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.     

Measuring tree stem diameters using intensity profiles from ground-based scanning lidar from a fixed viewpoint

This paper presents a method for using the intensity of returns from a scanning light detection and ranging (lidar) system from a single viewing point to identify the location and measure the diameter of tree stems within a forest. Such instruments are being used for rapid forest inventory and to provide consistent supporting information for airborne lidars. The intensity transect across a tree stem is found to be consistent with a simple model parameterised by the range and diameter of the trunk. The stem diameter is calculated by fitting the model to transect data. The angular span of the stem can also be estimated by using a simple threshold where intensity values are tested against the expected intensity for a stem of given diameter. This is useful when data are insufficient to fit the model or the stem is partially obscured. The process of identifying tree positions and trunk diameters is fully automated and is shown to be successful in identifying a high proportion of trees, including some that are partially obscured from view. The range and bearing to trees are in excellent agreement with field data. Trunk angular span and diameter estimations are well correlated with field measurements at the plot scale. The accuracy of diameter estimation is found to decrease with range from the scanning position and is also reduced for stems subtending small angles (less than twice the scanning resolution) to the instrument. A method for adjusting survey results to compensate for trees missed due to obscuration from the scanning point and the use of angle count methods is found to improve basal area estimates and achieve agreement within 4% of field measurements.     

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.     

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.     

Spatial Metrics to Analyse the Impact of Regional Factors on Pattern of Urbanisation in Gurgaon,India

In recent years, there has been lot of emphasis on the study of urban land use/ land cover changes to discover the growth pattern due to rapid urbanisation. This study presents spatial metrics and gradient analysis approach for quantifying and capturing changes in urban landscape using LISS III imagery of 1999, 2001 and 2004 of Gurgaon, India. A combination of spatial metrics i.e. percentage of landscape, mean patch size, number of patches, landscape shape index and largest patch index, available in Fragstats ver. 3.3, have been used to quantify the patterns of urban growth in different directions in terms of size, shape and complexity of development. The local built-up areas were quantified by the “moving window” technique. A gradient analysis has been carried out through sampling from a reference point to 8 km in 16 directions with a window size of 500 mts. Results of this study demonstrate the potential of spatial metrics and gradient modelling to quantify the impact of regional factors on the growth pattern of Gurgaon city.     

Transverse Mercator with an accuracy of a few nanometers

Implementations of two algorithms for the transverse Mercator projection are described; these achieve accuracies close to machine precision. One is based on the exact equations of Thompson and Lee and the other uses an extension of Krüger’s series for the mapping to higher order. The exact method provides an accuracy of 9 nm over the entire ellipsoid, while the errors in the series method are less than 5 nm within 3900 km of the central meridian. In each case, the meridian convergence and scale are also computed with similar accuracy. The speed of the series method is competitive with other less accurate algorithms and the exact method is about five times slower.     

Self-calibration Applied in Converting Simulation Surveying

In the field of converting simulation surveying and traditional close range photogrammetry, it has been developed so far to survey objects by commercial digital camera and this technique is applied widely in every part of production. In order to get three-dimensional information of objects, commercial digital camera must be examined. For a long time, digital camera has been examined by DLT. Then there must be a high-precision control field. For realizing surveying without control points, a method for self-calibration is proposed.