Журнал

About Editorial Board Information for authors and reviewers Publication ethics Contacts User Account: send / review a manuscript
Archive
Volume 21, 2024
Number 1
Volume 20, 2023
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 19, 2022
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 18, 2021
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 17, 2020
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6 Number 7
Volume 16, 2019
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 15, 2018
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6 Number 7
Volume 14, 2017
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6 Number 7
Volume 13, 2016
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 12, 2015
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 11, 2014
Number 1 Number 2 Number 3 Number 4
Volume 10, 2013
Number 1 Number 2 Number 3 Number 4
Volume 9, 2012
Number 1 Number 2 Number 3 Number 4 Number 5
Volume 8, 2011
Number 1 Number 2 Number 3 Number 4
Volume 7, 2010
Number 1 Number 2 Number 3 Number 4
Issue 6, 2009
Volume 1 Volume 2
Issue 5, 2008
Volume 1 Volume 2
Issue 4, 2007
Volume 1 Volume 2
Issue 3, 2006
Volume 1 Volume 2
Issue 2, 2005
Volume 1 Volume 2
Issue 1, 2004
Volume 1
Search
Find:
русский
ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2022, Vol. 19, No. 5, pp. 89-100

Mapping of forest fires in conjunction with anthropogenic objects and forest species in the vicinity of the Eastern Railway

A.V. Bazarov 1, 2 , R.S. Sychev 1, 3 , A.S. Bazarova 1 , O.V. Bazarova 4 
1 Institute of Physical Materials Science SB RAS, Ulan-Ude, Russia
2 Buryat State Agricutural Academy Named after V.R. Philippov, Ulan-Ude, Russia
3 Roslesinforg, Buryat Branch, Ulan-Ude, Russia
4 East Siberia State University of Technology and Management, Ulan-Ude, Russia
Accepted: 27.09.2022
DOI: 10.21046/2070-7401-2022-19-5-89-100
The article discusses the application of the results of cartographic methods as data for a quantitative analysis of the conditions for the occurrence of forest fires. Vector maps of forest fire locations, settlements, a network of roads, and a railway were built based on satellite images, digital maps and information systems that are in the public domain. Forest areas with predominant forest species were mapped using the geodata of the VEGA-Science shared satellite service. Vector layers with points of fires from 2011 to 2020 were built according to the information system of remote monitoring of the Federal Forestry Agency “ISDM-Rosleskhoz”. The use of data from relevant information systems provides a great advantage in organizing geoinformation layers over vast areas in comparison with the routine processing of arrays of satellite images. Geoinformation analysis methods were used to build data series on the distance of fires from infrastructure facilities and on the distribution of fires by forest species. A statistical analysis of the constructed data series was carried out. It is shown that proximity to infrastructure affects the number of fires, and that conifers (pine and larch) are the most fire-prone in the study area.
Keywords: forest fires, mapping, VEGA-Science, ISDM-Rosleskhoz, distance, railway, road, settlements, statistics
Full text

References:

  1. Bartalev S. A., Egorov V. A., Zharko V. O., Loupian E. A., Plotnikov D. E., Khvostikov S. A., Shabanov N. V., Information system for remote monitoring of forest fires of the Federal Forestry Agency of the Russian Federation (state and development prospects), Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2008, Vol. 5, No. 2, pp. 419–129 (in Russian).
  2. Bartalev S. A., Ershov D. V., Korovin G. N., Kotelnikov R. V., Loupian E. A., Shchetinsky V. E., Sputnikovoe kartografirovanie rastitel’nogo pokrova Rossii (Land cover mapping over Russia using Earth observation data), Moscow: IKI RAN, 2016, 208 p. (in Russian).
  3. Berlyant A. M., Kartografiya (Cartography), Moscow: Aspect Press, 2002, 336 p. (in Russian).
  4. Grzhibovsky A. M., Data types, control of distribution and descriptive statistics, Ekologiya cheloveka, 2008, No. 1, pp. 52–58 (in Russian).
  5. Grzhibovsky A. M., Ivanov S. V., Gorbatova M. A., Descriptive statistics using statistica and SPSS software, Nauka i zdravookhranenie, 2016, No. 1, pp. 7–23 (in Russian).
  6. Grzhibovsky A. M., Unguryanu T. N., Dannykh A. B., Analiz biomeditsinskikh dannykh s ispol’zovaniyem paketa statisticheskikh programm SPSS (Analysis of biomedical data using the SPSS statistical software package), Arkhangelsk: Izd. Severnogo gosudarstvennogo meditsinskogo universiteta, 2017, 296 p. (in Russian).
  7. GOST 17.6.1.01-83. Okhrana i zashchita lesov. Terminy i opredeleniya (Nature protection. Forest protection and preservation. Terms and definitions), USSR standard, 1985, 6 p. (in Russian).
  8. Ershov D. V., Korovin G. N., Loupian E. A., Mazurov A. A., Tashchilin S. A., Russian satellite monitoring system for forest fires, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2004, Vol. 1, No. 1, pp. 47–57 (in Russian).
  9. Kataeva L. Yu., On short-term prediction of forest fires in the Nizhny Novgorod Region, Nauka i tekhnika transporta, 2007, No. 4, pp. 47–54 (in Russian).
  10. Matveychuk O. S., Forest fire monitoring, Problems of technosphere safety, Voronezh: Rostov State Transport University, 2019, pp. 104–108 (in Russian).
  11. Petrov V. V., Zhizn’ lesa i cheloveka (The life of the forest and man), Moscow: Nauka, 1985, 132 p. (in Russian).
  12. Sutton T., Dassau O., Sutton M., Vector Spatial Analysis (Buffers), A Gentle Introduction to GIS, 2009, Pt. 9, pp. 83–90.
  13. Akay A. E., Wing M. G., Zengin M., Kose O., Determination of fire-access zones along road networks in fire-sensitive forests, J. Forestry Research, 2017, Vol. 28, No. 3, pp. 557–564, DOI: 10.1007/s11676-016-0283-5.
  14. Badia-Perpinyà A., Pallares-Barbera M., Spatial distribution of ignitions in Mediterranean periurban and rural areas: The case of Catalonia, Intern. J. Wildland Fire, 2006, Vol. 15, No. 2, pp. 187–196, DOI: 10.1071/WF04008.
  15. Bistinas I., Oom D., Sá A. C. L., Harrison S. P., Prentice I. C., Pereira J. M. C., Relationships between human population density and burned area at continental and global scales, PLoS ONE, 2013, Vol. 8, No. 12, pp. 1–12, DOI: 10.1371/journal.pone.0081188.
  16. Castillo Soto M. E., The identification and assessment of areas at risk of forest fire using fuzzy methodology, Applied Geography, 2012, Vol. 35, No. 1–2, pp. 199–207, DOI: 10.1016/j.apgeog.2012.07.001.
  17. Chuvieco E., Salas J., Mapping the spatial distribution of forest fire danger using GIS, Intern. J. Geographical Information Systems, 1996, Vol. 10, No. 3, pp. 333–345, DOI: 10.1080/02693799608902082.
  18. Pereira M. G., Aranha J., Amraoui M., Land cover fire proneness in Europe, Forest Systems, 2014, Vol. 23, No. 3, pp. 598–610, DOI: 10.5424/fs/2014233-06115.
  19. Szczygieł R., Piwnicki J., Kwiatkowski M., Forest fire hazard caused by rail transport and evaluation of the effectiveness of fire belts, Bezpechen’stvo i Tekhnika. Pozharnicha, 2014, No. 34, pp. 65–77, DOI: 10.12845/bitp.34.2.2014.6.