ArcGeophysics 1.0:GIS环境下综合处理、解释地球物理与地质、地球化学、遥感等资料的组件(COM)包与应用实例

地球物理资料综合处理与解释在油气、煤田、矿物勘探\[5\]、水文分析、水文工程与环境评价中有重要应用.然而,目前的(位场)地球物理处理与解释可视化程度低,无法利用其它资料有效的约束、关联分析与综合快速解释.虽然地理信息系统(GIS)是目前综合多种资料,进行空间处理、分析,提供决策支持的强有力工具,但是,GIS是为一般地理问题分析定制的,缺少综合地球物理处理解释的工具.本文给出了解决上述问题的,用组件对象模型(COM)实现的软件包－ArcGeophysics. 在ArcGeophysics中,实现了勘探数据的有效管理,空间统计分析,地球物理（正演、反演）,地球化学与遥感处理、分析、解释与可视化,信息集成与勘探靶区预测等功能.特别需要指出的是：(1) ArcGeophysics 无缝地结合了ArcObject (ArcGIS, ESRI),也就继承了当前国际上占主导地位的GIS软件包中所有的GIS功能;(2) ArcGeophysics是建立在COM基础之上,任何支持COM的应用环境(如MS Office),编程环境(如MS Visual Studio (.Net), Borland Delphi等都可以调用这些功能(相当于通用开发工具包); (3)ArcGeophysics对地球物理资料的处理解释结合了非线性系统、多尺度分析与多维分形理论.本文不仅给出了各向异性奇异性的应用实例,而且还给出了位场在Fourier空间处理分数维导数,以及在余弦变换空间多维分形模型(C-SA).本文应用加拿大Nova Scotia省南半部的地球物理、地球化学、地质与成矿资料进行了试算,得到了理想的结果,文中图２～图５均直接出之ArcGeophysics的输出.     

Integrated data processing method for GPS and INS field test over Rocky Mountain

IntroductionGPS/INS integrated system exploited the INSand differential GPS pseudo-range and carrierphase technique to promote the accuracy of thedynamic platform navigation and positioning,and increase the reliability and stabilization.Incalculation, Kal…     

基于网络的数字地震台网数据处理系统设计

基于网络的数字地震台网数据处理系统(EDSP_NET)是根据区域数字地震台网在宽频带数据处理、 数据共享方面的需求开发的。 EDSP_NET运行于Windows平台, 用于汇集、 处理来自数字地震台站的波形数据, 实现台网中心间的数据共享, 监视台站和台网中心处理系统的运行状态。 详细介绍了系统结构和功能, 并简要介绍了系统的三个应用模式。     

使用L0范数代价函数的二维相位快速解缠方法

针对最小范数解缠方法的代价函数模型以及迭代效率问题,提出一种符合L0范数准则的高效的二维相位全局最优解缠方法。在对最小范数代价函数模型特征进行分析的基础上,给出一种符合L0范数准则的代价函数,满足在相位不连续边界的切方向上相对法方向具有更强的约束作用,保证解缠迭代处理时连续相位按照代价函数的约束条件进行趋近的同时,不连续边界不会被破坏。为了解决线性方程中低频误差收敛慢的问题,根据最小范数方法独立性的特点,采用数据分块处理方法,注重高频信息以提高迭代处理效率,将低频信息处理转移到数据块间偏移量计算中。实验对比分析表明,新解缠方法在可靠性和效率方面都能够达到较好的水平。     

资源三号02星激光测高数据质量分析

近几年来,中国的对地观测卫星激光测高技术发展较快,资源三号02星上搭载了国内首台对地观测的卫星激光测高试验载荷,在后续的高分七号、陆地生态系统碳监测卫星上均装备业务化应用的激光测高仪,开展国产对地观测卫星激光测高数据质量分析研究非常必要,能有效填补国内空白并推动相关技术发展。本文对资源三号02星载荷的激光测高数据进行了严密几何处理,重点从夜间观测、卫星小角度侧摆、海面区域等不同条件下的数据质量进行了分析,对数据的平均可用率进行了统计分析。试验表明,资源三号02星激光测高仪能获得约30%有效测高数据,在夜间数据有效利用率略有提高,在大型水面也能获得有效数据,经后处理后在平坦地区验证的绝对高程精度优于1.0 m,部分点高程精度优于0.5 m,硬件本身的测距精度和卫星姿态测量误差是主要的误差源。相关结论对于后续国产卫星激光测高载荷的研制以及数据后处理和应用具有参考价值。     

Normalizing shadows in multi-temporal aerial frame imagery using relative radiometric adjustments to support near-real-time change detection

