A.V. Iatsyshyn, Yu. G. Kutsan, V.O. Artemchuk,
I.P. Kameneva, O.O. Popov, V.O. Kovach
Èlektron. model. 2019, 41(5):85-102
https://doi.org/10.15407/emodel.41.05.085
ABSTRACT
The main tasks of monitoring the atmospheric air and the requirements for improving the network
of environmental monitoring are analyzed in the context of reducing the negative impacts on urban
areas and population of industrial cities in Ukraine. Modern tools and tools for analyzing
large volumes of structured and unstructured geospatial data, such as Big Data processing methods
and geospatial data mining methods, are presented. The adaptation of separate means for the
monitoring of atmospheric air has been made. Examples of intellectual analysis and visualization
of geospatial data reflecting the levels of man-made loads on atmospheric air are given.
KEYWORDS
ecological safety, monitoring network, intellectual analysis, data visualization, atmospheric air.
REFERENCES
https://doi.org/10.1007/978-3-642-32180-1_1
2. Dias, D. and Tchepel, O. (2014), “Modelling of human exposure to air pollution in the urban environment: a GPS-based approach”, Environmental Science and Pollution Research 21.5, pp. 3558-3571.
https://doi.org/10.1007/s11356-013-2277-6
3. Meier, F. (2015), “Challenges and benefits from crowdsourced atmospheric data for urban climate research using Berlin, Germany, as testbed”, the Proceeding of the 9th International Conference on Urban Climate.
4. Peters, D. (2014), Harnessing the power of big data: infusing the scientific method with machine learning to transform ecology, Ecosphere, pp. 1-15.
https://doi.org/10.1890/ES13-00359.1
5. “Algorithms of the intellectual data analysis”, available at: https://tproger.ru/translations/top-10-data-mining-algorithms/ (accessed February 25, 2019).
6. Shitikov, V.K., Mastitsky, S.E. (2019), “Classification, regression, Data Mining algorithms using R”, available at: https://github.com/ranalytics/data-mining (accessed May 2, 2019).
7. Iatsyshyn, A.V., Kutsan, Yu.G., Artemchuk, V.O., Kameneva, I.P., Popov, O.O. and Kovach,V.O. (2019), “The principles andmethods of ecological safetymanagement through the data of air monitoring network analysis”, Elektronne modelyuvannya, Vol. 41, no. 4.
https://doi.org/10.15407/emodel.41.04.085
8. Artemchuk, V.O., Bilan, T.R. and Blinov, I.V. (2017), Teoretychni ta prykladni osnovy ekonomichnoho, ekolohichnoho ta tekhnolohichnoho funktsionuvannya ob"yektiv enerhetyky [Theoretical and applied bases of economic, ecological and technological functioning of energy objects], Nash format, Kyiv, Ukraine.
9. Artemchuk, V.O., Kameneva, I.P. and Yatsyshyn, A.V. (2017), “Specificity of the application of cognitive analysis of information in the tasks of ensuring environmental safety”, Elektronnoe modelirovanie, Vol. 39, no. 6, pp. 107-124.
https://doi.org/10.15407/emodel.39.06.107
10. Yatsyshyn, A.V. (2013), “Comprehensive assessment and management of environmental safety in air pollution”, Abstract of Doct. Sci. (Tech.) dissertation, 21.06.01, SI “Institute of Environmental Geochemistry of NAS of Ukraine”, Kiev, Ukraine.
11. Johnson, K. (2001), ArcGIS Geostatistical Analyst. Rukovodstvo pol'zovatelya [ArcGIS Geostatistical Analyst. User's manual], Data+, Moscow, Russia.
12. Kapralov, E.G. (2008), Geoinformatika: uchebnik dlya vuzov [Geoinformatics: a textbook for universities], Izdatel'skiy tsentr “Akademiya”, Moscow, Russia.
13. Putrenko, V.V. (2015), “The system basis of data mining of geospatial data”, Systemni doslidzhennya ta informatsiyni tekhnolohiyi, no. 3, pp. 20-33.
14. Artemchuk, V.O., Kameneva, I.P. and Yatsyshyn, A.V. (2016), “Models of representation and data transformation in the problems of environmental monitoring in urban areas”, Elektronnoye. modelirovaniye, Vol. 38, no. 2, pp. 49-66.
https://doi.org/10.15407/emodel.38.02.049
15. Orange, available at: http://orange.biolab.si/download/ (accessed February 2, 2019).
16. Kryviy Rih. Automated surveillance posts, available at: https://krmisto.gov.ua/ua/rc/ecomon.html (accessed February 2, 2019).