Skip to main content
SpringerLink
Log in

Evaluation of the Normalized Differential Vegetation Index as a Source of Information on Aboveground Phytomass in Steppes

  • USE OF SPACE INFORMATION ABOUT THE EARTH LAND USE RESEARCH FROM SPACE
  • Published:
Izvestiya, Atmospheric and Oceanic Physics Aims and scope Submit manuscript

Abstract

Labor consumption of phytomass measurements on sample plots hinders the extrapolation of point data to areas comparable to commercial lands or landscape units. Vegetation indices calculated from satellite images are usually considered indicators of green phytomass; they are used for its areal estimates. The task of this study is to establish the informativity of the normalized differential vegetation index (NDVI) depending on the fractional structure of living and dead aboveground phytomass, seasonal dynamics of the biological cycle, hydrothermal conditions, and landscape position. The results of monthly measurements of aboveground phytomass fractions on 13 sites in phytocenoses of forest feather grass and feather grass formations in the Burtinskaya steppe (Orenburg Nature Reserve) from May to September 2015–2020 were used. The NDVI values were calculated for each period from Landsat satellite images at all sites. Hypotheses about geobotanical, hydrothermal, phonological, and landscape factors of NDVI informativity were tested by calculating the Spearman correlation coefficients using the dispersion and multiregression analysis. The discrepancy between the seasonal peaks of the NDVI and green phytomass is not consistent with the common concept of a direct indicator value of the NDVI. The total live biomass correlates more clearly with the index in June and July; the correlation is lower in the end of the season. The NDVI index turned out to be sensitive not so much to the reserves of green phytomass, but more to the mass and proportion of forbs and the ratio of live and dead phytomass. In late spring and early summer, the NDVI is most closely associated with forbs and, in July, with cereals. The hypothesis about the possibility of screening green mass with standing dead biomass was confirmed, which leads to a decrease in the NDVI despite the preservation or growth of green phytomass. The NDVI may underestimate the real green phytomass if there is a sharp increase in the mass of standing dead biomass, usually in the second half of summer and early autumn. The NDVI more adequately reflects the state of the aboveground phytomass of steppe communities that have not been exposed to fires for a long time when compared with burned communities and fallows.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.

REFERENCES

  1. Araya, S., Ostendorf, B., Lyle, G., and Lewis, M., Remote sensing derived phenological metrics to assess the spatio–temporal growth variability in cropping fields, Adv. Remote Sens., 2017, vol. 6, pp. 212–228.

    Article  Google Scholar 

  2. Ayurzhanaev, A.A., Alymbaeva, Zh.B., Zharnikova, M.A., and Sodnomov, B.V., On the possibility of assessing the above-ground phytomass of steppe vegetation using colored vegetation indices (according to survey data from unmanned systems), Vestn. Buryat. Gos. Univ., Biol-., Geogr., 2021, no. 4, pp. 45–53.

  3. Bazilevich, N.I., Titlyanova, A.A., Smirnov, V.V., Rodin, L.E., Nechaeva, N.I., and Levin, F.I., Metody izucheniya biologicheskogo krugovorota v razlichnykh prirodnykh zonakh (Methods for Studying Biological Cycles in Various Natural Regions), Moskva: Mysl’, 1978.

  4. Dusaeva, G.Kh. and Maksutova, N.V., Seasonal dynamics of aboveground phytomass stocks in forb–oatmeal–fescue–forested–feather-grass community with Poa transbaicalica and Spiraea crenata, Vestn. Orenburg. Gos. Univ., 2017, no. 11, pp. 79–83.

  5. Dusaeva, G.Kh., Maksutova, N.V., and Kalmykova, O.G., Seasonal dynamics of the aboveground phytomass of the forb–oatmeal–fescue–forested–feather-grass community, in Sokhranenie raznoobraziya rastitel’nogo mira Tuvy i sopredel’nykh regionov Tsentral’noi Azii: istoriya, sovremennost', perspektivy (Preservation of the Diversity of Flora of Tuva and Adjacent Regions of Central Asia: History, Modernity, and Prospects), Kyzyl: TuvIKOPR SO RAN, 2016, pp. 67–69.

