Журнал

About Editorial Board Information for authors and reviewers Publication ethics Contacts User Account: send / review a manuscript
Archive
Volume 21, 2024
Number 1 Number 2 Number 3 Number 4 Number 5
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, 2021, Vol. 18, No. 4, pp. 140-148

Detection of clear-cuts using satellite-derived global forest change product

E.G. Shvetsov 1 , E.I. Ponomarev 1 
1 Krasnoyarsk Science Center SB RAS, Krasnoyarsk, Russia
Accepted: 05.07.2021
DOI: 10.21046/2070-7401-2021-18-4-140-148
We propose a method for logged areas monitoring using a satellite product of global forest change based on Landsat data and additional GIS layers (land cover, fires). A thematic clear-cut product was created for the Lower Angara region covering 2001–2019 with a spatial resolution of 30 m. The accuracy assessment performed for a sample of clear-cut polygons (about 1500 polygons) in the Angara forest region showed that the thematic product tends to underestimate clear-cut areas roughly by 20 %. The magnitude of the error of the first type (logged area that was missed by the algorithm) was about 27 % of the total area, while the error of the second type (erroneously classified clear cuts) was about 8 %. Total disturbed area between 2001 and 2019 was about 1.8 million ha, while the total area of clear-cuts was 512 thousand ha. Almost 43 % of all logged area occurred in pine-dominated (Pinus silvestris) forest stands, 26 % — in dark coniferous (Pinus sibirica, Abies sibirica, Picea obovata) stands, 25 % — in larch (Larix sibirica) stands and 5 % — in deciduous (Betula spp. , Populus tremula) forests. Mean logged area is ~27.0±12.2 thousand hectares per year. Linear approximation shows a statistically significant trend (r2 = 0.63) of an increase in the logged area within the study area.
Keywords: Angara forest region, clear-cuts, remote sensing data, Landsat
Full text

References:

  1. Bartalev S. A., Stytsenko F. V., Egorov V. A., Loupian E. A., Satellite-based assessment of Russian forest fire mortality, Lesovedenie, 2015, Vol. 2, pp. 83–94 (in Russian).
  2. Bartalev S. A., Egorov V. A., Zharko V. O., Loupian E. A., Plotnikov D. E., Khvostikov S., Shabanov N., Land cover mapping over Russia using Earth observation data, Moscow: IKI RAN, 2016, 208 p. (in Russian).
  3. Valendik E. N., Matveev P. M., Sofronov M. A., Krupnye lesnye pozhary (Large forest fires), Moscow: Nauka, 1979, 198 p.
  4. On approval of the list of forest zones of the Russian Federation and the list of forest regions of the Russian Federation: Order No. 367, Date 18.08.2014 (as amended on 19.02.2019), Moscow, 2014 (in Russian), available at: https://docs.cntd.ru/document/420224339.
  5. Ponomarev E. I., Shvetsov E. G., Satellite detection of forest fires and geoinformation methods of calibration of the results, Issledovanie Zemli iz kosmosa, 2015, No. 1, pp. 84–94 (in Russian).
  6. Galiatsatos N., Donoghue D. N. M., Watt P., Bholanath P., Pickering J., Hansen M. C., Mahmood A. R. J., An Assessment of Global Forest Change Datasets for National Forest Monitoring and Reporting, Remote Sensing, 2020, Vol. 12, Art. No. 1790.
  7. Gauthier S., Bernier P., Kuuluvainen T., Shvidenko A. Z., Schepaschenko D. G., Boreal forest health and global change, Science, 2015, Vol. 349, pp. 819–822.
  8. Global Forest Resources Assessment 2015, Desk reference, FAO, Rome, 2015, 253 p., available at: http://www.fao.org/3/a-i4808e.pdf.
  9. Hansen M. C., Potapov P. V., Moore R., Hancher M., Turubanova S. A., Tyukavin A., Thau D., Stehman S. V., Goetz S. J., Loveland T. R., Kommareddy A., Egorov A., Chini L., Justice C. O., Townshend J. R.G., High-Resolution Global Maps of 21st-Century Forest Cover Change, Science, 2013, Vol. 342, pp. 850–853.
  10. Kharuk V. I., Antamoshkina O. A., Impact of silkmoth outbreak on taiga wildfires, Contemporary Problems of Ecology, 2017, Vol. 10, No. 5, pp. 556–562.
  11. Krylov A., McCarty J. L., Potapov P., Loboda T., Tyukavina A., Turubanova  S., Hansen M. C., Remote sensing estimates of stand-replacement fires in Russia, 2002–2011, Environmental Research Letters 2014, Vol. 9, Art. No. 105007.
  12. Ponomarev E. I., Masyagina O. V., Litvintsev K. Y., Ponomareva T. V., Shvetsov E. G., Finnikov K. A., The effect of post-fire disturbances on a seasonally thawed layer in the permafrost larch forests of Central Siberia, Forests, 2020, Vol. 11(8), Art. No. 790.