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, 2023, Vol. 20, No. 4, pp. 175-186

Estimation of defoliation features in dark coniferous tree stands after the impact of Siberian silk moth according to remote data

E.I. Ponomarev 1, 2, 3 , N.D. Yakimov 1, 3 , P.D. Tretyakov 1, 3 , S.M. Sultson 3 
1 Krasnoyarsk Science Center SB RAS, Krasnoyarsk, Russia
2 Siberian Federal University, Krasnoyarsk, Russia
3 Reshetnev Siberian State University of Science and Technology, Krasnoyarsk, Russia
Accepted: 25.07.2023
DOI: 10.21046/2070-7401-2023-20-4-175-186
The paper presents the results of the analysis of defoliation features in the dark coniferous tree stands after the impact of the Siberian silkmoth (Dendrolimus sibiricus) in the mountain dark coniferous taiga of the Irbey forestry of the Krasnoyarsk Region of Central Siberia in 2018–2020. Landsat-8 OLI/TIRS (Operational Land Imager/Thermal Infrared Sensor) materials were used, as well as information about forest stands and forest taxation characteristics in the format of a vector layer for taxons within the zone of Siberian silkmoth infestation. The degree of forest stand disturbance was assessed in terms of the relative anomaly of the vegetation index (Δrel, %) compared with the characteristic background values for three variants of the dominant dark coniferous stands: fir (Abies sibirica), Siberian pine (Pinus sibirica) and spruce (Picea obovata). A transition was made from pixel-by-pixel data to values averaged over taxons and related to dominant tree stands. It is shown that the threshold values of the relative anomaly Δrel at the level of 10, 25, 50 % make it possible to detail the degree of defoliation according to 5 classes of the state of damaged areas. A conjugated analysis involving forest inventory data made it possible to emphasize the differences in the rate of defoliation features on satellite imagery, as well as to indirectly assess the resistance of the dominant dark coniferous (fir, Siberian pine and spruce stands) to the silkmoth impact, in terms of the portion of the area, with signs of extreme defoliation on final stage of outbreak development in 2020.
Keywords: Siberia, dark coniferous taiga, Siberian silkmoth (Dendrolimus sibiricus), satellite data, Landsat, NDVI
Full text

References:

