沉管沉放的实时监测

介绍了在沉管隧道施工中,实时监测沉管沉放的一种测量方法.它利用全站仪观测数据,通过坐标系之间的坐标转换,实时计算沉管管体特征点的坐标,从而对沉管的沉放过程进行实时监测.     

An improved direction relation detection model for spatial objects

Direction is a common spatial concept that is used in our daily life. It is frequently used as a selection condition in spatial queries. As a result, it is important for spatial databases to provide a mechanism for modeling and processing direction queries and reasoning. Depending on the direction relation matrix, an inverted direction relation matrix and the concept of direction pre- dominance are proposed to improve the detection of direction relation between objects. Direction predicates of spatial systems are also extended. These techniques can improve the veracity of direction queries and reasoning. Experiments show excellent efficiency and performance in view of direction queries.     

A fast clonal selection algorithm for feature selection in hyperspectral imagery

Clonal selection feature selection algorithm (CSFS) based on clonal selection algorithm (CSA), a new computational intelligence approach, has been proposed to perform the task of dimensionality reduction in high-dimensional images, and has better performance than traditional feature selection algorithms with more computational costs. In this paper, a fast clonal selection feature selection algorithm (FCSFS) for hyperspectral imagery is proposed to improve the convergence rate by using Cauchy mutation instead of non-uniform mutation as the primary immune operator. Two experiments are performed to evaluate the performance of the proposed algorithm in comparison with CSFS using hyperspectral remote sensing imagery acquired by the pushbroom hyperspectral imager (PHI) and the airborne visible/infrared imaging spectrometer (AVIRIS), respectively. Experimental results demonstrate that the FCSFS converges faster than CSFS, hence providing an effective new option for dimensionality reduction of hyperspectral remote sensing imagery.     

Biophysical factors of remote sensing approach in urban green analysis

Greenery in an urban environment is an important consideration when studying temperature, and such enquiry can benefit human health. The purpose of this paper is to investigate how ambient temperature in urban areas is affected by forests and parks. The focus is on biophysical parameters related to these green areas, such as impervious surface percentages, albedo, areal coverage, elevation, and leaf area index (LAI). Geographic information systems and remote sensing were used to quantify green spaces using a pixel-based method. It was found that coverage area has little correlation with temperature. Factor analysis was used to determine the minimum number of independent factors, which explained 63% of the variance of that temperature. Only elevation, LAI and albedo were significant biophysical factors. Guidelines for greenery programmes should include these significant data-sets to understand the influence of green areas on heat reduction.     

Addressing administrative units in international tsunami early warning systems: shortcomings in international geocode standards

Abstract

Administrative units reflect the territorial hierarchies established within all countries of the world. The units are addressable with geocodes that provide a bijective mapping between territories and unique identification codes. Early warning systems for natural or man-made hazards often map affected or threatened areas to administrative units to establish a spatial reference that is comprehensible to all parts of the population. Addressing these territories in an international context has several requirements, such as worldwide coverage, completeness and topicality, which must be met by geocode standards. In this paper, the practicability and suitability of international geocode standards are examined in the context of the requirements of large-scale early warning systems. This paper exposes the insufficiencies and limitations of existing geocode standards International Organization for Standardization (ISO)-3166, Second Administrative Level Boundaries data set project (SALB) and Nomenclature of the Territorial Units for Statistics (NUTS) and emphasises the suitability of the non-official hierarchical administrative subdivision codes (HASC). The analysis is framed in the context of addressing affected areas for an Indian Ocean tsunami early warning system. This system was developed within the Distant Early Warning Systems project according to the requirements of the United Nations Educational, Scientific and Cultural Organization (UNESCO) Intergovernmental Oceanic Commission for Regional Tsunami Watch Providers (RTWPs).     

