Methodology for jellyfish research in the Black Sea using UAV

Jellyfish blooms in the Black Sea have become more frequent and intense in recent years, which has caused ecological and socio-economic concerns. Due to their delicate nature, traditional sampling techniques are often ineffective. In order to evaluate the spatial distribution and dynamics of Rhizostoma pulmo and Aurelia aurita in the Bulgarian coastal zone, this study uses UAV-based monitoring as a non-invasive method. A DJI Phantom 4 Pro UAV was applied to capture high-resolution aerial images with 75% overlap from a height of 20 to 30 meters. After generating the orthomosaics in Agisoft Metashape, they were analyzed both automatically in Image J and manually in Global Mapper. Flights were conducted throughout the seasons from August 2023 to January 2025. Densities of Aurelia aurita and Rhizostoma pulmo determined by automated and manual counts from drone images were similar. The automated program was able to exclude false detections of objects that weren't likely to be jellyfish by highlighting the medusae from the background. The findings demonstrate how UAVs can deliver accurate, timely, and cost-effective jellyfish monitoring data. Limitations such as patchy distributions, sun glare and water clarity are explored, along with suggestions for improving data quality and incorporating UAV-based monitoring into larger frameworks for marine research.

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Publication Details

Published
2025-09-19
DOI
https://doi.org/10.1117/12.3073302
Primary Topic
Marine Invertebrate Physiology and Ecology
Type
article
Field-Weighted Citation Impact
0.00

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article

Methodology for jellyfish research in the Black Sea using UAV

Kremena Stefanova, Valentin T. Panayotov, Violeta Slabakova, Trayana Kaludova et al.
Marine Invertebrate Physiology and Ecology
article

Methodology for jellyfish research in the Black Sea using UAV

Kremena Stefanova, Valentin T. Panayotov, Violeta Slabakova, Trayana Kaludova, Ivelin Petkov
article en

Abstract

Jellyfish blooms in the Black Sea have become more frequent and intense in recent years, which has caused ecological and socio-economic concerns. Due to their delicate nature, traditional sampling techniques are often ineffective. In order to evaluate the spatial distribution and dynamics of Rhizostoma pulmo and Aurelia aurita in the Bulgarian coastal zone, this study uses UAV-based monitoring as a non-invasive method. A DJI Phantom 4 Pro UAV was applied to capture high-resolution aerial images with 75% overlap from a height of 20 to 30 meters. After generating the orthomosaics in Agisoft Metashape, they were analyzed both automatically in Image J and manually in Global Mapper. Flights were conducted throughout the seasons from August 2023 to January 2025. Densities of Aurelia aurita and Rhizostoma pulmo determined by automated and manual counts from drone images were similar. The automated program was able to exclude false detections of objects that weren't likely to be jellyfish by highlighting the medusae from the background. The findings demonstrate how UAVs can deliver accurate, timely, and cost-effective jellyfish monitoring data. Limitations such as patchy distributions, sun glare and water clarity are explored, along with suggestions for improving data quality and incorporating UAV-based monitoring into larger frameworks for marine research.

Bulgarian Academy of Sciences (BG), Institute of Oceanology (BG)
Horizon 2020 Framework Programme
Openalex Percentile: Top 89%
Marine Invertebrate Physiology and Ecology
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