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Forecast‐Cartographic Modeling of Pasture Production of the Volgograd Region Based on Remote Sensing

https://doi.org/10.18470/1992-1098-2020-1-69-78

Abstract

Aim. The work is devoted to identifying the productivity of pasture landscapes in the Volgograd region. The aim was to determine the direction of trends and the values of the coefficients of proportionality which would permit the definition of areas where the productivity of natural zonal vegetation has increased or decreased from 2000 until today. 

Material and Methods. Pasture productivity assessment is based on the analysis of the NDVI vegetation index, which is widely used in such studies. For analysis, specific pasture areas were identified in accordance with Global Land Cover, divided into egular grids and given overlays corresponding with the boundaries of municipalities and landscapes. 

Results. The largest areas of natural zonal pastures are located in the Trans‐Volga region and on the sandy massifs of the Don River valley. About 60% of pasture land has an average weighted average long‐term NDVI value from 0.3 to 0.4, and approximately a quarter – from 0.4 to 0.5. In most parts of the region there are negative NDVI trends. The highest rate of degradation is noted in the Trans‐Volga region. This is associated with larger pasturing loads than in the rest of the region, as well as with the regular occurrence of steppe fires. 

Conclusion. In summation: the productivity trends of zonal pastures in the Volgograd region have been determined, as have areas with different NDVI directions and dynamics. The application of these results in practice should make it possible to predict pasture productivity in various municipal districts and landscapes of the region, and thus assist in the regulation of pasture loads and the mitigation of risks of vegetation degradation.

About the Authors

S. S. Shinkarenko
Department of Geography and Cartography, Institute of Natural Sciences, Volgograd State University; Federal Research Centre for Agroecology, Integrated Land Improvement and Protective Agroforestry, Russian Academy of Sciences
Russian Federation

Stanislav S. Shinkarenko, Cand. Agri. Sciences, Associate Professor

Researcher

100 Prospekt Universitetskiy, Volgograd, 400062. Теl. +7(8442)461639



O. Yu. Kosheleva
Federal Research Centre for Agroecology, Integrated Land Improvement and Protective Agroforestry, Russian Academy of Sciences
Russian Federation
Olga Yu. Kosheleva


D. A. Solodovnikov
Department of Geography and Cartography, Institute of Natural Sciences, Volgograd State University
Russian Federation
Denis A. Solodovnikov


References

1. Shinkarenko S.S., Kosheleva O.Yu., Solodovnikov D.A., Pugacheva A.M. Analysis of pasture resources of Volgograd region in Geoinformation system. Proceedings of Nizhnevolzskiy Agrouniversity Complex: Science and Higher Vocational Education, 2019, no. 1, pp. 123‐130. (In Russian) DOI: 10.32786/2071‐9485‐2019‐01‐15

2. Zolotokrylin A.N., Cherenkova E.A., Titkova T.B. Bioclimatic Subhumid Zone of Russian Plains: Droughts, Desertification, and Land Degradation. Aridnye ekosistemy [Arid ecosystems]. 2018, vol. 24, no. 1 (74), pp. 13‐20. (In Russian)

3. Ryabinina N.O., Kanishchev S.N., Shinkarenko S.S. The current state and dynamics of geosystems in the south‐east of the Russian plain (by the example of the natural parks in Volgograd region). South of Russia: ecology, development, 2018, vol. 13, no. 1, pp. 116‐127. (In Russian) DOI: 10.18470/1992‐1098‐2018‐1‐116‐127

4. Rulev A.S., Kosheleva O.Yu., Shinkarenko S.S. Geomorphological criteria in agroforestry: Lake Elton area (SE Russian plain) case study. Geomorfologiya, 2017, no. 2, pp. 63‐71. (In Russian) DOI: 10.15356/0435‐4281‐2017‐2‐63‐71

5. Tkachenko N.A. Droughts and yield of cereal crops in Volgograd region. Proceedings of Nizhnevolzskiy Agrouniversity Complex: Science and Higher Vocational Education, 2018, no. 4, pp. 171‐178. (In Russian) DOI: 10.32786/2071‐9485‐2018‐04‐24

6. Kouzmina J.V., Treshkin S.E. Climate changes in the basin of the Lower Volga and their influence on the ecosystem. Arid Ecosystems, 2014, iss. 4, pp. 142‐157. DOI: 10.1134/S2079096114030044

7. Kulik K.N., Esmagulova B.Zh., Kosheleva O.Yu., Mushaeva K.B., Shinkarenko S.S. Phytocenoses change of the area between Volga and Ural under the influence of grazing loads. Vestnik Voronezhskogo gosudarstvennogo universiteta. Seriya: Geografiya. Geoekologiya [Proceedings of Voronezh State University. Series: Geography. Geoecology]. 2016, no. 4, pp. 25‐32. (In Russian)

8. Eroshenko F.V., Bartalev S.A., Lapenko N.G., Samofal E.V., Storchak I.G. Capabilities for rangelands state and degradation assessment using remote sensing data. Current problems in remote sensing of the Earth from space, 2018, vol. 5, no. 7, pp. 53‐66. (In Russian) DOI: 10.21046/2070‐7401‐2018‐15‐7‐53‐66

9. Deering D.W. Rangeland reflectance characteristics measured by aircraft and spacecraft sensors, Ph.D. Diss., Texas A&M Universini, College Station, 1978, 338 p.