Evaluation of environmental parameters in logistic regression models for landslide susceptibility mapping

Abstract

The aim of this study was to determine how well the landslide susceptibility parameters, obtained by data-dependent statistical models, matched with the parameters used in the literature. In order to achieve this goal, 20 different environmental parameters were mapped in a well-studied landslide-prone area, the Asarsuyu catchment in northwest Turkey. A total of 4400 seed cells were generated from 47 different landslides and merged with different attributes of 20 different environmental causative variables into a database. In order to run a series of logistic regression models, different random landslide-free sample sets were produced and combined with seed cells. Different susceptibility maps were created with an average success rate of nearly 80%. The coherence among the models showed spatial correlations greater than 90%. Models converged in the parameter selection peculiarly, in that the same nine of 20 were chosen by different logistic regression models. Among these nine parameters, lithology, geological structure (distance/density), landcover-landuse, and slope angle were common parameters selected by both the regression models and literature. Accuracy assessment of the logistic models was assessed by absolute methods. All models were field checked with the landslides resulting from the 12 November 1999, Kayna?li Earthquake (Ms = 7.2).     

Optimizing artificial neural network-based indoor positioning system using genetic algorithm

Abstract

The Global Positioning System (GPS) is expected to play an integral role in the development of digital earth; however, the GPS cannot provide positioning information in regions where a majority of the population spends their time, that is, in urban and indoor environments. Hence, alternate positioning systems that work in indoor and urban environments should be developed to achieve the vision of digital earth. Wi-Fi-based positioning systems (WPS) stand out because of the near-ubiquitous presence of the associated infrastructure and signals in indoor environments. The WPS-based fingerprinting is the most widely adopted technique for position determination, but its accuracy is lower than that of techniques such as time of arrival and angle of arrival. Improving the accuracy is still a challenging task because of the complex nature of the propagation of Wi-Fi signals. Here, a novel server-based, genetic-algorithm-optimized, cascading artificial neural network-based positioning model is presented. The model is tested in 2D and 3D indoor environments under varying conditions. The model is thoroughly investigated on a real Wi-Fi network, and its accuracy is found to be better than that of other well-known techniques. A mean accuracy of 1.9 m is achieved with 87% of the distance error within the range of 0–3 m.     

线性参照系在城市交通事故发布系统中的作用及应用

针对城市交通部门事故管理系统中存在道路数据不独立以及发布的事故信息易读性差导致应急部队无法准确定位事故地点进行救援的问题,基于公路的线性特征,结合GIS对地理数据的多样操作功能,提出路段名+特征参考点的一维定位表达方法。将线性参照系理论应用到以综合车道为公路模型的空间数据管理模式中,建立基于线性参照系的城市公路事故信息发布系统,实现二维坐标向一维坐标转换、降低数据冗余、实现事故地点的快速定位以及对定位的事故信息进行发布。     

一种基于参考数据的志愿者地理信息质量评价方法

志愿者地理信息数据大都依靠志愿者上传,数据质量未知,阻碍了志愿者地理信息的广泛应用,因此是志愿者地理信息首要解决的问题。本文分析了影响志愿者地理信息质量的相关因素和基于参考数据评价方法的相关研究成果,在此基础上提出了一种基于参考数据的志愿者地理信息质量评价方法,以最常见的数据完整性和数据精度作为质量评价的质量元素,详细论述了这两种质量元素的内涵。针对数据完整性评价,提出了与匹配相结合的几何数据完整性度量方法和基于属性项饱和度的属性数据完整性度量方法;针对几何数据精度评价,提出了基于变缓冲区的度量方法。然后给出了该评价方法的一般流程。最后,以深圳市Open Street Map数据为例,选取最新导航数据作为参考数据进行试验验证。实验结果表明,深圳市Open Street Map数据点要素完整性较差,但是线要素完整性与精度都非常高,可以作为基础地理信息的更新数据源。     

多基准点和基准方向的面阵与线阵影像匹配方法

针对面阵影像与线阵影像之间存在的尺度、旋转等几何差异所导致的难以高效获得稳定可靠匹配点问题,该文提出了一种稳健的面阵影像与线阵影像匹配方法。算法分为3个阶段:(1)对影像进行尺度、旋转预处理,消除影像间的尺度和旋转差异;(2)用Harris算子提取特征点,进行逐层金字塔匹配,在最底层影像上进行最小二乘匹配获取精匹配点,利用随机抽样一致算法获取准确性较高的匹配点;(3)对准确性较高的匹配点分区,构建4块匹配区域,根据每块区域的匹配点计算重心,以此4块区域的重心作为匹配基准点和基准方向,重约束初始匹配结果。通过多组面阵影像与线阵影像数据实验结果,验证了该方法的可行性和有效性,可为后续空中三角测量及相关应用提供可靠的匹配点。