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1
Content available remote Geospatial data processing characteristics for environmental monitoring tasks
EN
This paper explores the specifics of working with geospatial data when making decisions about the current environmental status of objects based on Earth space monitoring data. The expediency of sharing statistical data, Earth remote sensing data, and contact measurements is displayed. An analysis of the specifics of this approach to solving the problems of complex processing of multi-temporal a priori data obtained by various shooting equipment was carried out. The existing methods for combining such data are analyzed and possible options for reducing temporary resources and reducing requirements for information resources when working with large volumes of information are considered. It is appropriate to use the method of hierarchical partitioning of multi-temporal image data or images of the analyzed areas obtained at the same time, but from different satellites taking into account the specifics of the shooting equipment and subject to their correspondence to the given a priori geospatial information. One of the criteria for hierarchical partitioning is the identification of areas of greatest correspondence with a priori data with their geographical reference in satellite imagery to reduce the localization time of the corresponding zones throughout the analyzed image array. The economic application effect of this method is substantiated by reducing the computational complexity of costly pattern matching processes, as well as performance improvement of change determination algorithms in topological and geometric characteristics of these objects. An algorithm is shown for detecting changes in heterogeneity in images based on the result of overlay operations with time-differentiated satellite imagery. To confirm the adequacy of the proposed method, the results of its practical implementation are shown on the Ukraine-Poland border area. A comparative analysis of the obtained results with real data is carried out.
EN
A comprehensive approach to assessing the current ecological status of the Poland-Ukraine border areas has been considered, identifying possible negative effects associated with river water pollution. The main environmental impact factors that are directly related to the negative effects of anthropogenic load on the changing ecological status of the border areas and adjacent terrain have been identified. Particular attention was paid to the pollution monitoring data analysis of the Ukrainian part of the Western Bug basin. Using the space monitoring results, pollution sources that were not recorded in the official reports were identified. Their negative impact on the change of quality of life within the border areas was assessed. The integration specificities of heterogeneous time-differentiated ecosystem monitoring data were considered. The integration expediency of interdisciplinary joint analysis methods of decryption data and field observations for making operational decisions to prevent negative consequences of possible changes in the ecological status is shown. Modelling was utilized to determine the estimated contamination time of the river systems of Western Bug and Vistula from the Ukraine territory. The tendency of further changes in the ecological status of the analyzed areas has been ascertained, including the assessment of possible negative consequences.
PL
W bezprzewodowych sieciach sensorowych przeznaczonych do monitorowania dużych obszarów ziemi konieczne jest wyznaczenie pokrycia monitorowanej przestrzeni przez rozmieszczone w niej czujniki. W artykule przedstawiono metodę określania pokrycia przez obliczenie ścieżki najmniejszej ekspozycji i opisano algorytm umożliwiający wyznaczanie jej lokalnie, bez konieczności przesyłania danych o lokalizacji wszystkich węzłów sieci do centralnego komputera systemu.
EN
It is needed, for wireless sensor networks monitoring large areas of land, calculation of coverage. Using the minimal exposure path to evaluate a network is important since the user can manipulate sensors in the network or add algorithm helps to calculate coverage on-line, locally with only neighbour nodes engaged. It is efficient method since discovering the all network topography is costly in terms of computation and energy consumption.
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