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Unmanned Aerial Vehicle (UAV) – Mapping of In-Channel Aquatic Vegetation Under Contrasting Algal Conditions

Author(s): Emilia Karamuz; Monika B. Kalinowska; Filip Bojdecki

Linked Author(s): Monika Kalinowska

Keywords: No Keywords

Abstract: This study demonstrates a quantitative assessment of in-channel aquatic vegetation (filamentous algae and other macrophytes) in a small agricultural watercourse using Object-Based Image Analysis (OBIA) applied to low-altitude Red, Green, Blue (RGB) drone imagery. The approach is evaluated through a direct comparison of two strongly contrasting scenarios observed on consecutive days: a channel reach with dense algal and macrophyte coverage, and the same reach after mechanical removal of the algae on the following day, which represents a unique aspect of this study. The results confirm the OBIA detection accuracy and consistency across highly divergent vegetation conditions. The resulting high-resolution vegetation maps of coverage and spatial distribution may provide critical input for studies on vegetation-induced flow resistance, hydrodynamic alterations, longitudinal dispersion, and transport and mixing processes. By delivering high-resolution quantitative data on in-channel aquatic vegetation dynamics, this work provides crucial input for future research aimed at developing and implementing evidence-based, environmentally friendly channel maintenance strategies in lowland agricultural streams.

DOI:

Year: 2026

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