LiDAR点云生成DEM的水面置平方法研究与实现

以LiDAR激光点云数据为基础,分析了水面信息自动识别和置平处理的技术方法,并使用C#语言编程实现,取得了理想的效果,在实际DEM生产过程中得到了很好的应用。     

Multi‐dimensional analyses of the SEAM controlled source electromagnetic data—the story of a blind test of interpretation workflows

Using a subset of the SEG Advanced Modeling Program Phase I controlled‐source electromagnetic data, we apply our standard controlled‐source electromagnetic interpretation workflows to delineate a simulated hydrocarbon reservoir. Experience learned from characterizing such a complicated model offers us an opportunity to refine our workflows to achieve better interpretation quality. The exercise proceeded in a blind test style, where the interpreting geophysicists did not know the true resistivity model until the end of the project. Rather, the interpreters were provided a traditional controlled‐source electromagnetic data package, including electric field measurements, interpreted seismic horizons, and well log data. Based on petrophysical analysis, a background resistivity model was established first. Then, the interpreters started with feasibility studies to establish the recoverability of the prospect and carefully stepped through 1D, 2.5D, and 3D inversions with seismic and well log data integrated at each stage. A high‐resistivity zone is identified with 1D analysis and further characterized with 2.5D inversions. Its lateral distribution is confirmed with a 3D anisotropic inversion. The importance of integrating all available geophysical and petrophysical data to derive more accurate interpretation is demonstrated.     

基于热异常信息与BP神经网络的中强地震预测试验

地震预测是地震科学研究的主要领域之一。震前热异常现象(地表温度异常升高)普遍存在并且与地震三要素有复杂的非线性关系。文中结合神经网络的优点,提出将热异常信息作为地震预测的信息源,通过构建神经网络,进行地震预测的思路,并进行了试验。基于8d合成的1km分辨率的MODIS数据,利用RST算法提取震前热异常信息,在分析震前热异常信息时空变化的基础上,确定出BP神经网络的结构,利用该网络对中国及周边100个5级以上震例,以及70个随机无震样本进行训练和仿真。试验结果表明,通过RST算法提取的震前热异常指数值,用于BP神经网络地震预测是可行的,其预测的试验结果刻画出了地震要素与热异常值间的非线性相关性。未来预测区域范围的选取以及神经网络中隐层神经元的数量将对地震预测效果产生较大的影响。     

comparison of locations of rushan earthquake swarm from large and small network

A notable swarm occurred in Rushan, Shandong Peninsula and its activities continue since Oct. 2013 till now. Up to Sept. 30, 2014, more than 7 000 events have been recorded, in which locatable shocks exceed 2000, and 18 events with M_L≥3.0. The swarm is rarely seen in East China for its extraordinary duration time and surprising high frequency of aftershocks. 18 temporary seismometers have been deployed around the swarm since May 6, 2014, and composed a seismic array for monitoring the swarm activities. Based on data from permanent networks and temporary array, we relocated the earthquake sequence by using hypoDD method. It has been shown that, there is obvious difference between permanent network results and temporary array results. The permanent network of Shandong has a relative large coverage gap(more than 200°)for this swarm. Its location results therefore should not be reliable. There are maybe other errors in the permanent network result due to some problems in the raw data, such as too few stations for most locatable events(3 stations), and relative lower proportion of located events in final result(74.3%, while 95.1% in temporary array result). It can be found by comparing location results from permanent network and temporary array that, using temporary array's data can improve the location accuracy significantly. The results of temporary array are: aftershocks distribution of Rushan swarm is in NWW direction, the dip-direction of fitted fault plane is SW, and the strike and dip angle agree with focal mechanism of the mainshock. Focal depths of aftershocks are at 4.5～8km; the swarm is restricted in a small area about 3km×3km×1km, and has some characteristics such as clustering, staged activities, and etc; the aftershock activities are in accord with crack growth behavior pattern, hence we deduced that there may be fluid intrusion in source area. Finally, we discussed the seismogenic structures and active mechanisms of this swarm combined with relative geologic knowledge. We draw some conclusions as follows: 1)Rushan swarm probably occurred at the boundary of rock bodies of Duogu Mountain and Haiyangsuo super-unit; 2)The seismogenic structure is a blind fault, which should be a part of adjacent Heishankuang-Jilincun Fault, or might be a new fault at rock body boundaries; 3)Rushan swarm might be an evidence for the existence of the disputed Shidao Fault.     

中国天山西部山区森林积雪消融过程观测分析——以巩乃斯河谷为例

通过对2013年春季中国科学院天山积雪与雪崩研究站区内阳坡无林地和阴坡不同开阔度森林内积雪深度、融雪速率以及常规气象的观测,分析了融雪期不同开阔度森林积雪的消融过程以及积雪表面能量平衡特征。结果表明:不同开阔度林冠下积雪深度具有相同的变化趋势,森林的林冠开阔度越大,林下积雪深度越大,林下积雪开始消融和完全消融的时间越晚,消融期也越长。森林积雪融雪开始和结束时间比阳坡无林地区晚20~30 d左右。融雪前期林冠开阔度越大,其林下融雪速率越小。融雪后期则森林开阔度越大,森林积雪的融雪速率越大。不同时期由于不同开阔度林冠下雪面能量收支以及雪层深度等物理特性的差异,从而使不同开阔度林冠下森林积雪融雪速率的相对大小,融雪速率最大值出现时间和日变化特征均不相同。晴天森林积雪的消融速率和日变化特征取决于净短波辐射和长波辐射变化特征。降水期间,其融雪速率的变化则主要受降水形式、降水量以及积雪深度等雪层特性的影响。     

