Optional UNIGIS Modules

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.

With the increasing integration of society and economy in the European Union, purely regional or national approaches often make no sense, and a wider view is required. The EuroGIS module provides a fundamental overview of issues of geoinformation in Europe. Key information on how Europe works and which organisations and institutions are relevant on the EU level is provided. European datasets and projects are analysed, and European initiatives such as Galileo and Copernicus are assessed. Practical work introduces into finding of and working with European datasets e.g. in the context of Copernicus.Important policy developments related to GI are explored, and strategies to make geodata available at the European level, such as INSPIRE, are addressed.

This module aims at giving students practice in establishing and maintaining an Enterprise GIS site. Enterprise GIS is an implementation of an organization wide GIS infrastructure including its processes and tools. ArcGIS Enterprise is the foundation software solution proposed by Esri to foster data integration and management, perform web based geospatial analysis and provide solutions for web mapping and communication.

The ArcGIS Enterprise deployment and configuration options will be introduced together with the supported custom and OpenGIS compliant web services capabilities, the available server-client communication protocols, cloud-computing paradigm and existing efforts dedicated to standards in GIS. The following geospatial web services will be discussed in details: map service, tile service, feature service, coverage service and geoprocessing services. A dedicated ArcGIS Enterprise instance will serve as example of enterprise cloud-computing applications.

Dieses Modul gibt eine grundlegende Orientierung über Positionierung und Einsatzbereiche von Geomarketing und Business-GIS. Im Kontext unternehmerischer Entscheidungsfindung spielen Geographische Informationssysteme bzw. räumliche Analysemethoden eine wichtige Rolle. Das Modul gliedert sich in zwei Schwerpunktbereiche. Zunächst werden die methodischen Grundlagen (Daten, Verortung, Geokodierung etc.) behandelt. Im zweiten Abschnitt werden dann aufbauend auf Praxisbeispielen gängige Methoden im Bereich Geomarketing und Business-GIS zur Durchführung von Standortanalyse, Filialnetzplanung, Gebietsanalyse, Mediaplanung etc. vorgestellt und angewendet.

Das Optionale Modul „Landschaftsanalyse mit GIS“ bietet einen GIS-basierten, methodischen Zugang zum Thema Landschaftsanalyse. Der Fokus liegt dabei auf der Quantifizierung, Analyse und Bewertung von Landschaft und deren Zerschneidung/Fragmentierung mit Hilfe von Landschaftsstrukturmaßen (landscape metrics) anhand von prxisnahen Beispielen.
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.
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.
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.
The goal of this module is to introduce the use of QGIS for typical GIS tasks, such as data visualization, editing, and analysis. Course participants will also learn to use Python (in particular the QGIS Python API PyQGIS) to automate GIS workflows. Concepts that lend themselves to automation are first introduced using the QGIS GUI before we go into detail of achieving the goal in Python. The module is structured as follows: