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.     

Precise ionosphere-free single-frequency GNSS positioning

Ionospheric delays can be efficiently eliminated from single-frequency data using a combination of carrier phases and code ranges. Unfortunately, GPS and GLONASS ranges are relatively noisy which can limit the use of the positioning method. Nevertheless, position standard deviations are in the range of 6–8 cm (horizontal) and 7–9 cm (3d) obtained from diurnal data batches from selected IGS reference stations can be further reduced to 2–3 cm (3d) for weekly smoothed averages. GPS data sets collected in Ghana (Africa) reveal a typical level of 10 cm of deviation that must be anticipated under average conditions. Looking at the future of GNSS, the European Galileo system will, in contrast to GPS, provide the broadband signal E5 that is by far less affected by multipath thus providing rather precise range measurements. Simulated processing runs featuring both high ionospheric and tropospheric delay variations show a 3d position precision of 4 cm even for a data batch as short as just 1 h, whereas GPS L1/Galileo E1 performance is close to 13 cm for the same data set.     

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.     

GPS tomography in the polar cap: comparison with ionosondes and in situ spacecraft data

Tomographic 4D reconstructions of ionospheric anomalies appearing in the high-latitude polar cap region are compared with plasma density measurements by digital ionosonde located near the north magnetic pole at Eureka station and with in situ plasma measurements on-board DMSP spacecraft. The moderate magnetic storm of 14–17 October 2002 is taken as an example of a geomagnetic disturbance which generates large-scale ionospheric plasma anomalies at mid-latitudes and in the polar cap region. Comparison of the GPS tomographic reconstructions over Eureka station with the ionosonde measurements of the F layer peak densities indicates that the GPS tomography correctly predicts the time of arrival and passage of the ionospheric tongue of ionization over the magnetic pole area, although the tomographic technique appears to under-estimate the value of F peak plasma density. Comparison with the in situ plasma measurements by the DMSP SSIES instruments shows that the GPS tomography correctly reproduces the large-scale spatial structure of ionospheric anomalies over a wide range of latitudes from mid-latitudes to the high-latitude polar cap region, though the tomographic reconstructions tend to over-estimate the density of the topside ionosphere at 840 km DMSP orbit. This study is essential for understanding the quality and limitations of the tomographic reconstruction techniques, particularly in high-latitude regions where GPS TEC measurements and other ionospheric data sources are limited.     

Phase transitions and path dependence in urban evolution

There is a long history of recognising and interpreting discontinuous change—phase transitions—in urban systems. In this paper, we use the aggregate retail model as an archetype to explore some new ideas. For example, we argue that the dependence of paths of development on initial conditions has been understudied, and we offer a new graphical analysis that demonstrates explicitly their influence on discrete change. We introduce an order parameter, and we plot this on a ‘results grid’ to facilitate the discovery of possible phase transitions. We illustrate the use of these new developments with an application to London. We show how retail developers can change the ‘initial conditions’ at a point in time and possibly bring about phase transitions by their actions. This also shows that it should be possible to account for the history of urban development as a sequence of initial conditions, illustrating path dependence. Secondly, the model could be deployed in relation to a new shopping zone, and the tools developed here used to calculate the minimum size of a new development in order for it to compete. We explore the ‘minimum size’ idea in relation to a new shopping zone in London.     

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.     

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.