Reliable estimation of orbit errors in spaceborne SAR interferometry

An approach to improve orbital state vectors by orbit error estimates derived from residual phase patterns in synthetic aperture radar interferograms is presented. For individual interferograms, an error representation by two parameters is motivated: the baseline error in cross-range and the rate of change of the baseline error in range. For their estimation, two alternatives are proposed: a least squares approach that requires prior unwrapping and a less reliable gridsearch method handling the wrapped phase. In both cases, reliability is enhanced by mutual control of error estimates in an overdetermined network of linearly dependent interferometric combinations of images. Thus, systematic biases, e.g., due to unwrapping errors, can be detected and iteratively eliminated. Regularising the solution by a minimum-norm condition results in quasi-absolute orbit errors that refer to particular images. For the 31 images of a sample ENVISAT dataset, orbit corrections with a mutual consistency on the millimetre level have been inferred from 163 interferograms. The method itself qualifies by reliability and rigorous geometric modelling of the orbital error signal but does not consider interfering large scale deformation effects. However, a separation may be feasible in a combined processing with persistent scatterer approaches or by temporal filtering of the estimates.     

Characterization of spatial and temporal variation of suspended sediments in the Yellow and East China Seas using satellite ocean color data

Total suspended sediment (TSS) data concentrations are retrieved from two sets of satellite ocean color data (the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Aqua and the Korean Geostationary Ocean Color Imager (GOCI)) using an existing regional model to characterize spatial and temporal variation of TSS in the Yellow and East China Seas. MODIS-derived TSS maps show that TSS concentrations are, in general, high along the Korean and Chinese coasts including the Bohai Sea and the Yangtz River estuary, and lower in the middle of the Yellow Sea and the southeastern area of the East China Sea. The monthly average of 10-year MODIS data reveals that TSS values are highest during winter (January to February) and lowest in summer (July to August). Short-term TSS concentrations retrieved from GOCI data showed the dominant influence of semi-diurnal tidal changes on sediment dynamics through temporal (hourly) and spatial distribution in coastal zones of the Yellow sea. The results presented here demonstrate that the satellite-derived TSS products can be utilized as an application tool for future studies on long- and short-term sediment dynamics of turbid coastal waters. In particular, GOCI observations provide unique important capabilities to characterize and quantify the water properties at high temporal (hourly) and spatial (0.5 km) resolutions in the turbid coastal waters of the Yellow Sea and its vicinities.     

Modelling and Remote Sensing of Land Surface Temperature in Turkey

This study introduces artificial neural networks (ANNs) for the estimation of land surface temperature (LST) using meteorological and geographical data in Turkey (26?C45°E and 36?C42°N). A generalized regression neural network (GRNN) was used in the network. In order to train the neural network, meteorological and geographical data for the period from January 2002 to December 2002 for 10 stations (Adana, Afyon, Ankara, Eski?ehir, ?stanbul, ?zmir, Konya, Malatya, Rize, Sivas) spread over Turkey were used as training (six stations) and testing (four stations) data. Latitude, longitude, elevation and mean air temperature are used in the input layer of the network. Land surface temperature is the output. However, land surface temperature has been estimated as monthly mean by using NOAA-AVHRR satellite data in the thermal range over 10 stations in Turkey. The RMSE between the estimated and ground values for monthly mean with ANN temperature(LST_ANN) and Becker and Li temperature(LST_B-L) method values have been found as 0.077?K and 0.091?K (training stations), 0.045?K and 0.003?K (testing stations), respectively.     

An Artificial Intelligent design for GPS Surveying Networks

Metaheuristic techniques, which are based on ideas of Artificial Intelligence, are among the best methods for solving computationally the GPS surveying network problem. In this paper, the ant colony optimization metaheuristic, which is inspired by the behavior of real ant colonies, is developed to efficiently provide a general framework for optimizing GPS surveying networks. In this framework, a set of ants co-operate together using an indirect communication procedure to find good GPS observation schedules. A GPS surveying network can be defined as a set of stations, co-ordinated by a series of sessions formed by placing receivers on the stations. The problem is to search for the best order in which to observe these sessions to give the best schedule at minimum cost. Computational results obtained by applying the proposed technique on several networks, with known and unknown optimal schedules, prove the effectiveness of the proposed metaheuristic technique to solve the GPS surveying network problem.     

In-flight performance analysis of the CHAMP BlackJack GPS Receiver

JPL's BlackJack receiver currently represents the most widely used geodetic grade GPS receiver for space applications. Using data from the CHAMP science mission, the in-flight performance of the BlackJack receiver has been assessed and the impact of various software updates performed during the 2.5 years since launch is described. Key aspects of the study comprise the channel allocation, anomalous data points, and the noise level of the code and carrier data. In addition, it has been demonstrated that the code measurements collected onboard the CHAMP satellite are notably affected by multipath errors in the aft-looking hemisphere, which can be attributed to cross-talk between the occultation antenna string and the primary precise orbit determination antenna. For carrier smoothed 10 s normal points, the code noise itself varies between a minimum of 5 cm at high elevations and 0.5 m (C/A) to 1.0 m (P₁, P₂) at 10° elevation. Carrier-phase data exhibit representative errors of 0.2 to 2.5 mm. The results of the CHAMP GPS data analysis contribute to a better understanding and possible improvement of the BlackJack receiver and support the design of optimal data editing and weighting strategies in precise orbit determination applications.     

A note on frame transformations with applications to geodetic datums

Rigorous equations in compact symbolic matrix notation are introduced to transform coordinates and velocities between ITRF frames and modern GPS-based geocentric geodetic datums. The theory is general but, after neglecting higher than second-order terms, it is shown that the equations revert to the formulation currently applied in most major continental datums. We discuss several examples: the North American Datum of 1983 (NAD83), the European Terrestrial Reference System of 1989 (ETRS89), the Geodetic Datum of Australia of 1994 (GDA94), and the South American Geocentric Reference System (SIRGAS). Electronic Publication     

Bathymetric inversion of South China Sea from satellite altimetry data

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