A study on the polarimetric properties of various features using SIR-C data

Spaceborne Imaging Radar (SIR-C) data acquired over Gujarat, India in 1994 were processed and analysed using differnet techniques applicable to polarimetric SAR data such as polarization signatures, polarization index, decomposition of the signal and polarization phase difference and limited groundtruth data. It has been observed that multi-frequency polarimetric data enhances the potential of retrieving geo-physical parameters. The polarization signatures are found to vary with the nature of the target. Target decomposition of the returned signal will be useful for the classification of various features. Polarization Phase Difference (PPD) gives good information about the vegetation parameters.     

The GeoForschungsZentrum Potsdam/Groupe de Recherche de Gèodésie Spatiale satellite-only and combined gravity field models: EIGEN-GL04S1 and EIGEN-GL04C

The recent improvements in the Gravity Recovery And Climate Experiment (GRACE) tracking data processing at GeoForschungsZentrum Potsdam (GFZ) and Groupe de Recherche de Géodésie Spatiale (GRGS) Toulouse, the availability of newer surface gravity data sets in the Arctic, Antarctica and North-America, and the availability of a new mean sea surface height model from altimetry processing at GFZ gave rise to the generation of two new global gravity field models. The first, EIGEN-GL04S1, a satellite-only model complete to degree and order 150 in terms of spherical harmonics, was derived by combination of the latest GFZ Potsdam GRACE-only (EIGEN-GRACE04S) and GRGS Toulouse GRACE/LAGEOS (EIGEN-GL04S) mean field solutions. The second, EIGEN-GL04S1 was combined with surface gravity data from altimetry over the oceans and gravimetry over the continents to derive a new high-resolution global gravity field model called EIGEN-GL04C. This model is complete to degree and order 360 and thus resolves geoid and gravity anomalies at half- wavelengths of 55 km at the equator. A degree-dependent combination method has been applied in order to preserve the high accuracy from the GRACE satellite data in the lower frequency band of the geopotential and to form a smooth transition to the high-frequency information coming from the surface data. Compared to pre-CHAMP global high-resolution models, the accuracy was improved at a spatial resolution of 200 km (half-wavelength) by one order of magnitude to 3 cm in terms of geoid heights. The accuracy of this model (i.e. the commission error) at its full spatial resolution is estimated to be 15 cm. The model shows a reduced artificial meridional striping and an increased correlation of EIGEN-GL04C-derived geostrophic meridional currents with World Ocean Atlas 2001 (WOA01) data. These improvements have led to select EIGEN-GL04C for JASON-1 satellite altimeter data reprocessing. Electronic Supplementary Material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

An approach to aid INS using time-differenced GPS carrier phase (TDCP) measurements

This paper presents a simple and effective approach that incorporates single-frequency, L1 time-differenced GPS carrier phase (TDCP) measurements without the need of ambiguity resolution techniques and the complexity to accommodate the delayed-state terms. Static trial results are included to illustrate the stochastic characteristics and effectiveness of the TDCP measurements in controlling position error growth. The formulation of the TDCP observation model is also described in a 17-state tightly-coupled GPS/INS iterative, extended Kalman filter (IEKF) approach. Preliminary land vehicle trial results are also presented to illustrate the effectiveness of the TDCP which provides sub-meter positional accuracies when operating for more than 10 min.     

On the Use of CloudSat and MODIS Data for Estimating Hurricane Intensity

This letter presents preliminary results concerning the use of new observations from the A-Train Constellation for testing a new technique of remotely sensing hurricane intensity from space based on modeling a hurricane as a balanced, convectively neutral vortex. The key observational requirements are simultaneous, accurate measurements of cloud-top height, cloudtop temperature, and cloud profiling information across the center of the storm, although there are ways to bypass the need for cloud-top temperature. In this letter, the Moderate Resolution Imaging Spectroradiometer onboard Aqua provides an estimation of the cloud-top temperature, and the near-simultaneous CloudSat observations provide the essential cloud-top height and cloud profiling information. Initial results indicate that the new technique is a promising method for estimating storm intensity when compared post facto to the best track database. Potential uncertainties and room for further refinement of the technique are discussed.     

Open source, spatial analysis, and activity-travel behaviour research: capabilities of the aspace package

This paper reports on recent experience with the development of aspace, an Open Source (OS) library for the geographic visualization and analysis of activity-travel behaviour. The paper begins with an overview of recent progress with respect to the convergence of Open Source technology, spatial analysis, and travel behaviour research. The remainder of the paper focuses on aspace; a collection of functions that, when combined with data describing the geographical location of daily activities, can be used to visualize and describe spatial properties of individual and household activity spaces. These properties include: size, orientation, shape, and the geographical dispersion of activity locations contained within the activity space. Several planar geometries are used to transform measurable spatial properties into intuitive objects for visualizing spatial patterns of activity participation. Experiments are conducted, using data from the first wave of the 2003 Toronto Travel Activity Panel Survey, to demonstrate the potential application of aspace for basic and applied policy-based research into activity-travel behaviour. The toolkit is distributed as a downloadable ‘package’ from the Open Source R Project for Statistical Computing.