Optional UNIGIS Modules

Themen der angewandten Geoinformatik I+II

Applied Topics in Geoinformatics 1+2

Optional Module: Automated Data Processing with R

There are plenty of reasons to learn programming with R. R is among the most popular analytical scripting languages with diverse applications such as statistical analysis, geographic information analysis, machine learning and data visualization. R is free and open source, does have more comprehensive functionality than most proprietary solutions, is compatible with most popular operating systems and benefits from a large community. Upon the completion of this module, you will have the fundamental skills to make use of the wide R ecosystem.

Optional Module: LiDAR in theory and application

The aim of this module is to deepen the understanding of Laser Remote Sensing techniques. The module provides an overview of today’s common sensors used for the Light Detection And Ranging (LiDAR) Remote Sensing along with the practical use case scenarios revolving around use of Point Cloud data and its handling for feature extraction.

Optionales Modul: Geoprozessierung mit Python

Dieses Modul soll eine Einführung zur Erstellung von kleinen Programmen (Tools oder Scripts) zur Geoprozessierung mit der open-source Scriptsprache Python in ArcGIS Pro geben.

Optional Module: Spatial Simulation

Everything is related to everything else… This core principle of spatial analysis is equally true for the temporal domain: history matters! Together, the two dimensions of space and time build the spatio-temporal context of our environment. Whereas GIS has focussed primarily on the spatial perspective, there is a clear trend towards the incorporation of time. Dynamic models on the other side have for a long time ignored space. Only since a few decades a new theory of “complex systems” explicitly includes spatial heterogeneity. Therefore, spatial simulation models are fundamentally new tools to study systems from a truly spatio-temporal perspective.

Optional Module: Remote Sensing

This Remote Sensing module follows a multi step education, the typical workflow of remote sensing process: recording, processing, analyzing, and applying. The introduction gives a fundamental background about the theory of spectral data origin and its digital acquisition first. Operational sensors and platforms available for data acquisition will be described as well. Remotely sensed data processing means the elimination of system errors and the georeferencing of the image data. A very important part in the process is the data analysis, that is generating information from raw remote sensing data, such as extracting real world objects or mapping land use land coverage. Therefore, in principle two different methods are available: a statistical pixel-per-pixel approach and the more sophisticated object-based image analysis.

Optional Module: Environmental Monitoring

Knowledge about the state and trend of environmental systems is crucial for our livelihood. Environmental monitoring exactly provides this fundamental data and information. The goal of this module is to introduce you to the key concepts, elements and methodological approaches of environmental monitoring that enable you to formulate an environmental monitoring system and perform selected GIS-related monitoring tasks.

Optional Module: Developing Web-Applications with JS and Leaflet

Upon completion of this module, you know the structure of JavaScript code to write simple scripts from scratch, can apply the model-view-controller principle to design more complex scripts, can make use of frameworks and libraries to reuse existing code,develop a web-based application that acquires, processes and visualises spatial data, use web-browsers for debugging your code.

Optional Module: Basics of Application Development

Upon completion of this module, you get the big picture of application development beyond coding by understanding system architectures, understand the role of client-side and server-side scripting languages versus compiled programming languages, made the first steps into structuring code according to the object-oriented programming paradigm.