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[1] We provide a technique to efficiently produce high-resolution three-dimensional surface motion maps by combining information about the motion of the Earth's surface from interferometric observations of synthetic aperture radar images and repeated Global Positioning System (GPS) geodetic measurements. Unwrapped interferograms, showing pixel-wise change in range from ground to satellite, and sparse values of threedimensional movements are required as input. The problem of finding the full threedimensional motion field is separated into two two-dimensional problems. Initially, the vertical component of the deformation field and its horizontal component in the look direction of the satellite are found. Later, the look direction component is resolved into north and east components. Initial values for the motion fields are assigned to each pixel of interferograms from interpolation of available GPS observations. These values are then updated and optimized by comparison with the interferograms and the GPS observations. An additional constraint is an assumption of a smoothly varying motion field. Markov random field-based regularization and simulated annealing algorithm are used for the optimization. The technique is applied to create surface motion maps for the Reykjanes Peninsula, SW Iceland.INDEX TERMS: 0933 Exploration Geophysics: Remote sensing; 0910 Exploration Geophysics: Data processing; 1206 Geodesy and Gravity: Crustal movements-interplate (8155); 8150 Tectonophysics: Evolution of the Earth: Plate boundary-general (3040); 8155 Tectonophysics: Evolution of the Earth: Plate motions-general; KEYWORDS: remote sensing, motion maps, deformation, data fusion, interferometry, GPS Citation: Gudmundsson, S., F. Sigmundsson, and J. M. Carstensen, Three-dimensional surface motion maps estimated from combined interferometric synthetic aperture radar and GPS data,

Multispectral imaging is a new technology that is being deployed to assess seed quality parameters. Examples of applications in the detection and identification of fungi on seeds are presented, together with an example of the technology used for maturity determination in sugar beet seed. Results from multispectral imaging are compared with reference methods, and a high correlation is found. Applications of the technique for varietal discrimination and insect damage are also presented. There is a need for non-destructive, reliable and fast techniques, and it is concluded that multispectral imaging has potential for seed quality assessment, in particular for those components associated with surface structure and chemical composition, seed colour, morphology and size.

AbstractÐFactorization algorithms for recovering structure and motion from an image stream have many advantages, but they usually require a set of well-tracked features. Such a set is in generally not available in practical applications. There is thus a need for making factorization algorithms deal effectively with errors in the tracked features. We propose a new and computationally efficient algorithm for applying an arbitrary error function in the factorization scheme. This algorithm enables the use of robust statistical techniques and arbitrary noise models for the individual features. These techniques and models enable the factorization scheme to deal effectively with mismatched features, missing features, and noise on the individual features. The proposed approach further includes a new method for Euclidean reconstruction that significantly improves convergence of the factorization algorithms. The proposed algorithm has been implemented as a modification of the Christy-Horaud factorization scheme, which yields a perspective reconstruction. Based on this implementation, a considerable increase in error tolerance is demonstrated on real and synthetic data. The proposed scheme can, however, be applied to most other factorization algorithms.