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The Use of NDVI in Digital Mapping of the Content of Available Lithium in the Arable Horizon of Soils in Southwestern Siberia

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Abstract

We have determined the informational value of the Normalized Difference Vegetation Index (NDVI) for predictive mapping of the content of available lithium in the arable horizon of soils of different slope positions: the first (280–310 m) and the second (240–280 m) altitudinal levels. The NDVI is not informative for the diagnostics or mapping of the content of available lithium in soils of small drainage valleys, the width of which is smaller than the resolution of the satellite image (30 m). In the regression model, the NDVI explains 28% of the variation in the content of available lithium in soils. Based on this model, a predictive map of the content of available lithium in soils has been compiled. Data on the spatial distribution pattern of the NDVI calculated based on a Landsat 8 satellite image (resolution of 30 m) were used as an indicator and the cartographical basis for digital mapping. The accuracy of the prediction of the content of available lithium in soils is good (MAPE is 16.9%). It has been revealed that the NDVI values and the content of available lithium in soils of the first altitudinal level are higher than in the second. The differences between NDVI in the drainage valley and on the first altitudinal level are not insignificant.

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REFERENCES

  1. Afanas’ev, V.N. and Tsypin, A.P., Ekonometrika v pakete STATISTICA: uchebnoe posobie po vypolneniyu lanoratornykh rabot (Econometrics in the STATISTICA Package: A Textbook for Laboratory Works), Orenburg: GOU OGU, 2008.

  2. Akhmetov, R.M., Lithium in the geotechnosphere of the Southern Urals, Geol. Sb., 2009, no. 8, pp. 248–252.

  3. Avtsyn, A.P., Zhavoronkov, A.A., Rish, M.A., and Strochkova, A.S., Mikroelementozy cheloveka: etiologiya, klassifikatsiya, organopatologiya (Human Microelementoses: Etiology, Classification, and Organopathology), Moscow: Meditsina, 1991.

  4. Blagoveschenskii, Yu.N., Tainy korrelyatsionnykh svyazei v statistike (Secrets of Correlations in Statistics), Moscow: Nauchnaya kniga, 2009.

  5. Draper, N. and Smith, H., Applied Regression Analysis, New York: Wiley, 1981; Moscow: Finansy i statistika, 1986.

  6. Ekonometrika. Metodicheskie ukazaniya po izucheniyu distsipliny i vypolneniyu kontrol’noy i auditornoy raboty na PEVM (Econometrics. Methodical Instructions for Learning and Test Works on the PC), Moscow: Vuzovskiy uchebnik, 2005.

  7. Evdokimova, T.I., Pochvennaya s”yemka (Soil Survey), Moscow: MGU, 1987.

    Google Scholar 

  8. Gopp, N.V., Algorithmic approach to compiling digital soil maps from laboratory–field and satellite data, Issled. Zemli Kosmosa, 2013, no. 3, pp. 58–72.

  9. Gopp, N.V., Soils of the southwestern part of the Dzhulukul depression in the Altai Republic, Eurasian Soil Sci., 2015, vol. 48, no. 6, pp. 567–577.

    Article  Google Scholar 

  10. Huete, A.R. and Liu, H.Q., An error and sensitivity analysis of the atmospheric- and soil-correcting variants of the NDVI for the MODIS-EOS, IEEE Trans. Geosci. Remote Sens., 1994, no. 32, pp. 897–905.

  11. Ivanov, V.V., Ekologicheskaya geokhimiya elementov (Ecological Geochemistry of Elements), vol. 1: s-elements (s-Elements), Moscow: Nedra, 1994.

  12. Kabata-Pendias, A. and Pendias, H., Trace Elements in Soils and Plants, London: CRC,; Moscow: Mir, 1989.

  13. Kedrinskii, I.A. and Yakovlev, V.G., Li-ionnye akkumulyatory [Li-Ion Batteries), Krasnoyarsk: Platina, 2002. Khimicheskii entsiklopedicheskii slovar’ (Encyclopedic Dictionary of Chemistry), Knunyants, I.L., Ed., Moscow: Sov. entsiklopediya, 1983.

