|Paper title||Earth observation data science programs in NTUU "KPI"|
|Form of presentation||Poster|
Nowadays, satellite monitoring and geospatial intelligence are the drivers of digital transformation and economic development all over the world. At the same time, in Ukraine there is no higher education programs dealing with Earth observation data science or machine and deep learning on remote sensing data. In 2019, Space Research Institute in cooperation with the Department of Mathematical Modeling and Data Analysis (MMDA department) of National Technical University of Ukraine “Kyiv Polytechnic Institute” (NTUU “KPI”) joined the Copernicus Academy network for deeper involvement into educational activities related to the Copernicus program. As Copernicus Academy laboratory, we contribute into international scientific and innovative international programs, provide trainings and master classes for students, regional administrations and teachers. Most of our projects deal with machine learning on satellite and auxiliary data and satellite monitoring applications and require deep knowledge of mathematics, machine learning and data analysis.
To facilitate involvement of students into our projects, in 2021 MMDA department established a certificate program “Models and methods of intellectual analysis of heterogeneous data” for master students of Applied Mathematics specialty (https://mmda.ipt.kpi.ua/en/certificate-program-models-and-methods-of-intellectual-analysis-of-heterogeneous-data/). It includes big geospatial data analysis, geospatial information technologies and deep learning for satellite and heterogeneous data. It allows students to dive into Earth observation domain and bridge the gap between applied mathematics and satellite monitoring. Students do their master’s research within international projects, in particular, Horizon-2020 e-shape or NASA project “High-Impact Hot Spots of Land Cover Land Use Change: Ukraine and Neighboring Countries”. They develop machine learning models for different applications based on Copernicus data and implement them on different cloud platforms, such as GEE, CREODIAS and AWS. Some of them develop their startup projects based on this research.
For further development of our program and better motivation of our students we are interested in collaboration with similar programs for academic mobility of students and professors and looking for innovative educational forms and resources.