Real-time River Ice Prediction through Integrated Remote Sensing, and Monitoring

River ice holds significant importance across various disciplines, intertwining with engineering, ecology, sociology, and the lifestyles of nomadic peoples in profound ways. In engineering, river ice influences the design and management of infrastructures such as dams and bridges, necessitating solutions to mitigate the risks of ice jams and floods. Ecologically, the formation and melting of river ice are vital for aquatic ecosystems, affecting water temperature, oxygen levels, and the seasonal rhythms of flora and fauna, contributing to the ecosystem's biodiversity. In addition, river ice impacts community dynamics, influencing settlement patterns, transportation, and economic activities such as ice fishing, which are central to cultural traditions and social identity in cold regions. Real-time monitoring and prediction of river ice conditions are crucial for managing water resources, ensuring public safety, and maintaining ecosystems, especially in cold climate regions. The advent of advanced technologies has paved the way for innovative approaches to environmental monitoring, combining the strengths of remote sensing, in-situ observations, and data analytics to offer unprecedented insights into natural phenomena.

This PhD position focuses on the project “Real-time River Ice Prediction through Integrated Remote Sensing and Monitoring,” aiming to develop a comprehensive system for accurate and timely river ice analysis. The project seeks to harness the potential of cutting-edge remote sensing technologies and sophisticated monitoring techniques to capture dynamic changes in river ice conditions. By integrating diverse data sources and applying advanced analytical models, this research will contribute to the advancement of predictive capabilities, supporting effective water management practices and mitigating risks associated with river ice phenomena. The selected candidate will engage in a multidisciplinary research environment, collaborating with experts in hydrology, environmental science, computer science, and engineering. This position offers a unique opportunity to contribute to a critical area of environmental research, with significant implications for climate adaptation strategies, disaster preparedness, and sustainable development.

The ideal candidate for this PhD project will possess a comprehensive academic background in fields such as environmental science, hydrology, remote sensing, or computer science, with a particular interest in the dynamics of river ice in cold regions. Essential qualifications include advanced programming skills in languages like Python, R, or MATLAB, crucial for data analysis and environmental modeling. Additionally, extensive experience with Geographic Information Systems (GIS) and familiarity with Google Earth Engine are required for the processing and analysis of large-scale geospatial datasets. Candidates should also demonstrate proficiency in using remote sensing software and machine learning algorithms to interpret complex environmental data. Exceptional communication and collaboration skills are vital as the project demands active participation in interdisciplinary research efforts, aiming to innovate and push the boundaries of scientific understanding in environmental monitoring.

FGI and FMI

Water energy and environmental engineering research unit, University of Oulu

Ali Torabi Haghighi

Kari Luojus

Harri Kaartinen

Harri Kaartinen , FGI and Kari Luojus FMI