Spatial analysis of protective forest plantations based on geographic information technologies and remote sensing data

View or download the article (Rus)

About the Author

Sergey A. Antonov

FSBSI “North-Caucasian Federal Scientific Agrarian Center”, Laboratory of GIS-technology,
Nikonov str., 49, 356241, Mikhailovsk, Stavropol Territory, Russia,


In many agricultural regions of Russia, significant land areas are degraded and the Stavropol Territory is no exception. Protective forest plantations play an important role in protecting the soil from deflation and water erosion. Significant areas of protective forest plantations are in unsatisfactory condition, which leads to a decrease in the effectiveness of their protective function. As a result of the study, a new methodology was developed for assessing the spatial position of protective forest plantations using geographic information technologies and remote sensing data, which has tested in the territory of the Budyonnovsky District of the Stavropol Territory. It has been established that the existing protective forest plantations in the district are not sufficiently effective in protecting the arable land from deflation. Only 5 % of protective forest plantations are located at recommended distances from each other and 10 % are at an optimal angle to the most harmful winds. The low efficiency of protective forest plantations is associated with the peculiarities of their design at the initial stages of creating a protective framework, their achievement of the maximum age, as well as significant damage resulting from human activities. To assess the effectiveness of protective forest plantations in combating water erosion, we developed an original methodology for adjusting the digital elevation model SRTM in order to eliminate local elevations of the relief at the locations of protective forest plantations. It was found that the horizontal indicator of the boundaries in the territory of the Budyonnovsky District is 11 %, which indicates that protective forest plantations in the district were created primarily to protect the arable land from deflation. The presented methodological approaches can be used to adjust existing, and design new protective forest plantations.


geographic information technologies, remote sensing data, deflation, protective forest plantations, method


  1. Antonov S.A., Esaulko A.N., Sigida M.S., Golosnoy E.V. The estimation of water erosion processes on Stavropol Region agricultural landscapes and their impact on productivity. Agricultural Bulletin of Stavropol Region, 2018. No 1 (29). P. 67–73. DOI: 10.25930/vmg3-j684 (in Russian).
  2. Elkhrachy I. Vertical accuracy assessment for SRTM and ASTER Digital Elevation Models: A case study of Najran city, Saudi Arabia. Ain Shams Engineering Journal, 2018. V. 9. Iss. 4. P. 1807–1817. DOI: 10.1016/j.asej.2017.01.007.
  3. Esaulko A., Sigida M., Golosnoy E., Antonov S., Lobankova O. Condition monitoring and analysis of development in winter crops of water erosion processes using remote sensing technologies. Engineering for Rural Development, 2019. V. 18. P. 391–397. DOI: 10.22616/ERDev2019.18.N204.
  4. Gerasimov Yu.Yu., Hlyustov V.K., Kilpilyanen S.A., Borovikov N.Z. Aerospace methods in forestry: Textbook. Petrozavodsk: PetrSU, 2002. 248 p. (in Russian).
  5. Kholupyak K.L. The arrangement of anti-erosion forest plantations. Moscow: Forest Industry, 1973. 152 p. (in Russian).
  6. Kulik K.N., Koshelev A.V. Methodological basis for agroforestry assessment of protective forest stands according to remote monitoring data. Lesotekhnicheskiy zhurnal [Forestry Engineering Journal], 2017. No 3 (27). P. 107–114. DOI: 10.12737/article_59c22527885b57. 91268039 (in Russian).
  7. Kulik K.N., Kosheleva O.Yu. Automated decryption of protective forest stands from high-resolution satellite imagery. Reports of the Russian Academy of Agricultural Sciences, 2011. No 3. P. 55–57 (in Russian).
  8. Kulik K.N., Pugacheva A.M. Forest reclamation — the basis for creating sustainable agrolandscapes in conditions of insufficient moisture. Lesotekhnicheskiy zhurnal (Forestry Engineering Journal), 2016. V. 6. No 3 (23). P. 29–40 (in Russian).
  9. Kulik K.N., Rulev A.S. Geoinformation mapping in agroforestry. Reports of the Russian Academy of Agricultural Sciences, 2000. No 1. P. 42–43 (in Russian).
  10. Malysheva N.V. Cartographic support of the state forest fund using GIS. Forestry, 2007. No 3. P. 40–42 (in Russian).
  11. Pavlovskii E.S., Vinogradov B.V., Borovikov N.Z. Aerospace methods in agroforestry. Vestnik (Herald) of the Russian agricultural science, 1985. No 7 (346). P. 100–105 (in Russian).
  12. Rodin A.R., Rodin S.A., Vasiliev S.B., Silaev G.V. Land reclamation of landscapes: Textbook. Moscow: Moscow State Forestry University (MSFU), 2014. 192 p. (in Russian).
  13. Santillan J.R., Makinano-Santillan M. Vertical accuracy assessment of 30-m resolution ALOS, ASTER and SRTM global DEMS over Northeastern Mindanao, Philippines. XXIII ISPRS Congress. Comission IV. International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences, 2016. V. 41. Iss. B4. P. 149–156. DOI: 10.5194/isprsarchives-XLI-B4-149-2016.
  14. Sukhikh V.I. Contribution of aerospace methods to the development of Russian forestry. Forestry, 1998. No 3. P. 34–37 (in Russian).
  15. Sukhikh V.I. The formation of space methods in the forestry of Russia. Forestry, 2001. No 2. P. 6–11 (in Russian).
  16. Tskhovrebov V.S., Tul’panov V.I., Podsvirov V.I. The current state of the Central Ciscaucasia soils. Proceedings of the Second International Scientific Conference “Evolution and degradation of soil cover”, 2002. V. 1. P. 15–17 (in Russian).

For citation: Antonov S.A. Spatial analysis of protective forest plantations based on geographic information technologies and remote sensing data InterCarto. InterGIS. GI support of sustainable development of territories: Proceedings of the International conference. Moscow: Moscow University Press, 2020. V. 26. Part 2. P. 408–420. DOI: 10.35595/2414-9179-2020-2-26-408-420 (In Russian)