Assessing algae accumulation in an artificial pond using UAV-based orthophoto

Abstract

Artificial ponds serve as critical resources for various human activities, including agriculture, aquaculture, and water management. However, unchecked algae growth in these man-made water bodies can lead to eutrophication, oxygen depletion, and ecological degradation. Monitoring and managing algae accumulation in artificial ponds are essential for environmental sustainability. Traditional assessment methods have limitations in terms of spatial and temporal resolution, making them unsuitable for real-time monitoring. Recent advancements in Unmanned Aerial Vehicles (UAVs) and remote sensing technology have opened new possibilities for environmental monitoring. This study explores the application of UAV-based orthophotos and band ratios for assessing algae accumulation in artificial ponds. Structure from Motion (SfM) photogrammetry is used to create high-resolution orthophotos, providing detailed spatial information. Band ratios, derived from spectral information in RGB images, are employed to detect algae presence. Results show that UAV-based photogrammetry generates detailed orthophotos with a ground sampling distance of 1 cm, allowing for the identification of fine-scale features in the pond. The red/green band ratio proves effective in consistently detecting algae presence. The study demonstrates the potential of UAV-based RGB band ratios for accurate algae assessment, enabling informed decision-making and timely interventions to preserve the ecological integrity of artificial ponds. This innovative approach provides a valuable tool for safeguarding water quality and contributing to the sustainability of essential aquatic ecosystems.