Unverified paper record
Research on the Possibilities of Determining the Structural Characteristics of Plant Communities Dominated by Reeds Using High-Resolution Satellite Imagery, Ground Measurements, and Unmanned Aerial Vehicles
Cosmic Research · 1 Dec 2025 · 10.1134/s001095252560218x
Abstract
Abstract— Plant communities dominated by reeds (Phragmites altissimus (Benth.) Mabille, Phragmites australis (Cav.) Trin. ex Steud.) are widely distributed in floodplain and delta landscapes. Despite their significant biospheric role and potential for industrial use, insufficient attention has been paid to the mapping and assessment of these communities in Russia. The objective of this study is to explore the possibilities of mapping biomass and vegetation height in reed-dominated communities in the Volga Delta using Sentinel-1/2 satellite data supported by ground measurements and aerial surveys conducted with a drone. Allometric relationships between the heights, stem diameters of reeds, and biomass were established for 92 sample plots within the Astrakhan Nature Reserve in the Volga Delta enabling the use of aerial imagery to obtain reference data through photogrammetric methods. The application of vegetation height calculated photogrammetrically based on aerial imagery across 27 test polygons combined with temporally distinct satellite data and the Random Forest nonparametric regression method yielded a high accuracy in mapping heights (coefficient of determination R2 = 0.80, root mean square error (RMSE) 0.46 m) and biomass (R2 = 0.65, RMSE = 12.6 t/ha) of reed-dominated communities in the Volga Delta. Thus, the approach employed proves to be effective for mapping the biomass of reed communities in the Volga Delta and similar landscapes.
Plant phenotyping relevance
ヨシ群落の高さ・バイオマスという植物形質を、衛星画像、ドローン空撮、写真測量、回帰モデルで推定・検証する方法が研究の中心である。
abstractThe objective of this study is to explore the possibilities of mapping biomass and vegetation height in reed-dominated communities in the Volga Delta using Sentinel-1/2 satellite data supported by ground measurements and aerial surveys conducted with a drone.
abstractThe application of vegetation height calculated photogrammetrically based on aerial imagery across 27 test polygons combined with temporally distinct satellite data and the Random Forest nonparametric regression method yielded a high accuracy in mapping heights
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