  6. Dusaeva, G.Kh., Kalmykova, O.G., and Dusaeva, N.V., Fire influence on dynamics of above-ground phytomass in steppe plant communities in the Burtinskaya steppe (Orenburg state nature reserve, Russia), Nat. Conserv. Res., 2019, vol. 4, no. S1, pp. 78–92. https://doi.org/10.24189/ncr.2019.050

    Article  Google Scholar 

  7. Dusaeva, G.Kh., Kalmykova, O.G., and Dusaeva, N.V., Fire influence on the dynamics of underground phytomass of steppe phytocenoses in the Burtinskaya step’ section of the Orenburg reserve, Ekosistemy, 2020, no. 24, pp. 83–92.

  8. Elsakov, V.V., Satellite imagery in assessing the productivity of ecosystems in the European North, Sovrem. Probl. Distantsionnogo Zondirovaniya Zemli Kosmosa, 2012, vol. 9, no. 1, pp. 71–79.

    Google Scholar 

  9. Elsakov, V.V. and Telyatnikov, M.Yu., Interannual changes in the NDVI index in the European northeast of Russia and western Siberia under climatic fluctuations of recent decades, Sovrem. Probl. Distantsionnogo Zondirovaniya Zemli Kosmosa, 2013, vol. 10, no. 3, pp. 260–271.

    Google Scholar 

  10. Eroshenko, F.V., Bartalev, S.A., Lapenko, N.G., Samofal, E.V., and Storchak, I.G., The potential of remote assessment of the state and extent of degradation of natural fodder lands, Sovrem. Probl. Distantsionnogo Zondirovaniya Zemli Kosmosa, 2018, vol. 15, no. 7, pp. 53–66.

    Article  Google Scholar 

  11. Gamon, J.A., Huemmrich, K.F., Stone, R.S., and Tweedie, C.E., Spatial and temporal variation in primary productivity (NDVI) of coastal Alaskan tundra: Decreased vegetation growth following earlier snowmelt, Remote Sens. Environ., 2013, vol. 129, pp. 144–153.

    Article  Google Scholar 

  12. Gao, Y., Huang, J., Li, S., and Li, Sh., Spatial pattern of non-stationarity and scale-dependent relationships between NDVI and climatic factors: A case study in Qinghai-Tibet Plateau, China, Ecol. Indicators, 2012, vol. 20, pp. 170–176.

    Article  Google Scholar 

  13. Gopp, N.V., Nechaeva, T.V., Savenkov, O.A., Smirnova, N.V., and Smirnov, V.V., Evaluation of the slope mesorelief effect on the spatial variability of soil properties and vegetation cover characteristics according to Earth remote sensing data), Issled. Zemli Kosmosa, 2016, no. 3, pp. 66–74.

  14. Gulyanov, Yu.A., Monitoring of phytometric parameters using innovative crop scanning methods, Tavr. Vestn.: Agrar. Nauki, 2019, no. 3, pp. 64–76. https://doi.org/10.33952/2542-0720-2019-3-19-64-76

  15. Han, J.C., Huang, Y., Zhang, H., and Wu, X., Characterization of elevation and land cover dependent trends of NDVI variations in the Hexi region, northwest China, J. Environ. Manage., 2019, vol. 232, pp. 1037–1048.

    Article  Google Scholar 

  16. de Jong, R., Verbesselt, J., Schaepman, M.E., and Bruin, S.D., Trend changes in global greening and browning: Contribution of short-term trends to longer-term change, Global Change Biol., 2012, vol. 18, no. 2, pp. 642–655.

    Article  Google Scholar 

  17. Kalmykova, O.G., On the vegetation cover of the Orenburg State Reserve, Izv. Samar. Nauchn. Tsentra Ross. Akad. Nauk, 2012, vol. 14, no. 1, pp. 1024–1026.

    Google Scholar 

  18. Krasnaya kniga pochv Orenburgskoi oblasti (Red Book of Soils of the Orenburg Region), Ekaterinburg, 2001.

  19. Kurganovich, K.A. and Golyatina, M.A., Spatiotemporal response of NDVI to changes in climatic characteristics in the Trans-Baikal territory from 2000 to 2014, Vestn. Zabaik. Gos. Univ., 2015, no. 9, pp. 10–20.

