ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa


Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2021, Vol. 18, No. 1, pp. 138-148

Assessment the spatial-temporal changes in green phytomass of agricultural vegetation using spectral response

E.A. Terekhin 1 
1 Belgorod State National Research University, Belgorod, Russia
Accepted: 19.01.2021
DOI: 10.21046/2070-7401-2021-18-1-138-148
Assessment the relationships between fractional green vegetation cover and NDVI vegetation index values for main species of agricultural vegetation in the south of the Central Russian Uplands was carried out (winter wheat, sunflower, soybeans, perennial grasses). The study was carried out using actual data on green vegetation fraction of agroecosystems in the Belgorod Region. The relationship between fractional green vegetation cover and vegetation index can be described by a logistic curve for all studied crops. The calculated equations characterize the main differences in the dynamics of green phytomass between types of agricultural vegetation. A spatio-temporal assessment of the winter wheat green vegetation fraction in the Belgorod Region was carried out using the calculated equations. A series of schematic maps has been prepared that characterize the territorial change in the winter wheat green vegetation fraction during the growing season, from early April to mid-July. Differences in the seasonal dynamics of crop green vegetation fraction growing in different climatic conditions were identified: the typical and southern forest-steppe. They are observed during the ripening period of winter wheat. During the period of maximum values of the green vegetation fraction, no significant territorial differences were found within the region.
Keywords: fractional green vegetation cover, agroecosystems, spectral response, spatial analysis, NDVI, MODIS, Central Russian Upland
Full text


  1. Buryak Zh. A., Terekhin E. A., Geoinformatsionnoe modelirovanie prostranstvenno-vremennoi izmenchivosti agroklimaticheskikh uslovii (Geoinformation modeling of spatio-temporal variability of agroclimatic conditions), Regional’nye geosistemy, 2020, Vol. 44, No. 3, pp. 333–342.
  2. Lebedeva M. G., Solov’ev A. B., Tolstopyatova O. S., Agroklimaticheskoe raionirovanie Belgorodskoi oblasti v usloviyakh menyayushchegosya klimata (Agroclimatic zoning of the Belgorod Region in a changing climate), Nauchnye vedomosti Belgorodskogo gosudarstvennogo universiteta, Ser.: Estestvennye nauki, 2015, No. 9(206), Vyp. 31, pp. 160–167.
  3. Miklashevich T. S., Bartalev S. A., Plotnikov D. E., Interpolyatsionnyi algoritm vosstanovleniya dlinnykh vremennykh ryadov dannykh sputnikovykh nablyudenii rastitel’nogo pokrova (Interpolation algorithm for the recovery of long satellite data time series of vegetation cover observation), Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2019, Vol. 16, No. 6, pp. 143–154.
  4. Terekhin E. A., Otsenka sezonnykh znachenii vegetatsionnogo indeksa (NDVI) dlya detektirovaniya i analiza sostoyaniya posevov sel’skokhozyaistvennykh kul’tur (Assess the seasonal NDVI values for detection and analysis of agricultural crops), Issledovanie Zemli iz kosmosa, 2015, No. 1, pp. 23–31.
  5. Shinkarenko S. S., Bartalev S. A., Sezonnaya dinamika NDVI pastbishchnykh landshaftov Severnogo Prikaspiya po dannym MODIS (NDVI seasonal dynamics of the North Caspian pasture landscapes from MODIS data), Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2020, Vol. 17, No. 4, pp. 179–194.
  6. Brown L. A., Dash J., Ogutu B. O., Richardson A. D., On the relationship between continuous measures of canopy greenness derived using near-surface remote sensing and satellite-derived vegetation products, Agricultural and Forest Meteorology, 2017, Vol. 247, pp. 280–292.
  7. Camacho-De Coca F., García-Haro F. J., Gilabert M. A., Meliá J., Vegetation cover seasonal changes assessment from TM imagery in a semi-arid landscape, Intern. J. Remote Sensing, 2004, Vol. 25, No. 17, pp. 3451–3476.
  8. Didan K., MOD13Q1 — MODIS/Terra Vegetation Indices 16-Day L3 Global 250m SIN Grid, 2015, V006, NASA EOSDIS Land Processes DAAC, available at:
  9. Gao L., Wang X., Johnson B. A., Tian Q., Wang Y., Verrelst J., Mu X., Gu X., Remote sensing algorithms for estimation of fractional vegetation cover using pure vegetation index values: A review, ISPRS J. Photogrammetry and Remote Sensing, 2020, Vol. 159, pp. 364–377.
  10. Glenn E. P., Huete A. R., Nagler P. L., Nelson S. G., Relationship Between Remotely-sensed Vegetation Indices, Canopy Attributes and Plant Physiological Processes: What Vegetation Indices Can and Cannot Tell Us About the Landscape, Sensors, 2008, Vol. 8, pp. 2136–2160.
  11. Imukova K., Ingwersen J., Streck T., Determining the spatial and temporal dynamics of the green vegetation fraction of croplands using high-resolution RapidEye satellite images, Agricultural and Forest Meteorology, 2015, Vol. 206, No. Suppl. C, pp. 113–123.
  12. Jia K., Liang S., Liu S., Li Y., Xiao Z., Yao Y., Jiang B., Zhao X., Wang X., Xu S., Cui J., Global Land Surface Fractional Vegetation Cover Estimation Using General Regression Neural Networks from MODIS Surface Reflectance, IEEE Trans. Geoscience and Remote Sensing, 2015, Vol. 53, pp. 4787–4796.
  13. Johnson B., Tateishi R., Kobayashi T., Remote Sensing of Fractional Green Vegetation Cover Using Spatially-Interpolated Endmembers, Remote Sensing, 2012, Vol. 4, No. 9, pp. 2619–2634.
  14. Justice C. O., Townshend J. R. G., Vermote E. F., Masuoka E., Wolfe R. E., Saleous N., Roy D. P., Morisette J. T., An overview of MODIS Land data processing and product status, Remote Sensing of Environment, 2002, Vol. 83, pp. 3–15.
  15. Kallel A., Le Hégarat-Mascle S., Ottlé C., Hubert-Moy L., Determination of vegetation cover fraction by inversion of a four-parameter model based on isoline parametrization, Remote Sensing of Environment, 2007, Vol. 111, pp. 553–566.
  16. Shabanov N., Gastellu-Etchegorry J.-P., The stochastic Beer – Lambert – Bouguer law for discontinuous vegetation canopies, J. Quantitative Spectroscopy and Radiative Transfer, 2018, Vol. 214, pp. 18–32.