Small-world characteristics on transportation networks: a perspective from network autocorrelation

Studies on small-world networks have received intensive interdisciplinary attention during the past several years. It is well-known among researchers that a small-world network is often characterized by high connectivity and clustering, but so far there exist few effective approaches to evaluate small-world properties, especially for spatial networks. This paper proposes a method to examine the small-world properties of spatial networks from the perspective of network autocorrelation. Two network autocorrelation statistics, Moran’s I and Getis–Ord’s G, are used to monitor the structural properties of networks in a process of “rewiring” networks from a regular to a random network. We discovered that Moran’s I and Getis–Ord’s G tend to converge and have relatively low values when properties of small-world networks emerge. Three transportation networks at the national, metropolitan, and intra-city levels are analyzed using this approach. It is found that spatial networks at these three scales possess small-world properties when the correlation lag distances reach certain thresholds, implying that the manifestation of small-world phenomena result from the interplay between the network structure and the dynamics taking place on the network.      

Correcting superconducting gravity time-series using rainfall modelling at the Vienna and Membach stations and application to Earth tide analysis

We demonstrate the possibility to improve the signal-to-noise ratio of superconducting gravity time-series by correcting for local hydrological effects. Short-term atmospheric events associated with heavy rain induce step-like gravity signals that deteriorate the frequency spectrum estimates. Based on 4D modeling constrained by high temporal resolution rain gauge data, rainfall admittances for the Vienna and Membach superconducting gravity stations are calculated. This allows routine correction for Newtonian rain water effects, which reduces the standard deviation of residuals after tidal parameter adjustment by 10%. It also improves the correction of steps of instrumental origin when they coincide with step-like water mass signals.     

Hyperspectral Radiometry to Quantify the Grades of Iron Ores of Noamundi and Joda Mines,Eastern India

This paper present the results of a preliminary study to assess the potential of the visible, NIR and SWIR energy of the EMR in differentiating iron ores of different grades in a rapid manner using hyperspectral radiometry. Using different iron ore samples from Noamundi and Joda mines, Jharkhand and Orissa, states of India, certain spectro-radiometric measurements and geochemical analysis were carried out and the results have been presented. It was observed that the primary spectral characteristics of these iron ores lie in the 850 to 900 nm and 650–750 nm regions. The spectral parameters for each curve used for studying the iron ores are: (i) the slopes of the spectral curve in 685–725 nm region; (ii) position of the peak with respect to wavelength in 730–750 nm region and (iii) radius of curvature of the absorption trough in the 850–900 nm region. Comparison of these spectral parameters and the geochemistry of the samples indicates that the position of the peak of the curve in 730–750 nm region shifts towards longer wavelength with increasing iron oxide content, while the slope of the curvature in the 685–725 nm region has a strong negative correlation with the iron oxide content of the samples. Similarly, a strong negative correlation is observed between the radius of curvature of the 850–900 nm absorption trough and the iron oxide content. Such strong correlations indicate that hyperspectral radiometry in the visible and NIR regions can give a better estimate and quantification of the grades of iron ores. This study has demonstrated that generation of empirical models using hyperspectral radiometric techniques is helpful to quantify the grade of iron ores with limited geochemical analysis.     

Comparison of Two Data Smoothing Techniques for Vegetation Spectra Derived From EO-1 Hyperion

Hyperspectral data are generally noisier compared to broadband multispectral data because their narrow bandwidth can only capture very little energy that may be overcome by the self-generated noise inside the sensors. It is desirable to smoothen the reflectance spectra. This study was carried out to see the effect of smoothing algorithms - Fast-Fourier Transform (FFT) and Savitzky–Golay (SG) methods on the statistical properties of the vegetation spectra at varying filter sizes. The data used in the study is the reflectance spectra data obtained from Hyperion sensor over an agriculturally dominated area in Modipuram (Uttar Pradesh). The reflectance spectra were extracted for wheat crop at different growth stages. Filter sizes were varied between 3 and 15 with the increment of 2. Paired t-test was carried out between the original and the smoothed data for all the filter sizes in order to see the extent of distortion with changing filter sizes. The study showed that in FFT, beyond filter size 11, the number of locations within the spectra where the smooth spectra were statistically different from its original counterpart increased to 14 and reaches 21 at the filter size 15. However, in SG method, number of statistically different locations were more than those found in the FFT, but the number of locations did not changing drastically. The number of statistically disturbed locations in SG method varied between 16 and 19. The optimum filter size for smoothing the vegetation spectra was found to be 11 in FFT and 9 in SG method.     

