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https://sci.ldubgd.edu.ua/jspui/handle/123456789/11465| Title: | Visualization of fire in space and time on the basis of the method of spatial location of fire-dangerous areas |
| Authors: | Havrys, Andrii Yakovchuk, Roman Pekarska, Oleksandra Tur, Nazarii |
| Keywords: | civil protection fire points |
| Issue Date: | 2023 |
| Citation: | 1. Abdulsahib, G. M., & Khalaf, O. I. 2018. An improved algorithm to fire detection in forest by using wireless sensor networks. International Journal of Civil Engineering & Technology (IJCIET)-Scopus Indexed, 9(11), 369-377. 2. Muhammad, K., Khan, S., Elhoseny, M., Ahmed, S. H., & Baik, S. W. 2019. Efficient fire detection for uncertain surveillance environment. IEEE Transactions on Industrial Informatics, 15(5), 3113-3122. 3. Li, P., & Zhao, W. 2020. Image fire detection algorithms based on convolutional neural networks. Case Studies in Thermal Engineering, 19, 100625. 4. Luo, Y., Zhao, L., Liu, P., & Huang, D. 2018. Fire smoke detection algorithm based on motion characteristic and convolutional neural networks. Multimedia Tools and Applications, 77(12), 15075-15092. 5. Havrys, A.P., Moreniuk,R.Ya., Harasymiuk, I.M. 2019. Method of spatial location of fire-dangerous sites on the basis of Remote Sensing and Spatial Data. Naukovyi visnyk NLTU Ukrainy [Scientific bulletin of UNFU]. P.29(8): 36-42. DOI:10.36930/40290804[in Ukrainian]. 6. Nikolaevich, K. V., Starodub, Y., & Havrys, A. 2021. Computer Modeling in the Application to Geothermal Engineering. Advances in Civil Engineering, 2021. 7. Yakovchuk R., Kuzyk A., Skorobagatko T., Yemelyanenko S., Borys O., Dobrostan O. 2020. Computer simulation of fire test parameters façade heat insulating system for fire spread in fire dynamics simulator (FDS). News of the National Academy of Sciences of the Republic of Kazakhstan. Series of geology and technology sciences. Volume 4, Number 442 (2020), pp. 35 – 44. https://doi.org/10.32014/2020.2518-170X.82. 8. Popovych, V., Renkas, A. 2019. Features of Landscape Fires Occurrence (Based on the Example of Lviv Region of Ukraine). Ecologia Balkanica. Vol. 11, Issue 2. 99-111. 9. EARTHDATA. 2020. Active Fire Data | Earthdata. [online] Available at: https://earthdata.nasa.gov/earth-observation-data/near-real-time/firms/active-fire-data. 10. Starodub, Y. P., & Havrys, A. P. 2015a. Use of HEC-GEORAS and HEC-RAS assistant software in territorial security projects. Project management and development of production, 1(53), 30 35. Luhansk [in Ukrainian]. 11. Starodub, Y. P., & Havrys, A. P. 2015b. Increasing areas security project for the risk flooding territories of Ukraine. Central European Journal for Science and Research Stredoevropsky Vestnik pro vedu a vyzkum, 42 46. Praha. 12. Zatserkovnyi, V. I., Tishayev, I. V., & Shyshenko, O. I. 2016. Application of remote probe materials in tasks of forest monitoring and quantitative of vegetation. Science-intensive technologies, 1(29), 42 47 [in Ukrainian]. 13. Popovych, V., Gapalo, A. 2021. Monitoring of Ground Forest Fire Impact on Heavy Metals Content in Edafic Horizons. Journal of Ecological Engineering. 22(5). 96-103. https://doi.org/10.12911/22998993/135872. 14. Renkas, A.A., Popovych, V.V., Dominik, A.M. 2021. Method for determining the optimal location of firefighting equipment for localization of ground forest fires. News of the National Academy of Sciences of the Republic of Kazakhstan, Series of Geology and Technical Sciences. 2(446). 144-150. https://doi.org/10.32014/2021.2518-170X.46 15. Artur Renkas, Vasyl Popovych, Dmytro Rudenko. 2022. Optimization of Fire Station Locations to Increase the Efficiency of Firefighting in Natural Ecosystems. Journal of Environmental Research, Engineering and Management Vol. 78 / No. 1 / 2022 pp. 97–104. https://doi.org/10.5755/j01.erem.78.1.25581. 16. Liu, D., Xu, Z., & Fan, C. 2019. Generalized analysis of regional fire risk using data visualization of incidents. Fire and materials, 43(4), 413-421. 17. Li, J., Li, X., Chen, C., Zheng, H., & Liu, N. 2018. Three-dimensional dynamic simulation system for forest surface fire spreading prediction. 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[online] Available at: http://www.bbc.co.uk/news/world-asia-20967410> [Accessed 19 May 2021]. 23. Official data on the occurrence of wildfires in Tasmania, Australia for 2013. Retrieved from: http://www.tasmanianbushfires.com.au/tasmanian-bushfires-2013/. 24. ArcGIS Resources. 2012. ArcGIS Help 10.1. [online] Available at: http://resources.arcgis.com/en/help/main/10.1/index.html#/ [Accessed 19 May 2021]. |
| Abstract: | 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. |
| URI: | https://sci.ldubgd.edu.ua/jspui/handle/123456789/11465 |
| Appears in Collections: | 2023 |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Стаття EEET Scopus.pdf | 6.15 MB | Adobe PDF | View/Open |
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