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ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2026, V. 23, No. 3, pp. 223-238

A method for mapping the degradation degree of natural pastures based on long-term remote sensing data time series

S.S. Shinkarenko 1 , S.A. Bartalev 1 , V.A. Egorov 1 , S.A. Khvostikov 1 
1 Space Research Institute RAS, Moscow, Russia
Accepted: 24.03.2026
DOI: 10.21046/2070-7401-2026-23-3-223-238
The article proposes a method for large-scale mapping of the degradation degree of zonal vegetation in steppe and desert biomes. The method is based on calculating the deviation of the NDVI (Normalized Difference Vegetation Index) values, derived from the MODIS satellite system, from the zonal norm. To calculate this deviation, the 95th and 5th percentiles of the annual maximum NDVI values are determined for the vicinity of each pixel over the entire observation period, which exceeds 20 years. A key feature of this approach is the use of the IKI RAS (Space Research Institute of the Russian Academy of Sciences) terrestrial ecosystem map, which delineates zonal steppe and desert vegetation from intrazonal meadows. This allows for the deviation from the norm to be calculated separately for zonal and intrazonal forage lands. The deviation from the norm is calculated as the ratio of the difference between the current annual maximum NDVI value and the 5th percentile in the vicinity to the difference between the 95th and 5th percentiles, expressed as a percentage. The calculation of a linearly weighted moving average with a five-year averaging window smoothens the time series and eliminates the possibility of transitions from extreme degradation states. Using the degradation criteria based on the deviation of projective cover from the zonal norm, according to the Russian State Standard GOST R 70526-200 “Land Reclamation. Soils. Assessment of Degradation Degree”, the degradation degrees were calculated for the zonal vegetation of the country’s plain steppe and desert biomes. A comparison of the obtained estimates with the long-term dynamics of NDVI, the proportion of open sands and other vegetation-free areas in MODIS pixels with varying degrees of degradation, using the Caspian desert-steppe biome as an example, demonstrated the adequacy of the proposed method. As of 2024, a total of 13.6 million hectares of zonal vegetation in the country’s steppe and desert biomes were classified as being in a severe degradation state, and 0.44 million hectares in a very severe state, which collectively accounted for about 30 % of all steppe and desert vegetation. Further development of the method may involve transition from NDVI to indicators of projective cover and phytomass as the necessary set of reference data becomes available.
Keywords: steppes, deserts, desertification, land cover, satellite monitoring, remote sensing
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