In last years, accurate spatial data from high resolution satellite images are getting more and more frequently used for modelling topography and other surveying purposes. To extract accurate spatial information, a sensor's mathematical models are needed. Those models classified to two branches: rigorous (parameirical or physical) models and non-rigorous models. In the paper a dynamic sensor model is proposed to extract spatial information from geo-rectified images named the geo-images which their geometry at the time of imaging have been lost. The developed model has been reconstructed basing on a transformation of central-perspective projection into a parallel one.

Today, the new era with Very High Resolution Satellite (VHRS) imageries as IKON OS, QuickBird, EROS, Orb View etc., provides orthophoto in large scale of 1 :5 OOO, to update existing maps, to compile general-purpose or thematic maps. Orthophotomap in the scale of I :5 OOO with Ground Sampling Distance of 0.5 m is one of three important sources for establishing GIS together with a Digital Elevation Model of ±LO m accuracy in height and a topographic map in the scale of 1: IO OOO. Therefore, the accuracy of products of VHRS imageries affects reliability of GIS. Nevertheless, the accuracy of products of processing VHRS imageries is at first dependent on chosen geometrical sensor models. The understanding of geometrical sensor models of VHRS imageries is very important for improving processing of VHRS imageries. The polynomial models are to provide a simple, generic set of equations to represent the indirect relationship between the ground and its image. The polynomial models or replacement sensor models must not only model the ground-to-image relationship accurately. Physical (or parametrical) model describes dir~ctly strict geometrical relations between the terrain and its image, using satellite's orbital parameters and basing on the co-linearity condition. In such model, the above-mentioned multi-source distorting factors are taken into consideration. In this paper a review of practical accuracy of geometrical models of VHRS imageries taken from different research institutions in the world in last years has been presented.

Since 2000 when first imageries of Space Imaging of one metre resolution satellite products appeared on the World market, many institutions started using them for cartographic production such as orthophotomaps on a large scale. A choice of the mathematic sensor models of imageries for their orthorectification in producing orthophotomaps is one of the main investigation directions. In order to restitute the functional relation between imageries and their ground space, the use of sensor models is required. They can be grouped into two classes, the generalized sensor models (geometric or replacement sensor models) and physical or parametric models. The paper presents a brief overview of the geometric models such as RPC (Rational Polynomial Coefficients). Their properties, and in particular their advantages and disadvantages are discussed. Also the parametric models, developed by the authors are presented in this paper. They are based on time-dependent collinearity equation of the mathematic relation between ground space and its imageries through parameters describing the sensor position in satellite orbit and position of the orbit in the geocentric system.