青藏铁路格拉段典型沙害路段风沙地貌专题图编制

随着青藏铁路全线开通,风沙危害已成为影响铁路安全运营的主要环境问题之一。铁路沿线风沙危害路段主要集中在措那湖、沱沱河、北麓河等地。基于高分辨率卫星遥感影像QuickBird数据,通过野外实地勘察,同时参考Google Earth影像和DEM数据,绘制了3个典型沙害路段的风沙地貌专题图,地貌图比例尺为1:50000,采用二级分类系统,一级类为6个,共包含18个二级类。由于青藏铁路地处西风带中部急流区,风力强劲;铁路沿线生态环境脆弱、地表类型复杂,冻融和风蚀时空交错,地表沙物质丰富,风沙活动强烈而频繁,铁路沙害正呈现出迅速增长的态势。鉴于此,很有必要绘制青藏铁路沿线风沙灾害现状及防治措施布局的专题地图,为科学合理地制定青藏铁路沿线风沙危害综合防护体系提供依据。     

长江经济带开发与保护空间格局构建及其分析路径

长江流域经济—社会—生态系统完整,是中国国土空间开发最重要的东西轴线,在区域发展总体格局中具有重要战略地位。当下,为应对全球经贸格局重组、国家与区域经济社会转型以及资源环境约束趋紧等新形势,国家提出依托长江黄金水道,构建横贯东西、辐射南北、通江达海、经济高效、生态良好的中国经济新支撑带,这就要求长江经济带形成人口资源环境协调的均衡化开发与保护格局。本文基于“点—轴”、分区式与多中心网络式等空间组织结构,明确空间格局的推演逻辑与思路。进而,在区域差异性分析与空间开发适宜性评价基础上,认为长江经济带需重点构建以“一轴两翼,三区六廊”为主体的开发格局、以“六大片区”为主体的农业发展格局、以“五大屏障”为主体的生态安全格局,并提出不同区域差异化发展导向、路径与制度建议,以及今后长江经济带空间结构需进一步研究的主要科学问题。     

黄河三角洲滨海地区植物生长季大气氮沉降动态

利用SCJ-302型降水降尘自动采样器在植物生长季对黄河三角洲滨海湿地的大气氮沉降进行监测,对沉降物中水溶性离子、干、湿沉降氮输入量、铵态氮和硝态氮在总沉降量中的贡献率及月变化动态等分析表明：黄河三角洲植物生长季,大气干、湿沉降中SO₄^2-和NO₃^-占阴离子总量的92%以上,和Na⁺和Ca²⁺占阳离子总量的80%以上,总N沉降量约为2 264.24 mg/m²,且69%集中在降雨量较丰沛的6-8月。其中干沉降氮贡献率约为32.02%,主要集中在春季。N的湿沉降量与降雨量呈显著正线性相关（R²=0.82）,在降雨量丰沛的8月,达到最大值675.64 mg/m²。该地区大气干沉降的氮素形态以硝态氮为主,约占氮素输入量的57.21%,湿沉降中以铵态氮为主,约占氮素输入量的56.51%。植物生长季中,大气沉降中的硝态氮与铵态氮含量对表层10 cm土壤的月平均贡献率分别为约31.38%和20.50%,可见大气氮沉降是黄河三角洲滨海区域土壤主要氮素来源之一。     

乌鲁木齐霾天气PM10单颗粒物理化学特征

为了解乌鲁木齐冬季污染天气形成过程中大气颗粒物化学组分的变化,探讨霾天气快速形成的主要原因,应用扫描电镜/X射线能谱仪(SEM/EDX)对2013年2月乌鲁木齐东南郊一次典型霾天和正常天气所采集的大气颗粒物(PM₁₀)样品进行了微观形貌和化学组成的对比分析。结果表明:伴随着霾形成过程细粒子浓度呈现急剧上升趋势,PM_1.0/PM₁₀比值高达0.77。SEM/EDX观测显示,霾天形成前后,PM₁₀的形态结构和元素组成存在较明显的差异,霾天规则的石膏颗粒占规则颗粒的71.1%,明显高于正常天气,表明大气颗粒物的硫化现象比较普遍,大量硅铝酸盐飞灰说明采样点周边有较明显的燃煤源输送;二次无机颗粒组成主要为硫酸盐颗粒,由正常天气的16.1%增加到24.6%,高浓度硫酸盐与乌鲁木齐东南郊此次霾形成有密切的联系。     

长江三角洲地区制造业集群辨识及空间组织特征

本文基于投入产出表的主成分分析和企业空间分布数据的聚类分析,从产业功能联系和空间联系角度辨识长江三角洲地区主要的制造业集群,并从企业、产业、区域3个维度刻画和比较不同类型制造业集群的空间组织特征。研究表明,长江三角洲地区存在冶金及装备、电子信息、纺织及服装等12个垂直联系紧密的制造业群组,并高度集聚于沿沪宁线、沪杭线、杭甬线的“Z”字形区域。冶金及装备、电子信息和纺织及服装3个制造集群分别呈现轮辐式、卫星式和马歇尔式产业集群组织方式。上海和江苏的制造业集群在集群规模、大型企业占比、外资企业占比等方面,要明显高于浙江的制造业集群。