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. 164-175

Assessing the extent of landscape fires in the Middle Amur Lowland using long-term satellite data time series

A.V. Ostroukhov 1 
1 Institute of the Water and Ecology Problems FEB RAS, Khabarovsk, Russia
Accepted: 18.10.2022
DOI: 10.21046/2070-7401-2022-19-5-164-175
Studies of pyrogenic transformation of the landscapes of the temperate zone of the Russian Federation have traditionally focused on analyzing the impact of forest fires. However, the extent of landscape fires in non-forest geosystems, where they are also widespread, is still poorly understood. An assessment of the long-term average scale, recurrence, and spatial specificity of landscape fires in non-forest geosystems of the Middle Amur Lowland, in the Russian Federation’s Khabarovsk Territory, was carried out using an analysis of long-term series of remote sensing data of the Earth of medium spatial resolution (Landsat-5, -7, -8). According to the findings, fires affect 25.4 % of the total area of the study region on average each year, but in some years, this figure exceeds 50 %. Large areas of the territory were exposed to repeated fire, from 2 to 36 times in 37 years. During this period, fires covered more than 38 million ha, accounting for 938 % of the total land area of the Middle Amur lowland. Forest fires accounted for only 12 % of this area in this case. At the same time, fires passed through meadow and meadow-mire geosystems, as well as floodplain areas (the area of fires in them equals 1317.4 % of the total area of these geosystems). The spatial distribution of fires in the territory is related not only to the degree of development of the territory and transportation infrastructure, but also to the specifics of nature management, and are frequently caused by hunting, fishing, and collecting wild plants, which determines the high frequency of fires along rivers and lakes in the northern and central parts of the plain. A comparison of the data obtained with the materials of automatic mapping of fires and their consequences reveals that the methods used in automatic mapping of burns are insufficiently accurate, resulting in a significant underestimation of the area of fires in non-forest lands.
Keywords: landscape fires, remote sensing data, Landsat, non-forest geosystems, Middle Amur Lowland
Full text

References:

