https://studiegids.vu.nl/en/courses/2024-2025/AM_1197The objective of this course is to become familiar with more advanced approaches for the analysis of (large) spatial and temporal datasets in the context of earth and environmental sciences, for example related to (addressing) climate change.In this course you will acquire the necessary skills to conduct spatio-temporal analysis in the context of earth and environmental sciences. The course starts with the basics of programming in Python, and gradually focuses on tools that are useful for spatio-temporal analyses: reading and writing spatial and time-series data, libraries for handling spatial data and time series data, data analysis, and visualization of results. You will learn these skills using several practical cases, such as making climate stripes and optimization of an energy-grid using weather data.Each week will consist of one or two lectures and multiple computer labs (tutorials) where students can work on the assignments.The course requires 8 weeks of part-time (50%) study, and students are expected to spend approximately 20 hours a week on this course.Selected literature will be provided on Canvas.MSc students in Earth Sciences, MSc students in Hydrology, MSc students in Econometrics and Operations Research with specialization Climate Econometrics, and other relevant studies.It is advisable for students to have their own laptop for computer exercises. Lecturers: Dr. J.A. de Bruijn, and Dr. N. SchutgensThis course assumes a basic knowledge of GIS and GIS-based spatial analysis (such as the course GIS and Digital Spatial Data (AB_1076), or GIS en Aardobservatie AB_1271 or equivalent). This requirement is met by all students that completed their BSc in Earth Sciences, or Earth, Economics and Sustainability at VU University. MSc students in Econometrics and Operations are not expected to experience issues when they do not have this background. Prior experience with scripting or programming is not a requirement but will be helpful.Experience with GIS, spatial analysis, and programming/scripting is an asset.