ORCID ID: 0000-0003-4986-5470
Research Project Title: Development of a methodology of mapping seaweed in the intertidal zone of the coastline of Ireland by combination of hyperspectral, satellite and multispectral imagery
Supervisors/s: Dr Dean Callaghan, Dr Leon Cavanagh, Dr Owen Naughton
Project Funding: IRC Government of Ireland PhD Scholarship
- Research Project Description
- Publications and Outputs
As a postgraduate student at SETU, I research intertidal seaweed habitats using drones and multispectral sensors to map their distribution. My research setup varies between an office with a computer and the scenic rocky shoreline and turbulent sea. Having graduated with bachelor’s and master’s degrees in Physics from Kazan Federal University, I bring a multidisciplinary perspective to my research.
I am particularly drawn to the practical aspects of my research. Accurate seaweed distribution maps have crucial applications for policy makers, industry practitioners, and seaweed harvesters. Earth observation fascinates me as a tool to gather information about diverse habitats that traditional surveys cannot provide. It offers a means to balance biodiversity conservation and development of coastal economies.
Research Project Description
Seaweed represents a valuable asset for various industries, from agriculture to pharmaceuticals. Mapping of macroalgal communities is important to gain information about the availability of biomass and effective and sustainable management of aquatic resources. Effective inter-species discrimination is important to help identify the presence of the most valuable species, assist environmental monitoring of endangered species as well as act as a preventive measure against propagation of harmful algal blooms. Multi- and hyperspectral satellite sensors can monitor ecosystems on a large scale, however, the spatial resolution may not always meet the requirements of environmental monitoring. Furthermore, long revisit times of satellites and dependence on weather conditions can limit the applicability of such sensors for continuous observations. These limitations can be overcome by the use of unmanned aerial vehicles (UAVs) and drone sensors, whose rapid development in recent years has enabled more in-depth analysis of ecosystems using high-resolution data. The research aims to develop a methodology of mapping seaweed communities in the intertidal zone by using drones and multispectral sensors in combination with satellite imagery to establish an effective and accurate way of detecting and mapping of intertidal habitats.
Publications and Outputs
- Richard Fitzgerald Memorial Prize Best Aquatic Environment Poster: Akhmetshin, D. et al. (2022), Unmanned aerial vehicles for mapping seaweed: RGB and multispectral sensors, Environ 2022: ‘Unlocking Sustainability’, Ulster University, Belfast 20-22 June 2022.
Cutting-edge technology using drones and cameras can help protect the environment. A study compared different sensors on a drone to map seaweed on the Irish coastline. While standard cameras were good for basic identification, more advanced multispectral sensors provided better accuracy in identifying different seaweed species. Combining both types of sensors improved classification accuracy and the ability to detect seaweed in deeper waters. This technology can be a valuable tool for large-scale environmental monitoring and conservation efforts.