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JOURNALS // Computer Optics // Archive

Computer Optics, 2023 Volume 47, Issue 2, Pages 306–313 (Mi co1129)

This article is cited in 1 paper

IMAGE PROCESSING, PATTERN RECOGNITION

Spectral reflectance analysis of abandoned agricultural lands in the Central Russian forest-steppe using Sentinel-2 satellite data

E. A. Terekhin

National Research University "Belgorod State University"

Abstract: The article considers the spectral response of post-agrogenic landscapes in the forest-steppe zone based on Sentinel-2 data. The study was carried out on the territory of the Central Chernozem region. The type of forest that forms on abandoned agricultural land has a statistically significant effect on the spectral response in most Sentinel-2 bands. The reflectance of abandoned lands with deciduous and coniferous species is statistically significantly different in most bands. The reflec-tance of abandoned lands with mixed forests does not differ statistically significantly from other types of post-agrogenic landscapes. The reflectance of abandoned lands is inversely related to their forest cover in most Sentinel-2 bands. The strongest correlation with forest cover is typical for red (Band 4) and SWIR (Band 11, 12) ranges for all post-agrogenic landscape types. In the same bands, there are statistically significant differences between most of forest cover gradations of post-agrogenic landscapes. The established patterns make it possible to use the reflectance in the red (Band 4) and SWIR MSI bands (11, 12) to assess the forest cover of post-agrogenic landscapes.

Keywords: post-agrogenic landscapes, spectral responce, image processing, forest-steppe, Sentinel-2

Received: 21.05.2022
Accepted: 09.12.2022

DOI: 10.18287/2412-6179-CO-1160



© Steklov Math. Inst. of RAS, 2025