Call is closed!
The University of Jena, within the European alliance EC2U - European Campus of City-UniversitiesExterner Link, will host from 9 to 13 October 2023 the Autumn School "Geographic Data Science for Sustainability". The course is organized by Prof. Dr. Alexander Brenning and his GIScience GroupExterner Link within the Virtual Institute for Sustainable Cities and Communities.
The autumn school provides an overview of state-of-the-art machine-learning techniques for geospatial and environmental analysis and modelling. These methods promise to better account for nonlinearities, higher-order interactions, high dimensionality, and noisy data than ‘traditional’ statistical methods, offering improved predictive capabilities for decisio-making in environmental management for sustainability. Nevertheless, paticular challenges in the analysis of geospatial data relate to integrating process knowledge, interpreting black-box models, and accounting for spatial autocorrelation. Since operating these models requires statistical computing skills, the course also introduces the programming language R with its geospatial capabilities and machine-learning extensions, and students will apply the acquired skills using real-world geospatial data sets and hands-on exercises. Case studies considered in the course address physical as well as social aspects of sustainable development, such as landslide susceptibility, air pollution, and housing conditions.
Program: A draft program is available herepdf, 465 kb.
Learning formats: online preparation classes; on-site Lectures, Workshops, Lab classes.
Target Group: The event targets students of geographic information science, geography, earth and environmental sciences, engineering and related disciplines at the senior undergraduate level (last year of Bachelor), Master’s level, or Ph.D. level.
Staff are also welcome to apply.
- You need to be enrolled as student or PhD student, or be staff at an EC2U university in October 2023.
- Your Level of English needs to be at least B2.
More information on the CEFR levels here: https://europa.eu/europass/system/files/2020-05/CEFR%20self-assessment%20grid%20EN.pdfExterner LinkExternal linkExterner Link
- You need to have prior knowledge of basic statistical methods (e.g., multiple linear regression), GIS or geospatial data, and (ideally) basic programming skills (e.g., R or Python).
The Autmn School is generously supported by grants from EC2U mobilities. For detailed information contact your EC2U coordination office at your university.
Apply on the Event Webpage here en by 15 August 2023.
Contact: GIScience Group, firstname.lastname@example.org