有限带宽信道条件下的Double-delta技术多径抑制性能分析及优化设计

以一种基于码跟踪多径误差包络的多径抑制性能评估准则为基础,首先根据Double-delta技术的基本原理,首次推导出了其在无限带宽时的码跟踪多径误差公式,并由此得出了Double-delta技术的理论性能计算公式;然后以数值计算的方法分析了不同信道带宽条件下Double-delta技术的多径抑制性能。仿真结果表明,当信...     

Attitude estimation based on fusion of gyroscopes and single antenna GPS for small UAVs under the influence of vibration

An attitude estimation method is presented for small unmanned aerial vehicles (UAVs) powered by a piston engine which is the major source of vibration. Vibration of the engine significantly degrades the accuracy of the inertial measurement unit, especially for low-cost sensors that are based on micro electro-mechanical system. Therefore, a vibration model for a small UAV is proposed in order to examine the influence of vibration on attitude estimation with different sensors. The model is derived based on spectrum analysis with short-time Fourier transform. The vibration is compared with the drift of the gyroscope in order to examine the impact on attitude estimation. An attitude estimation method that fuses the gyroscopes and single antenna global positioning system (GPS) is proposed to mitigate the influence of engine vibration and gyroscope drift. The quaternion-based extended Kalman filter is implemented to fuse the sensors. This filter fuses the angular rates measured by the gyroscopes and the pseudo-attitude derived from the GPS velocity to estimate the attitude of the UAV. Simulations and experiment results indicate that the proposed method performs well both in short-term and long-term accuracy even though the gyroscopes are affected by drift and vibration noise, while the pseudo-attitude contains severe noise.     

TAZ-level variation in work trip mode choice between 1990 and 2000 and the presence of rail transit

Rail transit continues to be a popular alternative for cities as a tool for alleviating automobile congestion and for redeveloping areas into transit and pedestrian-friendly environments. Ideally, rail transit will draw trips away from cars, but the quantitative work that tests this notion has often been either case studies of neighborhoods, in which conclusions are tough to generalize, or citywide comparisons where important spatial variation is lost in aggregation. This study seeks to narrow this gap in the research by using multivariate analysis of covariance to isolate the effect of covariates and cities on changes in work trip mode choice at the traffic analysis zone (TAZ) level for nine cities between 1990 and 2000. The results suggest differences by city in the change at the TAZ level of the proportion of people driving alone and taking transit. Increases in transit usage were associated with cities that built rail transit, while increases in automobile commuting and decreases in transit usage were associated with cities that did not.     

Skyline-based registration of 3D laser scans

Acquisition and registration of terrestrial 3D laser scans is a fundamental task in mapping and modeling of cities in three dimensions. To automate this task marker-free registration methods are required. Based on the existence of skyline features, this paper proposes a novel method. The skyline features are extracted from panoramic 3D scans and encoded as strings enabling the use of string matching for merging the scans. Initial results of the proposed method in the old city center of Bremen are pre-sented.     

Analytical methods for error propagation in planar space–time prisms

The space–time prism demarcates all locations in space–time that a mobile object or person can occupy during an episode of potential or unobserved movement. The prism is central to time geography as a measure of potential mobility and to mobile object databases as a measure of location possibilities given sampling error. This paper develops an analytical approach to assessing error propagation in space–time prisms and prism–prism intersections. We analyze the geometry of the prisms to derive a core set of geometric problems involving the intersection of circles and ellipses. Analytical error propagation techniques such as the Taylor linearization method based on the first-order partial derivatives are not available since explicit functions describing the intersections and their derivatives are unwieldy. However, since we have implicit functions describing prism geometry, we modify this approach using an implicit function theorem that provides the required first-order partials without the explicit expressions. We describe the general method as well as details for the two spatial dimensions case and provide example calculations.