  1. Bartalev S. A., Ershov D. V., Isaev A. S., Estimation of Forest Defoliation in Multispectral Satellite Images by a Spectral Mixture Decomposition Method, Issledovanie Zemli iz kosmosa, 1999, No. 4, pp. 76–86 (in Russian).
  2. Zhirin V. M., Knyazeva S. V., Eydlina S. P., Long-term dynamics of vegetation indices in dark coniferous forest after Siberian moth disturbance, Contemporary Problems of Ecology, 2016, Vol. 9, No. 7, pp. 834–843, DOI: 10.1134/S1995425516070118.
  3. Im S. T., Fedotova E. V., Kharuk V. I., Spectroradiometer Data in Siberian Silkmoth Outbreak Zone Analysis, Tekhnika i tekhnologii, 2008, No. 1, pp. 346–358 (In Russian).
  4. Knyazeva S. V., Koroleva N. V., Eidlina S. P., Sochilova E. N., Health of vegetation in the area of mass outbreaks of Siberian moth based on satellite data, Contemporary Problems of Ecology, 2019, Vol. 12, No. 7, pp. 743–752, https://doi.org/10.1134/S1995425519070114.
  5. Kondakov Yu. P., Patterns of mass reproduction of the Siberian silkmoth, Ecology of Forest Animals in Siberia, 1974, pp. 206–265 (in Russian).
  6. Kharuk V. I., Antamoshkina O. A., Impact of Silkmoth Outbreak on Taiga Wildfires, Contemporary Problems of Ecology, 2017, Vol. 10, pp. 556–562, https://doi.org/10.1134/S1995425517050055.
  7. Creeden E. P., Hicke J. A., Buotte P. C., Climate, weather, and recent mountain pine beetle outbreaks in the western United States, Forest Ecology and Management, 2014, Vol. 312, pp. 239–251, https://doi.org/10.1016/j.foreco.2013.09.051.
  8. Flø D., Rafoss T., Wendell M., Sundheim L., The Siberian moth (Dendrolimus sibiricus), a pest risk assessment for Norway, Forest Ecosystems, 2020, Vol. 7, Article 48, https://doi.org/10.1186/s40663-020-00258-9.
  9. Foster J. R., Townsend P. A., Mladenoff D. J., Spatial dynamics of a gypsy moth defoliation outbreak and dependence on habitat characteristics, Landscapes Ecology, 2013, Vol. 28, pp. 1307–1320, https://doi.org/10.1007/s10980-013-9879-8.
  10. Guha S., Govil H., Land surface temperature and normalized difference vegetation index relationship: A seasonal study on a tropical city, SN Applied Sciences, 2020, Vol. 2, Article 1661, https://doi.org/10.1007/s42452-020-03458-8.
  11. Kharuk V. I., Ranson K. J., Kozuhovskaya A. G. et al., NOAA/AVHRR satellite detection of Siberian silkmoth outbreaks in eastern Siberia, Intern. J. Remote Sensing, 2004, Vol. 25, No. 24, pp. 5543–5555, https://doi.org/10.1080/01431160410001719858.
  12. Kharuk V. I., Im S. T., Soldatov V. V., Siberian silkmoth outbreaks surpassed geoclimatic barrier in Siberian Mountains, J. Mountain Science, 2020, Vol. 17, pp. 1891–1900, https://doi.org/10.1007/s11629-020-5989-3.
  13. Kirichenko N. I., Baranchikov Y. N., Vidal S., Performance of the potentially invasive Siberian moth Dendrolimus superans sibiricus on coniferous species in Europe, Agricultural and Forest Entomology, 2009, Vol. 11, No. 3, pp. 247–254, https://doi.org/10.1111/j.1461-9563.2009.00437.x.
  14. Kovalev A., Soukhovolsky V., Analysis of Forest Stand Resistance to Insect Attack According to Remote Sensing Data, Forests, 2021, Vol. 12, Article 1188, https://doi.org/10.3390/f12091188.
  15. Loupian E., Burtsev M., Proshin A. et al., Usage Experience and Capabilities of the VEGA-Science System, Remote Sensing, 2022, Vol. 14, Article 77, https://doi.org/10.3390/rs14010077.
  16. Möykkynen T., Pukkala T., Modelling of the spread of a potential invasive pest, the Siberian moth (Dendrolimus sibiricus) in Europe, Forest Ecosystems, 2014, Vol. 1, Article 10, https://doi.org/10.1186/s40663-014-0010-7.
  17. Niinemets Ü., Responses of forest trees to single and multiple environmental stresses from seedlings to mature plants: Past stress history, stress interactions, tolerance and acclimation, Forest Ecology and Management, 2010, Vol. 260, No. 10, pp. 1623–1639, DOI: 10.1016/j.foreco.2010.07.054.
  18. Pavlov I. N., Litovka Y. A., Golubev D. V., Astapenko S. A., Chromogin P. V., New outbreak of Dendrolimus sibiricus tschetv. in Siberia (2012–2017): monitoring, modeling and biological control, Contemporary Problems of Ecology, 2018, Vol. 11, No. 4, pp. 406–419, https://doi.org/10.1134/S1995425518040054.
  19. Soukhovolsky V., Kovalev A., Tarasova O. et al., Wind Damage and Temperature Effect on Tree Mortality Caused by Ips Typographus L.: Phase Transition Model, Forests, 2022, Vol. 13, Article 180, https://doi.org/10.3390/f13020180.
  20. Sultson S. M., Goroshko A. A., Verkhovets S. V. et al., Orographic Factors as a Predictor of the Spread of the Siberian Silk Moth Outbreak in the Mountainous Southern Taiga Forests of Siberia, Land, 2021, Vol. 10, Article 115, https://doi.org/10.3390/land10020115.
  21. Teixeira Pinto C., Jing X., Leigh L., Evaluation Analysis of Landsat Level-1 and Level-2 Data Products Using in situ Measurements, Remote Sensing, 2020, Vol. 12, Article 2597, https://doi.org/10.3390/rs12162597.