oils from the Tarim Basin of northwestern China are mainly divided into two oil families. One oil family contains relatively low amounts of C₁₅-C₂₀ isoprenoid hydrocarbons and shows pristane predominance with Pr/Ph ratios ranging from 1.50 to 3.00. The GC/MS analytical data of these oils show the occurrence of abundant hopanes, and low concentrations of steranes and tricyclic terpanes with hopanes/steranes ratios from 6.25 to 12.24 and tricyclic terpanes/hopanes ratios from 0.03 to 0.24. These oils contain low drimane relative to homodrimane (C₁₅/C₁₆ < 1.0) and abundant rearranged bicyclanes in bicyclic sesquiterpanes. They are dominated by low carbon number (C₁₉-C₂₁) compounds in the tricyclic terpanes, and are rich in rearranged hopanes, C₂₉Ts and an unknown C₃₀ compound in pentacyclic triterpanes. These geochemical characteristics suggest that the oils were generated mainly from terrigenous organic matter. The other oil family shows remarkably different biomarker compositions and distributions. The oils revealed Pr/Ph ratios of about 1.0, high drimane/homodrimane ratios (>1.0), low hopanes/steranes ratios (0.65–2.50), high tricyclic terpanes/hopanes ratios (0.30–2.00) and a dominant peak at C₂₃ in tricyclic tepanes, suggesting a marine organic origin. Oil-source rock correlation indicates that these two oil families seem to have been derived from Mesozoic Jurassic-Triassic terrestrial source rocks (shales and coal seams) and Lower Paleozoic Ordovician-Cambrian marine source rocks, respectively.