多源数据整合在地震信息上报系统中的应用

以地震信息上报系统为例,从多源数据类型、数据库构建和信息服务平台建设等方面入手,剖析了多源空间数据整合存在的诸多问题,并给出相关解决方案。结果表明,多源空间数据的整合与挖掘提高了数据可视性和利用率,从而使地震数据更好地服务于地震科研预报与应急决策。     

科学超深井硬岩取心关键技术

科学超深井是人类观测深部地球的“望远镜”。获取典型区块的原状岩心,建立高分辨率的地层剖面及其物、化性剖面,是科学钻探的最主要的目的之一。在深部钻探中,钻头驱动方式和岩心提取方法,是影响工程能源消耗、施工周期和工程经费的关键因素,从多方面阐述了科学超深井取心钻进多项关键技术和难点,并提出了针对性的解决方案和研究方向。     

基于多源数据约束的成矿动力学模拟——以宁芜盆地钟姑矿田典型矿床为例

数据驱动是大数据分析的特点之一。成矿过程的数值模拟即采用数据驱动方式,在基本的物理化学方程及地质模型基础上,通过定量的手段,模拟不同阶段、不同条件下成矿系统的演化过程,从而能够更深入、直观的讨论各种地质要素对成矿系统的影响,验证已有的成矿理论,获得新的认识。姑山铁矿床和杨庄铁矿床是宁芜火山岩盆地钟姑矿田内的典型矿床。前人研究显示,杨庄铁矿床为典型的充填-接触交代型热液矿床,而姑山铁矿床目前在成因上仍存在争议,存在岩浆成因和热液成因等多种观点。为了更好的对比和了解姑山铁矿床和杨庄铁矿床的成因及成矿过程,本文基于多源数据的综合解译剖面,采用力-热耦合数值模拟方法对与热液矿床密切相关的扩容空间的形成机制和特点开展研究。模拟结果显示,姑山铁矿床和杨庄铁矿床可能分属不同的成因类型;随着岩体的逐渐冷却,杨庄铁矿床内岩体和地层接触带会出现明显的扩容空间,可为成矿流体的汇聚及矿质的沉淀提供良好的条件,有利于热液矿床的形成;而姑山铁矿床内岩体和地层接触带只有局部区域出现扩容空间,同时体应变数值较小且形态变化大,并不利于大规模的流体汇聚及矿质的沉淀,姑山铁矿床可能主要为岩浆成因,并受少量热液的叠加改造。     

第三次全国国土调查土地利用矢量数据栅格化方法

第三次全国国土调查县级土地利用图斑层包含利用类型、耕地类型、坡度等级、种植属性等多属性信息,将县级土地利用矢量数据集成栅格化形成全国无缝的多尺度、多专题栅格产品存在一定技术难度。本文针对第三次全国国土调查土地利用栅格产品应用需求,探讨了多属性综合编码、全国基础地理网格框架、栅格化产品数据模型、矢量栅格化等技术方法,建立了全国土地利用栅格产品生产流程,开展了全国多尺度、多专题土地利用栅格产品生产验证。结果表明:本文方法能够实现第三次全国国土调查土地利用矢量图斑多属性信息集成栅格化和全国多尺度、多专题土地利用栅格产品工程化生产,可为今后的国土调查土地利用栅格产品生产和共享应用提供支撑。     

准噶尔盆地南缘中-新生界碎屑成份特征与构造期次

准噶尔盆地南缘晚侏罗世-早白垩世早期、晚白垩世及晚新生代发育的近源粗碎屑沉积显示构造活动的存在。野外剖面及镜下碎屑成份统计表明:砾岩的砾石成份、砂岩碎屑成份的物源属性主要是再旋回造山带和晚古生代的岩浆弧,但盆地南缘东段与西段的岩屑组成及物源属性存在较大的差异。其中,沉积岩岩屑在晚侏罗世—早白垩世早期、晚白垩世和晚新生代发生了相应的增加,显示盆缘沉积岩物源的隆升—剥蚀作用和构造活动的相对活跃。砂岩碎屑特征、重矿物相对含量及重矿物组合特征证明盆地南缘东、西两段的物源属性存在较大差异,特别是不稳定重矿物的增加显示晚侏罗世-早白垩世早期、晚白垩世和晚新生代为构造相对活跃的构造环境。综合中-新生界沉积碎屑特征及差异分析,准噶尔盆地南缘中-新生代盆山格局发生了3次较大的转变过程,分别对应于上述3个时期。中-新生代3次构造活动对含油气系统形成具有重要控制作用,构造活动期次与油气藏形成、调整的期次也有良好的对应关系。     

青龙村群及其地质时代

青龙村群在延边地体中具有重要地质意义。笔者通过对该群的工作和所获得的微古化石，认为青龙村群在层序上仅包含该区１：５万区调青龙村剖面中的中、下段，其上段不属于青龙村群范畴；青龙村群的形成地质时代应为晚震旦─早寒武世。     

