No abstract

Measurements in engineering surveying are aimed at determining the coordinates of the points of a geodetic control, spatially setting out a technical design of an engineering structure, determining the spatial coordinates of points (or their displacement) that represent an engineering structure, and identifying the displacement and deformation of a studied engineering structure. Provided that the aforementioned measurements are to represent the same engineering structure, such observation results should be settled (adjusted) in one calculation process. The application of the Gauss-Markov theorem for this adjustment using covariance matrix Cov(L) for observed values L is the classical approach for adjusting the results of surveying observations of various accuracy (taking into account accuracy weights). Determining the displacements of points in the process of adjusting the results of periodic measurements, applying different methods of tying geodetic controls to national networks, and using various instruments and measurement methods result in the individual displacement components or coordinates of the observed points being determined with different accuracies. This circumstance forms the basis for the assumption that the estimated parameters (unknown values) should be random. This paper will formulate the principles of estimation of Gauss-Markov models in which the estimated parameters (X) are random. For this purpose, methods for the prior definition of covariance matrix C X for the estimated parameters will be provided, which will be used to determine the conditional covariance matrix of observation vector L and then to estimate the most probable values of the X parameters. Covariance matrix Cov(X) obtained as a result of this estimation will be used to define the limit values of the variances of these parameters.

In this paper, the authors verified the formulated principles of the estimation of Gauss-Markov models in which estimated parameters X were random. For this purpose, methods for the prior definition of covariance matrix C X for the estimated parameters were provided, which were used to determine the conditional covariance matrix of observation vector L and then estimate the most probable values of parameters X . Covariance matrix Cov(X) obtained as a result of this estimation was used to define the limit values of the variance of these parameters. Practical application of the proposed method for the Gauss-Markov model estimation for random parameters was illustrated on a fragment of a leveling network of points to determine the vertical displacements of a landslide surface.

In Poland, it often happens that construction objects are subject to demolition work for different reasons.Demolition, according the Construction Law, is defined as a type of construction works and, as such, represents a particular type of construction project. As in other construction projects, a very important phase, in addition to execution of the works, is to prepare, design and plan demolition works. Some demolition activities are covered by appropriate regulations and can be described as typical. On the other hand the technical side of demolition works depends on many factors such as: the type of building, its age, technical condition, type of construction, etc.This article covers the analysis of the stages and tasks in the preparatory phase of the building demolition. This work will also present a description of the tasks carried out during the demolition works based on the example of a historic tenement house located in Krakow. This analysis aims to identify implementation problems and sources of risk that may occur during this type of construction work.

Procedura powszechnej taksacji nieruchomości w Polsce