  20. Lidzhieva, N.Ts., Ulanova, S.S., and Fedorova, N.L., The experience of using the vegetation index (NDVI) to determine the biological productivity of phytocenoses in arid zones on the example of the Chernye Zemlya region, Izv. Saratov. Univ.: Ser. Khim., Biol., Ekol., 2012, vol. 12, no. 2.

  21. Lyle, G., Lewis, M., and Ostendorf, B., Testing the temporal ability of Landsat imagery and precision agriculture technology to provide high resolution historical estimates of wheat yield at the farm scale, Remote Sens., 2013, vol. 5, pp. 1549–1567.

    Article  Google Scholar 

  22. Maksutova, N.V., Dusaeva, G.Kh., and Kalmykova, O.G., Seasonal dynamics of the aboveground phytomass of the forb–oatmeal–fescue–forested–feather-grass community, in Sokhranenie raznoobraziya rastitel’nogo mira Tuvy i sopredel’nykh regionov Tsentral’noi Azii: istoriya, sovremennost', perspektivy (Preservation of the Diversity of Flora of Tuva and Adjacent Regions of Central Asia: History, Modernity, and Prospects), Kyzyl: TuvIKOPR SO RAN, 2016, pp. 77–80.

  23. Maynard, J.J. and Levi, M.R., Hyper-temporal remote sensing for digital soil mapping: characterizing soil–vegetation response to climatic variability, Geoderma, 2017, vol. 285, pp. 94–109.

    Article  Google Scholar 

  24. Mikhailov, V.V., Spesivtsev, A.V., and Sobolevskii, V.A., Multimodel evaluation of phytomass dynamics of tundra plant communities based on satellite images, Izv., Atmos. Ocean. Phys., 2021, vol. 57, no. 9, pp. 1198–1210.

    Article  Google Scholar 

  25. Nagy, A., Fehér, J., and Tamás, T., Wheat and maize yield forecasting for the Tisza river catchment using MODIS NDVI time series and reported crop statistics, Comput. Electron. Agric., 2018, vol. 151, pp. 41–49.

    Article  Google Scholar 

  26. Nemtseva, L.D., Bespalova, L.A., Golubeva, E.I., and Mikhailov, S.I., Assessment of the state of vegetation cover of dry-steppe landscapes under grazing conditions using methods of remote sensing of the Earth, Tr. YuNTs RAN, 2018, vol. 2, pp. 151–164.

    Google Scholar 

  27. Peng, W., Kuang, T., and Tao, T., Quantifying influences of natural factors on vegetation NDVI changes based on geographical detector in Sichuan, western China, J. Cleaner Prod., 2019, vol. 233, pp. 353–367.

    Article  Google Scholar 

  28. Piao, S.L., Nan, H.J., Huntingford, C., Ciais, P., Friedingstein, P., Sitch, S., Peng, S.S., Ahlstrom, A., Canadell, J.G., Cong, N., Levis, S., Levy, P.E., Liu, L.L., Lomas, M.R., Mao, J.F., et al., Evidence for a weakening relationship between interannual temperature variability and northern vegetation activity, Nat. Commun., 2014, vol. 5, p. 5018.

    Article  Google Scholar 

  29. Piedallu, C., Cheret, V., Denux, J.P., Perez, V., Azcona, J.S., Seynave, I., and Gegout, J.C., Soil and climate differently impact NDVI patterns according to the season and the stand type, Sci. Total Environ., 2019, vol. 651, pp. 2874–2885.

    Article  Google Scholar 

  30. Polevaya geobotanika (Field Geobotany), Lavrenko, E.M. and Korchagin, A.A., Eds., Moscow–Leningrad: Nauka, 1964, vol. 3.

    Google Scholar 

  31. Rabotnov, T.A., Fitotsenologiya (Phytocenology), Moscow: MGU, 1992.

    Google Scholar 

  32. Rulev, A.S., Kanishchev, S.N., and Shinkarenko, S.S., Analysis of the seasonal dynamics of NDVI in natural vegetation of the Trans-Volga area of the Volgograd region, Sovrem. Probl. Distantsionnogo Zondirovaniya Zemli Kosmosa, 2016, vol. 13, no. 4, pp. 113–123.