青藏高原东部基于噪声的面波群速度分布特征

通过收集青海、甘肃、四川三省的76个地震台记录的2008年1—12月三分量的连续噪声数据,利用噪声面波层析成像的方法获得了青藏高原东部的面波群速度分布特征。首先采用多重滤波方法提取了1 000多条台站对5～50 s的三分量面波群速度频散曲线,然后将研究区域划分为0.2°×0.2°的网格,利用O ccam方法反演了瑞利波(R-R)和勒夫波(T-T)的群速度分布。反演得到的群速度分布特征与地表地质和构造特征表现出较好的相关性,清晰地揭示了地壳内部的横向速度变化。层析成像的结果显示在短周期(8～20 s)内,拥有较厚的沉积层的四川盆地表现为明显的低速特征,而青藏高原东部则表现为较高的群速度分布特征;随着周期的增加(>20 s),群速度的分布特征呈现出与短周期相反的特性,青藏高原东部下方的速度远远低于四川盆地,这可能与青藏高原东部中、下地壳低速层相关联,同时也意味着研究区域的地壳结构具有明显的横向不均匀性。在群速度分布图上,龙门山不仅是四川盆地与青藏高原的地形和构造分界带,同时也对应着高群速度与低群速度的过渡带。     

Remote Sensing Inversion for Simulation of Soil Salinization Based on Hyperspectral Data and Ground Analysis in Yinchuan,China

The Pingluo area, as an experimental study area in Yinchuan, has been subjected to major environmental degradation due to soil salinization problems. Soil salinization is one of the main problems of land degradation in arid and semiarid regions. In the present study, remote sensing was integrated with mathematical modeling to evaluate soil salinization adequately. To detect soil salinization, soil water content and electrical conductivity of soil samples were analyzed. The reflectance of soil samples was measured using a spectrometer (SR-3500) with 1024 bands. Indices of soil salinity, vegetation and drought were analyzed using Landsat images over the study area. Based on Landsat images, physicochemical analysis, reflectance of sensitive bands for soil salinization and environmental indices, canopy response salinity index (CRSI), perpendicular drought index (PDI) and enhanced normalized difference vegetation index (ENDVI), a new model was established for simulation and prediction of soil salinization in the study area. Correlation analyses and multiple regression methods were used to construct an accurate model. The results showed that green, blue and near-infrared light was significantly correlated with soil salinity and that the spectral parameters improved this correlation significantly. Therefore, the model was more effective when combining spectral parameters with sensitive bands with modeling. After mathematical transformation of soil reflectance, the correlations of bands sensitive to soil salinization were 0.739 and 0.7 for electrical conductivity and water content, respectively. After transformation of vegetation reflectance, the correlation coefficient of soil salinity became 0.577. After inversion of the model based on soil hyperspectral and water content, the significance became 0.871 and 0.726, respectively, which can be used to predict soil salinity and water content. The spectral soil salinity model had a coefficient of 0.739 for soil salinity prediction. Among the salinity indices, the CRSI was selected as the most significant, with R² of 0.571, whereas the R² for PDI reached only 0.484. Among the vegetation indices, the ENDVI had the highest response to soil salinity, with R² of 0.577. After scale conversion, the correlation percentages between CRSI and measured soil salinity and between ENDVI and measured soil salinity increased to 16.2% and 8.5%, respectively. Following the correlation between PDI and soil water content, the percentage of correlation increased to 11.6%. The integration of hyperspectral remote sensing, ground methods and an inversion method for salinity is a very important and effective technique for rapid and nondestructive monitoring of soil salinization.

     

基于SuperMap林业地理信息平台的设计与实现

为了满足当前基层林场生产任务和业务管理的实际需求,本文针对其生产中面临着的一些问题,组件式GIS-SuperMa PObjects和林业领域模型库为基础,建立林业地理信息系统平台(Superma PForest Star)的思想,实现森林资源的信息化管理.林业地理信息系统平台包括森林资源数据管理功能模块、造林决策支持模...     

Impact factors on distribution and characteristics of natural plant community in reclamation zones of Changjiang River estuary

To identify impact factors on the distribution and characters of natural plants community in reclamation area, with survey data from 67 plant quadrats in July 2009, soil properties data from 216 sampling points in April 2009, and TM (30 m) data in 2006, the composition and characteristics of natural plants community in different time of the Fengxian area in the Changjiang (Yangtze) River estuary were analyzed with two-way indicator species analysis (TWINSPAN), multivariate analysis of variance (MANOVA), detrended canonical correspondence analysis (DCCA) and canonical correspondence analysis (CCA). The results show that: 1) The plant communities in the reclaimed area are mainly mesophytes and helophytic-mesophytic transitional communities, showing a gradient distribution trend with the change in reclamation years. Species richness (MA), species diversity (H) and above-ground biomass also increase with the increase of reclamation years. Nevertheless, they appear to decline slightly in the middle and late reclamation period (> 30 years). 2) With the rise in land use levels, the changes in species richness and species diversity tend to increase at first and then decrease; species dominance (D), however, tends to decline; and above-ground biomass increases slightly. 3) The distribution of the plant community is mainly influenced by the following factors: land use levels (R = 0.55, p < 0.05), soil moisture (R = 0.53, p < 0.05), soil salinity (R = 0.43, p < 0.05) and reclamation time (R = 0.40, p < 0.05).