VLBI-derived troposphere parameters during CONT08

Time-series of zenith wet and total troposphere delays as well as north and east gradients are compared, and zenith total delays (ZTD) are combined on the level of parameter estimates. Input data sets are provided by ten Analysis Centers (ACs) of the International VLBI Service for Geodesy and Astrometry (IVS) for the CONT08 campaign (12?C26 August 2008). The inconsistent usage of meteorological data and models, such as mapping functions, causes systematics among the ACs, and differing parameterizations and constraints add noise to the troposphere parameter estimates. The empirical standard deviation of ZTD among the ACs with regard to an unweighted mean is 4.6?mm. The ratio of the analysis noise to the observation noise assessed by the operator/software impact (OSI) model is about 2.5. These and other effects have to be accounted for to improve the intra-technique combination of VLBI-derived troposphere parameters. While the largest systematics caused by inconsistent usage of meteorological data can be avoided and the application of different mapping functions can be considered by applying empirical corrections, the noise has to be modeled in the stochastic model of intra-technique combination. The application of different stochastic models shows no significant effects on the combined parameters but results in different mean formal errors: the mean formal errors of the combined ZTD are 2.3?mm (unweighted), 4.4?mm (diagonal), 8.6?mm [variance component (VC) estimation], and 8.6?mm (operator/software impact, OSI). On the one hand, the OSI model, i.e. the inclusion of off-diagonal elements in the cofactor-matrix, considers the reapplication of observations yielding a factor of about two for mean formal errors as compared to the diagonal approach. On the other hand, the combination based on VC estimation shows large differences among the VCs and exhibits a comparable scaling of formal errors. Thus, for the combination of troposphere parameters a combination of the two extensions of the stochastic model is recommended.     

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.     

The ionosphere: effects,GPS modeling and the benefits for space geodetic techniques

The main goal of this paper is to provide a summary of our current knowledge of the ionosphere as it relates to space geodetic techniques, especially the most informative technology, global navigation satellite systems (GNSS), specifically the fully deployed and operational global positioning system (GPS). As such, the main relevant modeling points are discussed, and the corresponding results of ionospheric monitoring are related, which were mostly computed using GPS data and based on the direct experience of the authors. We address various phenomena such as horizontal and vertical ionospheric morphology in quiet conditions, traveling ionospheric disturbances, solar flares, ionospheric storms and scintillation. Finally, we also tackle the question of how improved knowledge of ionospheric conditions, especially in terms of an accurate understanding of the distribution of free electrons, can improve space geodetic techniques at different levels, such as higher-order ionospheric effects, precise GNSS navigation, single-antenna GNSS orientation and real-time GNSS meteorology.     

Synergistic Application of Optical and Radar Data for Archaeological Exploration in the Talakadu Region,Karnataka

Talakadu is a well known historic place situated on bank of the river Cauvery in Mysore district of Karnataka. The place is close to concave side of a prominent meander where large amount of sand has accumulated. It is believed that after construction of a reservoir upstream, sand was exposed to wind action burying the structures of Ganga dynasty and other later kingdoms. A number of buried sites have been identified by archaeological excavations conducted so far. Presently the area forms sand dunes with thick plantation cover. Analysis of RADAR data (fine beam RADARSAT and ENVISAT ASAR) led to identifying a hitherto unknown buried channel through the Old Talakadu town adjoining the excavated archaeological sites. The study suggests that RADAR penetration through the plantation canopy seems to have occurred as observed by comparing with corresponding optical data of LISS-IV. Below the canopy, sand and shrubs on top of the channel (topographically low area) are acting as smooth surface providing dark tone on radar imagery. During field validation GPS was extensively used to navigate through the forest canopy and locate the buried channel, excavated archaeological sites as well as other anomalous patterns. Synergistic application of optical (RESOURCESAT-1 LISS-IV and CARTOSAT-1 & 2) and radar (fine beam RADARSAT and ENVISAT ASAR) data led to identifying remote sensing based guides for archaeological exploration. Integration of known archaeological sites with the identified anomalous patterns was done in GIS environment. This study adds on to the knowledge base of the site and compliments already known information and suggested new areas for further archaeological exploration.     

Spatio-Temporal Coherence Based Technique for Near-Real Time Sea-Ice Identification from Scatterometer Data

The identification of sea-ice has frequently been cited as one of the most important tasks for deriving the sea-ice parameters and to avoid erroneous retrieval of wind vector over sea-ice infested oceans using space-borne scatterometer data. Discrimination between sea-ice and ocean is ambiguous under the high wind and/or thin/scattered ice conditions. The pre-launch technique developed for Oceansat-2, utilizes the dual-polarized QuikSCAT scatterometer data by using the spatio-temporal coherence properties of sea ice in addition to backscatter coefficient and the Active Polarization Ratio. Results were compared with the operational sea-ice products from National Snow and Ice Data Center. The threshold API value of −0.025 was found optimum for sea-ice and ocean discrimination. The overall sea-ice identification accuracy achieved was of the order of 95 per cent, ranging from 92.5% (during December in Southern Hemisphere) to 98% (during March in Northern Hemisphere). The applicability of the algorithm for both the Arctic as well as Antarctic makes it suitable for its operational use with the Oceansat-2 scatterometer data.     

A Dutch multi-date land use database: Identification of real and methodological changes

Land cover and land use are important information sources for environmental issues. One of the most important changes at the Earth's surface concerns land cover and land use. Knowledge about the location and type of these changes is essential for environmental modeling and management. Remote sensing data in combination with additional spatial data are recognized as an important source of information to detect these land cover and land use changes.     

Constructing a Near Real‐time Space‐time Cube to Depict Urban Ambient Air Pollution Scenario

This study adopts a near real‐time space‐time cube approach to portray a dynamic urban air pollution scenario across space and time. Originating from time geography, space‐time cubes provide an approach to integrate spatial and temporal air pollution information into a 3D space. The base of the cube represents the variation of air pollution in a 2D geographical space while the height represents time. This way, the changes of pollution over time can be described by the different component layers of the cube from the base up. The diurnal ambient ozone (O₃) pollution in Houston, Texas is modeled in this study using the space‐time air pollution cube. Two methods, land use regression (LUR) modeling and spatial interpolation, were applied to build the hourly component layers for the air pollution cube. It was found that the LUR modeling performed better than the spatial interpolation in predicting air pollution level. With the availability of real‐time air pollution data, this approach can be extended to produce real‐time air pollution cube is for more accurate air pollution measurement across space and time, which can provide important support to studies in epidemiology, health geography, and environmental regulation.     

Surface Ice Flow Velocity and Tide Retrieval of the Amery Ice Shelf using Precise Point Positioning

Five days of continuous GPS observation data were collected in the frontal zone of the Amery ice shelf and subsequently post-processed using precise point position (PPP) technology based on precise orbit and clock products from the International GNSS service. The surface ice flow velocity of the observed point was derived from PPP to be 2.25 m/day toward the northeast with an azimuth of 41°. Major semi-diurnal and diurnal oceanic tide constituents could be recovered from the 5 days of PPP-derived height variations and compared well with a hydrodynamic ocean tide model. The PPP technique can replace double-difference GPS positioning in remote or hostile environments, and be used to retrieve the surface ice flow velocity without any reference station. Furthermore, the solution can be derived epoch-by-epoch with accuracy in the centimeters to decimeter range.