    Article  Google Scholar 

  33. Safronova, I.N. and Kalmykova, O.G., Zonality problems and the role of nature reserves in their solution, Izv. Samar. Nauchn. Tsentra Ross. Akad. Nauk, 2012, vol. 14, no. 1, pp. 1638–1641.

    Google Scholar 

  34. Savin, I.Yu., Tanov, E.R., and Kharzinov, S., Using the vegetation index NDVI to assess the quality of arable soils (on the example of the Baksan district of Kabardino–Balkaria), Byull. Pochv. Inst. im. V.V. Dokuchaeva, 2015, no. 77, pp. 51–65.

  35. Titlyanova, A.A., Bazilevich, N.I., Shmakova, E.I., Snytko, V.A., Dubynina, S.S., Magomedova, L.N., Nefed’eva, L.G., Semenyuk, N.V., Tishkov, A.A., Ti, T., Khakimzyanova, F.I., Shatokhina, N.G., Kyrgys, Ch.O., and Sambuu, A.D., Biologicheskaya produktivnost' travyanykh ekosistem. Geograficheskie zakonomernosti i ekologicheskie osobennosti (Biological Productivity of Grass Ecosystems. Geographic Patterns and Ecological Features). Novosibirsk: IPA SO RAN, 2018.

    Google Scholar 

  36. Verhulst, N. and Govaerts, B., The Normalized Difference Vegetation Index (NDVI) GreenSeeker™ Handheld Sensor: Toward the Integrated Evaluation of Crop Management. Part A: Concepts and Case Studies, Mexico: CIMMYT, 2010.

    Google Scholar 

  37. Yaroshenko, P.D., Geobotanika (Geobotanics), Moscow–Leningrad: Akad. Nauk SSSR, 1961.

    Google Scholar 

  38. Zalikhanov, M.Ch., Kolomyts, E.G., Sharaya, L.S., Tsepkova, N.L., and Surova, N.A., Vysokogornaya geoekologiya v modelyakh (High-Altitude Geoecology in Models), Moscow: Nauka, 2010.

  39. Zhao, Z., Gao, J., Wang, Y., Liu, J., and Li, S., Exploring spatially variable relationships between NDVI and climatic factors in a transition zone using geographically weighted regression, Theor. Appl. Climatol., 2015, vol. 120, nos. 3–4, pp. 507–519. https://doi.org/10.1007/s00704-014-1188-x

    Article  Google Scholar 

  40. Zhukov, A.V., Kunakh, O.N., Zadorozhnaya, G.A., and Andrusevich, E.V., Landscape ecology as a basis for spatial analysis of the productivity of agrocenoses, Ecol. Noospherol., 2013, vol. 24, nos. 1–2.

  41. Zolotokrylin, A.N., Cherenkova, E.A., and Titkova, T.B., Aridization of drylands in the European part of Russia: Secular trends and links to droughts, Izv. Ross. Akad. Nauk: Ser. Geogr., 2020, no. 2, pp. 207–217. https://doi.org/10.31857/S258755662002017X

Download references

ACKNOWLEDGMENTS

The authors are grateful to A.P. Ashikhmin for participation in the preparation of remote data.

Funding

This study was supported by the Russian Foundation for Basic Research (project no. 20-05-00464).

Author information

Authors and Affiliations

  1. Moscow State University, Moscow, Russia

    A. V. Khoroshev

  2. Institute of Steppe, Ural Branch of the Russian Academy of Sciences, Orenburg, Russia

    O. G. Kalmykova & G. Kh. Dusaeva

Authors
  1. A. V. Khoroshev
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. O. G. Kalmykova
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. G. Kh. Dusaeva
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to A. V. Khoroshev.

Ethics declarations

The authors of this work declare that they have no conflicts of interest.

Additional information

Translated by E. Morozov

Publisher’s Note.

Pleiades Publishing remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Khoroshev, A.V., Kalmykova, O.G. & Dusaeva, G.K. Evaluation of the Normalized Differential Vegetation Index as a Source of Information on Aboveground Phytomass in Steppes. Izv. Atmos. Ocean. Phys. 59, 1166–1179 (2023). https://doi.org/10.1134/S0001433823090116

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S0001433823090116

Keywords:

Search

Navigation