  1. Ageenko A. S., Lesa Dal’nego Vostoka (Forests of the Far East), Moscow: Lesnaya promyshlennost’, 1969, 392 p. (in Russian).
  2. Maiorova L. P., Sadykov A. I., Sych Y. I., Assessment of emissions and carbon dioxide emissions in forest fires (illustrated Khabarovsk territory), Uchenye zametki TOGU, 2013, Vol. 4, No. 4, pp. 9–13 (in Russian), http://ejournal.khstu.ru/media/2013/TGU_4_27.pdf.
  3. Shinkarenko S. S., Doroshenko V. V., Berdengalieva A. N., Komarova I. A., Dynamics of arid landscapes burning in Russia and adjacent territories based on active fire data, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2021, Vol. 18, No. 1, pp. 149–164 (in Russian), DOI: 10.21046/2070-7401-2021-18-1-149-164.
  4. Shinkarenko S. S., Bartalev S. A., Berdengalieva A. N., Ivanov N. M., Spatio-temporal analysis of the combustibility of floodplain landscapes of the Lower Volga, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2022, Vol. 19, No. 1, pp. 143–157 (in Russian), DOI: 10.21046/2070-7401-2022-19-1-143-157.
  5. Argañaraz J., Gavier-Pizarro G., Zak M., Bellis L., Fire regime, climate, and vegetation in the Sierras de Córdoba, Argentina, Fire Ecology, 2015, No. 11, pp. 55–73, https://doi.org/10.4996/fireecology.1101055.
  6. Bartalev S. A., Egorov V. A., Loupian E. A., Uvarov I., Multiyear circumpolar assessment of the area burnt in boreal ecosystems using SPOT-Vegetation. Intern. J. Remote Sensing, 2007, Vol. 28, Issue 6, pp. 1397–1404, https://doi.org/10.1080/01431160600840978.
  7. Korontzi S., McCarty J., Loboda T., Kumar S., Justice C., Global distribution of agricultural fires in croplands from 3 years of Moderate Resolution Imaging Spectroradiometer (MODIS) data, Global Biogeochemical Cycles, 2006, Vol. 20, Issue 2, Art. No. GB2021, https://doi.org/10.1029/2005GB002529.
  8. Kukavskaya E. A., Soja A. J., Petkov A. P., Ponomarev E. I., Ivanova G. A., Conard S. G., Fire emissions estimates in Siberia: Evaluation of uncertainties in area burned, land cover, and fuel consumption, Canadian J. Forest Research, 2012, Vol. 43, No. 5, pp. 493–506, https://doi.org/10.1139/cjfr-2012-0367.
  9. Kusangaya S., Sithole V. B., Remote sensing-based fire frequency mapping in a savannah rangeland. South African J. Geomatics, 2015, Vol. 4, No. 1, pp. 36–49, DOI: 10.4314/sajg.v4i1.3.
  10. Li J., Li Y., Bo Y., Xie S., High-resolution historical emission inventories of crop residue burning in fields in China for the period 1990–2013, Atmospheric Environment, 2016, Vol. 138, pp. 152–161, DOI: https://doi.org/10.1016/j.atmosenv.2016.05.002.
  11. McCarty J., Krylov A., Prishchepov A., Banach D., Tyukavina A., Potapov P., Turubanova S., Agricultural fires in European Russia, Belarus, and Lithuania and their impact on air quality, 2002–2012, In: Land-Cover and Land-Use Changes in Eastern Europe after the Collapse of the Soviet Union in 1991, Gutman G., Radeloff V. (eds.), Cham, Switzerland: Springer Intern. Publ., 2017, pp. 193–221, DOI: 10.1007/978-3-319-42638-9_9.
  12. Oliva P., Martín P., Chuvieco E., Burned area mapping with MERIS post-fire image. Intern. J. Remote Sensing, 2011, Vol. 32, Issue 15, pp. 4175–4201, https://doi.org/10.1080/01431161.2010.489062.
  13. Ostroukhov A. V., Klimina E. M., Survey of Middle Amur lowland terrain transformations based on remote sensing data, Proc. Joint Symp. Tropical Peatland Restoration: Responsible Management of Tropical Peatland following up to the Jakarta Declaration, Jakarta, Indonesia, 22 Feb. 2018, Bogor, Indonesia: IKAPI, 2018, pp. 123–129.
  14. Poulter B., Christensen N. L., Halpin P. N., Carbon emissions from a temperate peat fire and its relevance to interannual variability of trace atmospheric greenhouse gases. J. Geophysical Research, 2006, Vol. 111, Issue D6, Art. No. D06301, 11 p., https://doi.org/10.1029/2005JD006455.
  15. Romanenkov V., Rukhovich D., Koroleva P., McCarty J., Estimating black carbon emissions from agricultural burning, In: Novel Measurement and Assessment Tools for Monitoring and Management of Land and Water Resources in Agricultural Landscapes of Central Asia, Book Ser.: Environmental Science and Engineering, Mueller L., Saparov A., Lischeid G. (eds.), Cham, Switzerland: Springer Intern. Publ., 2014, pp. 347–364, DOI: 10.1007/978-3-319-01017-5_20.
  16. Sannigrahi S., Pilla F., Basu B., Basu A. S., Sarkar K., Chakraborti S., Joshi P. K., Zhang Q., Wang Y., Bhatt S., Examining the effects of forest fire on terrestrial carbon emission and ecosystem production in India using remote sensing approaches. Science of the Total Environment, 2020, No. 725, Art. No. 138331, https://doi.org/10.1016/j.scitotenv.2020.138331.
  17. Sheingauz A., The role of fire in forest cover, structure, and dynamics in the Russian Far East, In: Fire in Ecosystems of Boreal Eurasia, Book Ser.: Forestry Sciences, Goldammer I. G., Furyaev V. V. (eds.), Dodrecht; Boston; London: Kluwer Academic Publ., 1996, Vol. 48, pp. 186–190, DOI: 10.1007/978-94-015-8737-2_13.
  18. Tishkov A. A., Fires in Steppes and Savannas, Natural Disasters, Vol. 2, Encyclopedia of Life Support Systems, Kotlyakov V. M. (ed.), Oxford, UK: EOLSS Publ., 2010, pp. 144–158.
  19. Vivchar A. V., Moiseenko K. B., Pankratova N. V., Estimates of carbon monoxide emissions from wildfires in Northern Eurasia for air quality assessment and climate modeling. Izvestiya, Atmospheric and Oceanic Physics, 2010, No. 46, pp. 281–293, https://doi.org/10.1134/S0001433810030023.