Assessment of the Transformation of Forests in the Southern Urals Based on Multi-Temporal Satellite Images. С. 51-62

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630:528.88(470.57)

DOI:

10.37482/0536-1036-2025-2-51-62

Abstract

The transformation of forests in the Southern Urals over a 25-year period has been studied using geoinformation systems and remote sensing methods. The Normalized Difference Vegetation Index (NDVI) has been determined, which reflects the influence of such factors as chlorophyll content, leaf surface area, vegetation density and structure. The index has been calculated based on the interpretation of multi-temporal satellite images (1995, 2013 and 2020) from the Pleiades-1A, Landsat-5 and -8 satellites using the ArcGIS software package to create a vegetation map reflecting NDVI values and a retrospective analysis of the condition of forest vegetation. The values found have a close correlation with the vitality indicators obtained by the field method (the correlation coefficient is 0.69). The calculation of the NDVI index, the generation of maps of the range of fixed NDVI values and the combination of “artificial colours” channels by year has made it possible to identify forest areas with optimal density, age and sanitary condition (dark colour) and areas in need of reforestation. A comparison of the distribution of territory by NDVI classes for 1995–2020 indicates a significant change in the area of individual classes, which are grouped into 11 classes and are represented by values from –0.14 to +0.91. By 2020, the superior part of the study area has begun to belong to higher NDVI classes – 9 and 10, and has amounted to 98 %, which indicates the age uniformity of plantations and an increase in forest productivity since 1995. Plantations with higher NDVI indices are characterized by an increased accumulation of woody biomass compared to other forest stands. The territories of classes 1–9 (NDVI 0–0.8) demonstrate a significant reduction in area and similar dynamics, while the territories of grades 10–11 (NDVI 0.8–1.0) demonstrate noticeable positive dynamics. The results of the study confirm the correctness of choosing the NDVI index from the known vegetation indices for assessing the transformation of the underlying surface types of the study area over 25 years. Thus, this index is an objective indicator of the assessment of the condition of forest ecosystems. Spatial image interpretation methods can be used to determine the area of forested lands and significantly improve the efficiency of forest resource management.

Authors

Rida R. Sultanova, Doctor of Agriculture, Prof.; ResearcherID: G-1513-2018, ORCID: https://orcid.org/0000-0002-0415-7342
Regina R. Baiturina*, Candidate of Biology, Assoc. Prof.; ResearcherID: G-4845-2018, ORCID: https://orcid.org/0000-0002-8156-2165
Svetlana V. Diarova, Assistant; ORCID: https://orcid.org/0009-0005-5403-1683

Affiliation

Bashkir State Agrarian University, ul. 50-letiya Oktyabrya, 34, Ufa, 450001, Russian Federation; vestnik-bsau@mail.ru, aspirant_bsau@mail.ru*, 999di@mail.ru

Keywords

forest condition, forest condition change, remote sensing, geographic information system, vegetation index, underlying surface type, mapping, the Southern Urals

For citation

Sultanova R.R., Baiturina R.R., Diarova S.V. Assessment of the Transformation of Forests in the Southern Urals Based on Multi-Temporal Satellite Images. Lesnoy Zhurnal = Russian Forestry Journal, 2025, no. 2, pp. 51–62. (In Russ.). https://doi.org/10.37482/0536-1036-2025-2-51-62

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