Abstract. In the cadastral operations, geodesic measurements are extremely necessary. These measurements must be accurate and precise. In the present work, we studied the measurement accuracy of electronic measuring devices and tried to emphasize the influence of atmospheric parameters on measurement accuracy.
Forest vegetation across Southern Carpathians is distributed in altitudinal layers. The aim of this study was to highlight the productivity differences between the Southern and Northern slopes of the Southern Carpathians for Norway spruce, silver fir, birch and black alder. Data from 45 forest management plans (46.329 stands from the Southern slopes and 32.787 stands from the Northern slopes) were used. For each stand, the mean diameter, mean height, age, standing volume, current volume increment and production class were assessed. Elementary statistical methods were used to identify the factors influencing productivity. Significant differences between the Southern and Northern slopes were recorded for silver fir. The volume and the current volume increment were higher on the Northern slopes. In the case of birch and black alder, the same two parameters recorded higher values on the Southern slopes. As regards Norway spruce, insignificant differences were recorded between the two slopes. The correlation between structure type and stand volume was positive and statistically significant in the case of Norway spruce, silver fir and birch, but it was negative in the case of alder. Analysing the correlation between stand volume and the main stand characteristics also revealed a statistically significant positive correlation between age and stand volume for all analysed species. The results of this study are especially interested for the forest managers and forest owners whose aim is to obtain a higher productivity for the studied species.
The identification of a temporal evolution model for complex systems has, since ancient times, been a subject of great interest. Whether it is mechanical systems for which it was essential knowledge of the final state or electrical systems, the problem of identifying evolution over time has always been extremely interesting. In the case of a complex system such as a river, whose condition is described by a set of physico-chemical parameters, the time description of the evolution of the state becomes a rather difficult problem. In this paper, two ways of identifying and predicting the parameters describing the state of such a system are presented. A LRS type algorithm and a process of approximating evolution over time considering neural networks was used for comparison. Recorded series of pH and carbonic acid values were used as study parameters. The data used covers the period 1990-1998 and consists of measurements of the water samples taken from the Danube River in the area of Galati City. The main result was to obtain a rapid convergence for the adaptive filter used. For comparison, a number of 6 neural network models were built. Finally, findings and discussion of the results are presented.
In this paper are presented preliminary results of seasonal statistical approach on monitoring of a series of drilled water well corresponding on a surface of about a quarter of Galati County which has a total area of 4,466 square km. In order to offer an adequate picture of the status of this natural resource we started a monthly monitoring program that cover approximatively 20 monitoring points for two years. The study is an extension of previous research, with a total of 21 sampling points.
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