Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2026, V. 23, No. 5, pp. 312-323
Application of spectral vegetation indices (NDVI, NDMI and CI) from Sentinel 2 data in monitoring abandoned lands of different ages in specially protected natural areas
E.M. Iliushkova 1 , M.V. Tikhonova 1 1 Russian State Agrarian University — Moscow Timiryazev Agricultural Academy, Moscow, Russia
Accepted: 30.07.2026
DOI: 10.21046/2070-7401-2026-23-5-312-323
The assessment of the spatiotemporal dynamics of vegetation across five fallow plots in the Central Forest Reserve is based on an analysis of time series derived from Sentinel-2 satellite imagery for 2020–2024. Vegetation condition was assessed using three indicators: NDVI (Normalized Difference Vegetation Index), NDMI (Normalized Difference Moisture Index) and CI (Chlorophyll Index). A comparison of long term averages using Student’s t-test reveals spectral similarity in the early stages of reforestation. Grassland fallow and young birch stands aged 20–70 years form a statistically homogeneous group with a chlorophyll concentration of 17.36–21.96 mg/g (p > 0.05). As expected, old-growth spruce stands are distinguished from these communities by a significantly lower pigment content (p < 0.001), reflecting the specific characteristics of a closed, dark-coniferous stand. NDMI values approach their maximum as early as May, responding to the abundance of spring moisture in taiga ecosystems following snowmelt. The accumulation of green biomass takes longer, so the NDVI peak is shifted to June, after which the NDVI gradually decrease towards the beginning of autumn. A close correlation of NDMI with soil moisture and chlorophyll CI (R2 up to 0.75) confirms the sensitivity of this indicator. The use of the proposed combination of indicators ensures reliable differentiation of succession stages and the possibility of their quantitative assessment within the framework of long-term satellite monitoring of succession processes in the southern taiga subzone.
Keywords: Sentinel-2, Earth remote sensing, vegetation indices, NDVI, NDMI, CI, uneven-aged fallow land, forest ecosystems, Central Forest Nature Reserve
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