Sodalitas Bildungshaus, Propsteiweg 1, Tainach
Institut für Geographie und Regionalforschung
With the rapidly increasing availability of geospatial data, novel geocomputing techniques and powerful software tools, geographical research and professional practice are undergoing a transformation that comes with many new opportunities but also challenges. This talk highlights and discusses issues related to (1) novel types and sources of geospatial data, (2) reproducible and open science, and (3) the potentials and pitfalls of statistical and machine-learning techniques. Which new opportunities arise from the growing amount of geospatial data? What best practices should we follow to make our research open and reproducible? Should we give up model interpretability to improve the predictive performance of our models? Practical recommendations are given based on case studies related to Earth surface processes, and implications for training young geographers are considered.
Prof. Dr. Alexander Brenning
Natalie Schöttl (natalie [dot] schoettl [at] aau [dot] at)