The main goal of the article is to develop a toolkit algorithm for the application of computer modelling in the analysis of hazardous areas during flooding using ArcGIS software for representatives of administrative-territorial authorities. The created toolkit algorithm can be utilized at the regional and local self-government levels for analysing potential negative consequences of flooding, followed by decision-making regarding the implementation of appropriate protective measures. The authors have developed a toolkit algorithm for the application of computer modelling to analyse hazardous areas during the flooding of territories using ArcGIS software, specifically designed for representatives of administrative-territorial authorities. This algorithm involves modelling the watershed basins of the area and identifying hazardous areas that may pose additional dangers or lead to a “domino effect” during the flooding of the studied territory. The authors have identified a list of hazardous areas that pose additional risks to the population’s livelihood in the territory that may be affected by flooding. Additionally, the practical application of the proposed computer modelling algorithm has been examined using the example of the Drohobych district in the Lviv region, where frequent flooding has been observed in the past. The Drohobych district includes the territorial communities of Medenychi, Drohobych, Truskavets, Skhidnytsia, and Boryslav. In the region, there are two solid household waste landfills near the villages of Bronytsia and the city of Boryslav, which can be considered hazardous areas in the event of flooding. The greatest danger of consecutive contaminations due to flooding occurs in the area of the cities of Borislav and Truskavets. Water covers four cemeteries and comes dangerously close to the landfill as a result of flooded territories. The city of Drohobych is in a relatively safe zone; however, the water sources supplying the city are within the boundaries of the city of Truskavets, which also causes an additional danger to these and adjacent settlements. Subsequently, the developed toolkit algorithm can be utilized at the regional and community levels for analysing potential negative consequences of flooding, followed by decision-making regarding the implementation of appropriate engineering protection measures in specific areas.
The subject of the study is the forecasting of fires, on the example of Australian events in the winter of 2013, using the spatial location of fire-hazardous areas. To do this, several approaches were used to visualize data in space and time. A temporary map has been created showing the points of fires using a color scheme linked to the date. A series of small multiple visualizations has been developed. A time series has been created in which the regularity of the brightness of points is distributed depending on the date of origin and animated maps that allow you to view data in space and time. In this case, the geographic information system was used as the main tool when working with maps, as it is one of the best ways to process georeferenced data displayed on the map. A space-time cube is displayed, which displays data in 3D format, or rather, fire points, symbolized by the average temperature of the fire (displayed in different colors) in accordance with the day of the month. Finally, clusters of focal points were created using the space-time framework in the ArcGIS software environment. The described results of using the method of spatial location of fire hazardous zones, in addition to the direct task – localization of fire points (fires), this method makes it possible to study patterns in spatial and temporal scales, with the possibility of further visualization of the spatio-temporal cube in 3D format in the ArcScene program, which will allow more efficient predict fire hazardous periods and areas in the study area. The method of spatial location of fire hazardous areas can be used for any investigated area for which there are statistical and spatial data, both for the purpose of localizing fires, and for the purpose of studying patterns in selected space-time scales.
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