DEM制作检查及精度问题的解决方法

介绍了通过数字化仪手扶跟踪及扫描仪半自动采集现有地形图等高线的步骤,再通过内插方法生成DEM,并对如何提高DEM精度提出了解决方案。     

‘Box‐Profile’ Ion Implants as Geochemical Reference Materials for Electron Probe Microanalysis and Secondary Ion Mass Spectrometry

Although electron probe microanalysis and secondary ion mass spectrometry are widely used analytical techniques for geochemical and mineralogical applications, metrologically rigorous quantification remains a major challenge for these methods. Secondary ion mass spectrometry (SIMS) in particular is a matrix‐sensitive method, and the use of matrix‐matched reference materials (RMs) is essential to avoid significant analytical bias. A major problem is that the number of available RMs for SIMS is extremely small compared with the needs of analysts. One approach for the production of matrix‐specific RMs is the use of high‐energy ion implantation that introduces a known amount of a selected isotope into a material. We chose the more elaborate way of implanting a so‐called ‘box‐profile’ to generate a quasi‐homogeneous concentration of the implanted isotope in three dimensions, which allows RMs not only to be used for ion beam analysis but also makes them suitable for EPMA. For proof of concept, we used the thoroughly studied mineralogically and chemically ‘simple’ SiO₂ system. We implanted either ⁴⁷Ti or ⁴⁸Ti into synthetic, ultra‐high‐purity silica glass. Several ‘box‐profiles’ with mass fractions between 10 and 1000 μg g^?1 Ti and maximum depths of homogeneous Ti distribution between 200 nm and 3 μm were produced at the Institute of Ion Beam Physics and Materials Research of Helmholtz‐Zentrum Dresden‐Rossendorf. Multiple implantation steps using varying ion energies and ion doses were simulated with Stopping and Range of Ions in Matter (SRIM) software, optimising for the target concentrations, implantation depths and technical limits of the implanter. We characterised several implant test samples having different concentrations and maximum implantation depths by means of SIMS and other analytical techniques. The results show that the implant samples are suitable for use as reference materials for SIMS measurements. The multi‐energy ion implantation technique also appears to be a promising procedure for the production of EPMA‐suitable reference materials.     

对1989年以来华北北部6级左右地震前山西电磁异常的总结

概述了近１０ａ来分布于山西中北部电磁观测台站的综合状况,对这些台站在１９８９年山西大同—阳高６．１级,１９９６年内蒙古包头６．４级及１９９８年河北张北６．２级地震前后的观测资料进行了认真分析,在排除干扰和对出现的地震异常进行识别、核实的基础上,总结了其变化特征,给出了信度。对这３次地震的分析总结后,对今后电磁学科的工作提出了建议。     

关于震磁关系"综合解释"层次的初步分析

从系统分析的角度出发,提出以磁报震的实质是综合预报,而综合预报的基础则是综合解释。作为一个认识系统,以磁报震的综合解释主要由４个层次（４个要素）组成,即地磁场异常变化（层次Ｉ）,构造环境及应力场的变化（层次Ⅱ）,系统相关要素的变化（层次Ⅲ）,外部环境要素的变化等（层次Ⅳ）。以磁报震不应简单归结为完全以地磁异常变化为基点的地震预报,而应是由多要素（层次）组成的有机分析系统,即在以层次Ｉ为核心的认识基     

中国湖泊综合分类原则、级别划分及分类程序之初探

在略述了国内外湖泊分类研究现状的基础上,探讨了开展我国湖泊综合分类的原则、级别划分以及综合分类所应该遵循的程序。主导因素与综合因素相结合,建立分类的主导标志,是湖泊综合分类系统中高层次分类的关键;区域相似性（相对一致性）与差异性的对比分析是低层次分类的重要环节。在此基础上,还应充分考虑到人类经济活动的方式与强度对湖泊诸自然因素的影响,以便使湖泊综合分类工作既具有理论上的意义,同时又具有实用价值。级     

利用控制点三维信息标定机载双天线干涉SAR参数

采用基于敏感度方程的方法,研究基于三维重建模型下的机载双天线干涉SAR系统的干涉参数定标问题.干涉参数定标是生成高精度数字高程模型的关键.本文修正了Madsen提出的干涉SAR三维重建的视向量正交分解算法,采用电磁波波前的球面波模型,加入了载机的姿态旋转,构建一种新的干涉SAR三维重建模型.利用各干涉参数对控制点三维信息的不同的敏感性,提出分别利用地面控制点三维信息,对各干涉参数进行定标.并利用中国科学院电子学研究所自主设计、研制的机载干涉SAR系统数据,进行定标处理实验验证.     

Dynamics in land-surface conditions on the Tibetan Plateau observed by Advanced Synthetic Aperture Radar (ASAR)

Abstract

A time series analysis of 152 VV-polarized Advanced Synthetic Aperture Radar (ASAR) Wide Swath Mode (WSM) images collected over the central part of the Tibetan Plateau is presented for the period from April 2005 to September 2007. The signatures of a grassland and a wetland are studied to identify the impact of three land-surface states on the backscatter (σ°). The considered land-surface states are soil moisture, soil temperature and vegetation biomass represented by Système Pour l'Observation de la Terre (SPOT) Normalized Difference Vegetation Index (NDVI). Comparison of the σ° time series with these land-surface states via a multivariate regression shows that the grassland σ° are well represented by the soil moisture dynamics, while the wetland σ° also has a strong correlation with soil temperature. Further, we found that the contribution of the NDVI to the explanation of the temporal σ° variability is limited for both the grassland and wetland.