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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. 5, pp. 324-337

Mapping bare soils in Minsk Region using Sentinel-2 spectral indices

B. Zhao 1 
1 Belarusian State University, Minsk, Belarus
Accepted: 30.07.2026
DOI: 10.21046/2070-7401-2026-23-5-324-337
Bare soil is an important target in agricultural remote sensing, but its identification is complicated by spectral similarity to dry vegetation, crop residues, and bright anthropogenic surfaces. For Belarus, Sentinel-2-based approaches to bare-soil mapping remain insufficiently studied. This study aims to develop and test a threshold-based method for mapping open soil surfaces in Minsk Region using the Bare Soil Index (BSI), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Built-up Index (NDBI). Sentinel-2 Level-2A imagery for 2024 was processed in Google Earth Engine (GEE) with clouds, shadows, snow, and invalid observations masked using the Scene Classification Layer (SCL); 27 threshold combinations were evaluated. The operational rule was defined as BSI > 0.18, NDVI < 0.20, and NDBI < 0.20. Validation using 1000 control points per quarter for Q2–Q4 yielded overall accuracies of 88.8–89.6 %, F1-scores of 87.7–88.6 %, and kappa values of 0.775–0.792. Random Forest models RF_index (using only BSI, NDVI, and NDBI) and RF_full (using Sentinel-2 spectral bands and indices) increased overall accuracy to 90.4–92.0 and 91.9–93.2 %, respectively. Most detected open surfaces were associated with arable-suitable land, but their within-class share did not exceed 1.0–1.6 %. The proposed approach is suitable for regional mapping of seasonally exposed soil surfaces provided that thresholds are locally calibrated, seasonal robustness is checked and accuracy is evaluated using control points.
Keywords: Sentinel-2; bare soil; remote sensing; Bare Soil Index; NDVI; NDBI; threshold classification; Random Forest; agricultural landscapes; Minsk Region
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