High-resolution satellite image segmentation using Hölder exponents

Texture in high-resolution satellite images requires substantial amendment in the conventional segmentation algorithms. A measure is proposed to compute the Hölder exponent (HE) to assess the roughness or smoothness around each pixel of the image. The localized singularity information is incorporated in computing the HE. An optimum window size is evaluated so that HE reacts to localized singularity. A two-step iterative procedure for clustering the transformed HE image is adapted to identify the range of HE, densely occupied in the kernel and to partition Hölder exponents into a cluster that matches with the range. Hölder exponent values (noise or not associated with the other cluster) are clubbed to a nearest possible cluster using the local maximum likelihood analysis.     

新疆和田河流域柽柳沙堆的生物地貌发育过程

Tamarix nabkha is one of the most widespread nabkhas,distributing in the arid region of China.Based on the observations outdoors and the simulation experiments in laboratories,analysis in this paper refers to the biological geomorphologic features and growth process of Tamarix nabkhas in the middle and lower reaches of the Hotan River,Xin- jiang.And the results indicate that the ecological type of Tamarix in the study area is a kind of Tugaic soil habitat based on the deep soil of the Populus Diversifolia f...     

Aluminum Consumption and Economic Growth: Evidence from Rich Countries

The article attempts to test the aluminum consumption–economic growth nexus for 20 rich economies for the period 1970–2009. Various panel data unit root and cointegration tests are applied. The series are found to be integrated of order one and cointegrated, especially after controlling for cross-sectional dependence. Moreover, the Blundell–Bond system generalized methods-of-moments is employed to conduct a panel causality test in a vector error-correction mechanism setting. Unidirectional causality running from aluminum consumption to real GDP is uncovered in the short-run, while real GDP is found to Granger-cause aluminum consumption in the long-run. Moreover, a 1% increase in real GDP generates an increase of 0.44% in aluminum consumption in the long-run for the whole panel.     

Automatic mapping of lunar landforms using DEM-derived geomorphometric parameters

Developing approaches to automate the analysis of the massive amounts of data sent back from the Moon will generate significant benefits for the field of lunar geomorphology. In this paper, we outline an automated method for mapping lunar landforms that is based on digital terrain analysis. An iterative self-organizing (ISO) cluster unsupervised classification enables the automatic mapping of landforms via a series of input raster bands that utilize six geomorphometric parameters. These parameters divide landforms into a number of spatially extended, topographically homogeneous segments that exhibit similar terrain attributes and neighborhood properties. To illustrate the applicability of our approach, we apply it to three representative test sites on the Moon, automatically presenting our results as a thematic landform map. We also quantitatively evaluated this approach using a series of confusion matrices, achieving overall accuracies as high as 83.34% and Kappa coefficients (K) as high as 0.77. An immediate version of our algorithm can also be applied for automatically mapping large-scale lunar landforms and for the quantitative comparison of lunar surface morphologies.     

Automated mapping of rock slope geometry,kinematics and stability with RSS-GIS

A GIS-implemented, deterministic approach for the automated spatial evaluation of geometrical and kinematical properties of rock slope terrains is presented. Based on spatially distributed directional information on planar geological fabrics and DEM-derived topographic attribute data, the internal geometry of rock slopes can be characterized on a grid cell basis. For such computations, different approaches for the analysis and regionalization of available structural directional information applicable in specific tectonic settings are demonstrated and implemented in a GIS environment. Simple kinematical testing procedures based on feasibility criteria can be conducted on a pixel basis to determine which failure mechanisms are likely to occur at particular terrain locations. In combination with hydraulic and strength data on geological discontinuities, scenario-based rock slope stability evaluations can be performed. For conceptual investigations on rock slope failure processes, a GIS-based specification tool for a 2-D distinct element code (UDEC) was designed to operate with the GIS-encoded spatially distributed rock slope data. The concepts of the proposed methodology for rock slope hazard assessments are demonstrated at three different test sites in Germany.     

