Aquorbitals

Description

Problem

Climate change has been affecting all of our lives. Extreme weather events are becoming more frequent. E.g. Vienna flooding 2024, Tyrol flash floods 2023, 2024, 2025. Glaciers and snow in the Alpine region are melting due to climate change. Rivers change their course over time. That means that in the future, more regions will become prone to climate-change-induced landslides and flooding. Timely prediction of landslides and floods allows for evacuation and saves lives and property. 

Current solutions

However, current prediction models allow for only short-term emergency prediction and last-minute evacuation. 

Our solution

We propose developing a tool for long-term prediction of landslide and flooding-prone areas, using time-series satellite data. Our model will allow predictions as far as 50+ years in the future. 

Demo: https://drive.google.com/file/d/1_0AqQSqZdS4tZQSwe3V2HqiQPmzNXSRY/view

Git repository https://github.com/ylruiz/11th_cassini_hackathon

Impact

Timely prediction of the future river course and water-affected areas will prevent the need for last-minute evacuations and possible loss of life and property. Development in the areas for which the future water-induced risk is assessed can be prevented. Our prediction model will allow local and national authorities enough time to implement non-environmentally invasive and sustainable water management policies. For example, the beaver population could be introduced to the areas where the river rerouting is deemed necessary. That way, human labour and construction could be avoided, further contributing to conservation and reducing the need for human labour and financial resources.

Target audience

Local and national authorities, insurance companies, general public.

EU Space Technologies used

Copernicus Sentinel Dataset

Challenge addressed

Disaster-risk prediction

Our Team

We are a multidisciplinary team combining deep scientific expertise, industry experience, and strong engineering capabilities. With multiple PhDs across physics and life sciences, as well as experience in startups and enterprise IT, we bring both theoretical rigor and practical execution to predictive analytics challenges. Our strength lies in rapidly translating complex data into actionable models and deployable solutions.

Team structure: 

Project Management & Coordination: Alexandra Vayle

Software development: Volker Karle, JoHanna Russ, Yunet Luis Ruiz, Raimel Alberto Medina Ramos

Data Analysis: Florian Kluibenschedl, Andrea Mrnjavac

Team qualifications: 

Volker Karle -  Data Scientist (PhD, Quantum Theory) Background in theoretical physics with deep expertise in statistics, predictive modeling, and quantitative methods. Focused on solving complex, high-dimensional problems using rigorous analytical approaches. 

JoHanna Russ -  Software development, Project development, Data mining; Combines hands-on software development with structured project management, enabling rapid prototyping and efficient execution. 

Alexandra Vayle -  Project Lead & Senior Consultant Senior IT consultant with extensive experience leading critical projects in the financial services sector, ensuring reliable delivery and stakeholder alignment. 

Yunet Luis Ruiz - Software engineer, Project management, Front-end developer 

Raimel Alberto Medina Ramos - Startup Founder & Full-Stack Developer (PhD, Quantum Theory) Founder with entrepreneurial experience, bringing both technical depth and product-oriented thinking. Focused on building scalable solutions and robust data pipelines. 

Florian Kluibenschedl - Data Analyst (PhD Candidate) Combines academic research with practical data analysis, specializing in data exploration, preprocessing, and extracting actionable insights. 

Andrea Mrnjavac -  Data Analyst & Life Scientist (PhD, Evolutionary Biology) Brings a strong scientific and analytical perspective, with expertise in experimental design, complex data interpretation, and interdisciplinary problem-solving, alongside project coordination skills.