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103-0251-00L 4 Credits MSC D-BAUG

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Computational Methods for Geospatial Analysis

Lecturers & Examiners: Prof. Dr. Konrad Schindler, Dr. Jemil Avers Butt, Prof. Dr. Benedikt Soja, Olivier Dietrich, Dr. Nina Wiedemann

VVZ CR n/a

Last Updated: 2026-02-05 16:30:03

Abstract

Introduction to mathematical and statistical tools for geospatial data analysis.

Objective

The goal is to familiarise students with the principles and tools of geospatial data analysis, and to enable them to apply those tools to practical tasks.

Content

The course introduces basic methods of geostatistics and geospatial data analysis. Topics include spatial correlation, auto-correlation and the variogram; surface interpolation (kernel-based, kriging, parametric surface models); spatially adaptive filtering (bilinear, guided filter); spatial stochastic processes and random fields; time series models and spatio-temporal analysis.

General Information

Language: English
Levels: MSC
Frequency: Yearly recurring

Examination

Type: session examination
Mode: written 90 minutes
Aids: None

The grade is determined by (i) the written exam (70%) and (ii) continuous performance assessment during the semester assignments through programming assignments (30%).

Course Components