This study addresses the problem of shadows in multi-temporal imagery, which is a key issue with change detection approaches based on image comparison. We apply image-to-image radiometric normalizations including histogram matching (HM), mean-variance (MV) equalization, linear regression based on pseudo-invariant features (PIF-LR), and radiometric control sets (RCS) representing high- and low-reflectance extrema, for the novel purpose of normalizing brightness of transient shadows in high spatial resolution, bi-temporal, aerial frame image sets. Efficient shadow normalization is integral to remote sensing procedures that support disaster response efforts in a near-real-time fashion, including repeat station image (RSI) capture, wireless data transfer, shadow detection (as precursor to shadow normalization), and change detection based on image differencing and visual interpretation. We apply the normalization techniques to imagery of suburban scenes containing shadowed materials of varied spectral reflectance characteristics, whereby intensity (average of red, green, and blue spectral band values) under fully illuminated conditions is known from counterpart reference images (time-1 versus time-2). We evaluate the normalization results using stratified random pixel samples within transient shadows, considering central tendency and variance of differences in intensity relative to the unnormalized images. Overall, MV equalization yielded superior results in our tests, reducing the radiometric effects of shadowing by more than 85 percent. The HM and PIF-LR approaches showed slightly lower performance than MV, while the RCS approach proved unreliable among scenes and among stratified intensity levels. We qualitatively evaluate a shadow normalization based on MV equalization, describing its utility and limitations when applied in change detection. Application of image-to-image radiometric normalization for brightening shadowed areas in multi-temporal imagery in this study proved efficient and effective to support change detection.     

显著性权重RX高光谱异常点检测

高光谱图像异常点检测中,传统RX异常点检测算法忽略了空间相关性,背景估计不准确。本文提出了一种基于图像局部邻域光谱显著性分析的加权RX算法。该算法通过引入图像显著性分析,对基于概率密度为权重的图像背景建模进行改进,建立光谱显著性权重图,重新定义RX算法中的均值向量和协方差矩阵,并给不同的目标赋予不同的权值,达到优化背景估计的目的。利用合成高光谱数据和真实高光谱数据进行异常点检测实验,结果表明,对于同一组数据,本文算法检测到的异常点数比传统算法多,虚警率较低,有效地提高了检测率。     

基于Pix4Dmapper的无人机低空摄影测量数据处理

随着科技发展,无人机的使用就像汽车一样应用于各个领域,成熟的航空摄影测量理论为无人机在测量方面的使用提供了坚实的基础,而后处理成像软件通过提供三维模型来实现数据的精确可视化,更进一步提高了无人机的有效性。本文利用航空摄影测量的中心投影原理,提出基于Pix4Dmapper的无人机低空摄影测量数据处理流程,对经过空中三角测量和相机校准的航摄像片经过光束法区域网平差、空三加密、点云编辑、滤波处理,生成高精度的Google瓦片、正射影像图(DOM)、三维点云模型、数字表面模型(DSM)、数字高程模型(DEM)、数字地面模型(DTM),经过多次应用表明:处理成果能够满足应用需求,极大促进了摄影测量技术的发展。     

Parallel computing solutions for Markov chain spatial sequential simulation of categorical fields

The Markov chain random field (MCRF) model is a spatial statistical approach for modeling categorical spatial variables in multiple dimensions. However, this approach tends to be computationally costly when dealing with large data sets because of its sequential simulation processes. Therefore, improving its computational efficiency is necessary in order to run this model on larger sizes of spatial data. In this study, we suggested four parallel computing solutions by using both central processing unit (CPU) and graphics processing unit (GPU) for executing the sequential simulation algorithm of the MCRF model, and compared them with the nonparallel computing solution on computation time spent for a land cover post-classification. The four parallel computing solutions are: (1) multicore processor parallel computing (MP), (2) parallel computing by GPU-accelerated nearest neighbor searching (GNNS), (3) MP with GPU-accelerated nearest neighbor searching (MP-GNNS), and (4) parallel computing by GPU-accelerated approximation and GPU-accelerated nearest neighbor searching (GA-GNNS). Experimental results indicated that all of the four parallel computing solutions are at least 1.8× faster than the nonparallel solution. Particularly, the GA-GNNS solution with 512 threads per block is around 83× faster than the nonparallel solution when conducting a land cover post-classification with a remotely sensed image of 1000?×?1000 pixels.     

国产走航式声学海流剖面仪的应用分析

针对国产走航式声学海流剖面仪的应用性能进行评价,为用户及生产厂家提供借鉴。首先,就国产走航式声学海流剖面仪的实际数据,从不同角度和层面,全面分析和考察了其测量数据的各项性能,有针对性地绘制了各类图件,并通过数据质量、数据有效性、测流精度、测流深度等各方面的分析比对,对国产走航式声学海流剖面仪做出定性评价。其次,通过与国外同类仪器的以往应用情况进行对比分析,发现在船只转向和往复航行、加速和减速航行、高速航行时,国产走航式声学海流剖面仪表现更佳。最后,基于应用中的不足给出相关建议。