三维激光扫描点云数据在CloudWorx for MicroStation下的处理

三维激光扫描技术作为一种先进的测量手段应用前景十分广阔,但是,在应用其扫描所得的点云数据进行内处理上又遇到了许多技术性的问题。CAD系统处理大量点云数据过程中存在局限性,一旦用CAD系统处理点云时,CAD程序就会出现错误操作提示,甚至完全停止进程。CloudWorx克服了这些局限性,它避免了直接输入数据,而是利用Cyclone技术作为MicroStation环境下有效管理和解决点云的工具,使MicroStation内点云操作与CAD程序执行再无冲突。本文主要介绍了并且还介绍了CloudWorx模块的功能,并举例就点云数据在CloudWorx for MicroStation软件环境下的处理工作进行了详细的介绍。     

基于KML的三维专题图表示方法

近几年来,虚拟地理环境系统得到广泛应用。专题图制作在制图学上有着悠久的历史。但是在虚拟地理环境浏览系统中(如Google Earth)对专题要素的表达没有得到足够的重视。文中研究如何利用KML制作专题符号,并在三维虚拟地理环境浏览系统中利用基于KML的专题符号实现定点符号法、分区图表法、质别底色法等专题图表示方法。通过实验说明KML在专题图的制作中具有巨大潜力,但同时也有一些重点问题需要解决。     

面向对象分类特征优化选取方法及其应用

与传统基于像元的分类方法比较,面向对象的分类方法可利用的地物信息更加丰富,然而如何从众多信息中筛选出能够有效提取不同地物的分类特征,从而提高分类效率与精度,是使用面向对象方法分类时急需解决的问题。SEaTH算法（分离阈值法）是一种有效的自动选取分类特征并计算阈值的方法,但其只考虑了类间距离,容易存在信息的冗余,从而对分类精度造成一定影响。本文在SEaTH算法的基础上,综合考虑了特征间的相关性、类间距离以及类内距离,对SEaTH算法进行了优化,并将改进前后的两种方法运用到广东省肇庆市TM影像及环境一号卫星影像土地覆盖分类中进行对比分析。实验结果表明,改进后的方法筛选出的特征在提取地物上更为有效,尤其使耕地的分类精度提高了12.26%,使分类总体精度由80%提高到了85.26%。改进后的方法对不易获取多时相影像的地区的土地覆盖分类具有重要意义。     

直升机飞行专题图分层设色方案研究与实践

随着我国低空空域的逐步开放,直升机的应用会越来越广泛。面向直升机飞行使用的专题图需求会越来越迫切。本文在深入研究直升机的飞行特点基础之上,结合分层设色的原理和方法,研究和设计了面向直升机飞行使用的专题图分层设色方案。实践表明该方案能够突出直升机飞行时对地形、地貌关注的特点,对飞行员认知地形具有一定的帮助,具有一定的实用价值。     

Singular value decomposition and cluster analysis as regression diagnostics tools for geodetic applications

It is well known that high-leverage observations significantly affect the estimation of parameters. In geodetic literature, mainly redundancy numbers are used for the detection of single high-leverage observations or of single redundant observations. In this paper a further objective method for the detection of groups of important and less important (and thus redundant) observations is developed. In addition, the parameters which are predominantly affected by these groups of observations are identified. This method thus complements other diagnostics tools, such as, e.g., multiple row diagnostics methods as described in statistical literature (see, e.g., Belsley et al. in Regression diagnostics: identifying influential data and sources of collinearity. Wiley, New York, 1980). The method proposed in this paper is based on geometric aspects of adjustment theory and uses the singular value decomposition of the design matrix of an adjustment problem together with cluster analysis methods for regression diagnostics. It can be applied to any geodetic adjustment problem and can be used for the detection of (groups of) observations that significantly affect the estimated parameters or that are of negligible impact. One of the advantages of the proposed method is the improvement of the reliability of observation plans and thus the reduction of the impact of individual observations (and outliers) on the estimated parameters. This is of particular importance for the very long baseline interferometry technique which serves as an application example of the regression diagnostics tool.