10. Gao Q.Z., Wan Y.F., Xu H.M., Li Y., Jiangcun W.Z., Borjigidai A. Alpine grassland degradation index and its response to recent climate variability in Northern Tibet, China. Quaternary International, 2010, vol. 226, iss. 1‐2, pp. 143‐150. DOI: 10.1016/j.quaint.2009.10.035

11. Lehnert L.W., Meyer H., Meyer N., Reudenbach Ch., Bendix J. A hyperspectral indicator system for rangeland degradation on the Tibetan Plateau: A case study towards spaceborne monitoring. Ecological Indicators, 2014, vol. 39, pp. 54‐64. DOI: 10.1016/j.ecolind.2013.12.005

12. Telnova N.O. Revealing and mapping long‐term NDVI trends for the analysis of climate change contribution to agroecosystems’ productivity dynamics in the Northern Eurasian forest‐steppe and steppe. Current problems in remote sensing of the Earth from space, 2017, vol. 14, no. 6, pp. 97‐107. (In Russian) DOI: 10.21046/2070‐7401‐2017‐14‐6‐97‐107

13. Chen J., Ban Y., Li S. China: Open access to Earth land‐cover map. Nature, 2014, vol. 514, 434 p. DOI: 10.1038/514434c

14. Rulev A.S., Kanishev S.N., Shinkarenko S.S. Analysis of NDVI seasonal dynamics of natural vegetation of Low Trans‐Volga in Volgograd Region. Current problems in remote sensing of the Earth from space, 2016, vol. 13, no. 4, pp. 113‐123. (In Russian) DOI: 10.21046/2070‐7401‐2016‐13‐20‐113‐123

15. Shvidenko A., Shchepashchenko D., MakKallum Ya. SD‐ROM «Lesa i lesnoe khozyaistvo Rossii» [SD‐ROM «Forests and Forestry in Russia»]. Laxenburg, 2007. (In Russian) Available at: http://www.iiasa.ac.at/Research/FOR/forest_cdrom/index.html (accessed 03.04.2019)

16. Harris I., Jones P.D., Osborn T.J., Lister D.H. Updated high‐resolution grids of monthly climatic observations – the CRU TS3.10 Dataset. Int. J. Climatol., 2014, vol. 34, iss. 3, pp. 623‐642. DOI: 10.1002/joc.3711

17. Vlasenko M.V., Kulik A.K. Modern State of the Steppe Vegetation of the Don Sand Massifs. Agrarnaya Rossiya [Agrarian Russia]. 2017, no. 9, pp. 22‐29. (In Russian)

18. Vdovenko A.V. The specifics of the formation of oleaster shrubs pastures in the area of the Middle Don. Izvestiya Nizhnevolzhskogo agrouniversitetskogo kompleksa: nauka i vysshee professional'noe obrazovanie [Proceedings of Nizhnevolzskiy Agrouniversity Complex: Science and Higher Vocational Education]. 2015, no. 2 (38), pp. 85‐90. (In Russian)

19. Manaenkov A.S., Zhdanov Yu.M., Vdovenko A.V. Reconstruction of shrub pastures of river‐valleys. Izvestiya Nizhnevolzhskogo agrouniversitetskogo kompleksa: nauka i vysshee professional'noe obrazovanie [Proceedings of Nizhnevolzskiy Agrouniversity Complex: Science and Higher Vocational Education]. 2016, no. 4 (44), pp. 70‐76. (In Russian)

20. Shinkarenko S.S., Berdengalieva A.N. Analysis of steppe fires long‐term dynamics in Volgograd Region. Current problems in remote sensing of the Earth from space, 2019, vol. 16, no. 2, pp. 98‐110. (In Russian) DOI: 10.21046/2070‐7401‐2019‐16‐2‐98‐110


Review

For citations:


Shinkarenko S.S., Kosheleva O.Yu., Solodovnikov D.A. Forecast‐Cartographic Modeling of Pasture Production of the Volgograd Region Based on Remote Sensing. South of Russia: ecology, development. 2020;15(1):69-78. (In Russ.) https://doi.org/10.18470/1992-1098-2020-1-69-78

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ISSN 1992-1098 (Print)
ISSN 2413-0958 (Online)