Геопросторове моделювання радононебезпечної території
Methods for identification of potentially radon-prone areas using geospatial analysis in ArcGIS 10.6 software environment and mathematical modeling in SPSS 19.0 on the example of high background radiation area have been developed. High level of natural radioactivity associated with uranium content i...
Збережено в:
Дата: | 2020 |
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Автори: | , , , , |
Формат: | Стаття |
Мова: | English |
Опубліковано: |
State Scientific and Technical Center for Nuclear and Radiation Safety
2020
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Онлайн доступ: | https://nuclear-journal.com/index.php/journal/article/view/383 |
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Назва журналу: | Nuclear and Radiation Safety |
Репозитарії
Nuclear and Radiation SafetyРезюме: | Methods for identification of potentially radon-prone areas using geospatial analysis in ArcGIS 10.6 software environment and mathematical modeling in SPSS 19.0 on the example of high background radiation area have been developed. High level of natural radioactivity associated with uranium content in environment objects and natural uranium occurrences, and also the spatial density of faults (reliable and unreliable) and lineaments were taken into account as well as the distance from uranium mine located nearby.
The method of linear discriminant functions was used to make a math model for determining the level of radon hazard. To do this, data on all locations were divided into training and test samples. Determination of predictors of the mathematical model was performed using Fisher's criterion by their sequential inclusion in discriminant equations. Among the considered 13 factors of radon hazard, seven of them turned out to be informative. For them, canonical coefficients were calculated using the least squares method for first- and second-order polynomials. Based on the values of discriminant functions, a territorial map was constructed to assign the new location to a certain level of radon hazard.
The maps obtained present the correlation of the radon-prone areas with the zones of high spatial density of faults and lineaments, and confirmed by the data of direct indoor radon measurements. In a limited number of measurements, the methods might get a good help in prioritization for round-the-country radon survey. As far as the model for identification of potentially radon-prone areas is mainly based on geological studies, the further research is supposed to be directed to its approbation for a different geological environment of the Ukrainian shield. |
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