  14. Klassifikatsiya i diagnostika pochv Rossii (Classification and Diagnostics of Soils in Russia), Smolensk: Oikumena, 2004.

  15. Kumar, P., Pandey, P.C., Singh, B.K., Katiyar, S., Mandal, V.P., Rani, M., Tomarf, V., and Patairiya, S., Estimation of accumulated soil organic carbon stock in tropical forest using geospatial strategy, Egypt. J. Remote Sens. Space Sci., 2016, vol. 19, pp. 109–123.

    Google Scholar 

  16. Mashkovskiy, M.D., Lekarstvennye sredstva (Medicines), Moscow: Novaya volna, 2005.

  17. McKenzie, N.J. and Ryan, P.J., Spatial prediction of soil properties using environmental correlation, Geoderma, 1999, vol. 89, pp. 67–94.

    Article  Google Scholar 

  18. Michael, A., Anderson, Paul, M., Bertsch, P., et al., Exchange and apparent fixation of lithium in selected soils and clay minerals, Soil Sci., 1989, vol. 148, no. 1, pp. 46–51.

    Article  Google Scholar 

  19. Orlov, A.D., Eroziya i erozionnoopasnye zemli Zapadnoi Sibiri (Erosion and Erosion-Hazardous Lands of Western Siberia), Novosibirsk: Nauka, 1983.

  20. Perel’man, A.I. and Kasimov, N.S., Geokhimiya landshafta (Geochemistry of the Landscape), Moscow: Astreya-2000, 1999.

  21. Polevoi opredelitel’ pochv Rossii (Field Identifier of Soils in Russia), Moscow: Pochv. inst. im. V. V. Dokuchayeva, 2008.

  22. Poluektov, N.S., Meshkova, S.B., and Poluektova, E.N., Analiticheskaya khimiya litiya (Analytical Chemistry of Lithium), Moscow: Nauka, 1975.

  23. Rivero, R.G., Grunwald, S., Newman, S., Osborne, T.Z., and Reddy, K.R., Incorporation of ASTER satellite imagery into multivariate geostatistical models to predict soil phosphorus, in Biannual Meeting of Commission 1.5 Pedometrics Division 1 Int. Union of Soil Sci., Naples, Florida, USA: IUSS, 2005, pp. 75–76.

    Google Scholar 

  24. Rouse, J.W., Haas, R.H., Schell, J.A., and Deering, D.W., Monitoring vegetation systems in the Great Plains with ERTS, in Third ERTS Symposium NASA SP-351, 1993, pp. 309–317.

  25. Rusanov, A.K., Osnovy kolichestvennogo spektral’nogo analiza rud i mineralov (Fundamentals of Quantitative Spectral Analysis of Ores and Minerals), Moscow: Nedra, 1978.

  26. Zvonkova, T.V., Prikladnaya geomorfologiya (Applied geomorphology), Moscow: Vysshaya Shkola, 1970.

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Authors and Affiliations

  1. Institute of Soil Science and Agrochemistry, Siberian Branch, Russian Academy of Sciences, Novosibirsk, Russia

    N. V. Gopp, O. A. Savenkov, T. V. Nechaeva & N. V. Smirnova

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  1. N. V. Gopp
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  2. O. A. Savenkov
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  3. T. V. Nechaeva
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  4. N. V. Smirnova
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Correspondence to N. V. Gopp.

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Translated by I. Bel’chenko

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Gopp, N.V., Savenkov, O.A., Nechaeva, T.V. et al. The Use of NDVI in Digital Mapping of the Content of Available Lithium in the Arable Horizon of Soils in Southwestern Siberia. Izv. Atmos. Ocean. Phys. 54, 1152–1157 (2018). https://doi.org/10.1134/S0001433818090165

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