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Teaching information and download centre


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Teaching information and download centre

GIS and Remote Sensing in Geosciences


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BOKU 872.000 VU2 WS2016 2015 2014 2013 2012 2011 2010

Martin Mergili
Anna Iglseder (Teaching assistant)

Geographic Information Systems or Sciences (GIS) stand for computer software, digital data and computing methods designed to manage spatial information. Spatial information carries a spatial reference, usually bound to a projected or geographic coordinate system. This means that the location of a point or an image pixel does not just contain interior coordinates, but also exterior ones. Today, remotely sensed datasets like aerial or satellite imagery are an integral part of GIS. Most problems in applied geosciences are not restricted to one single point, but are spatially - and often also temporally - more complex. Lakes or glaciers may change in size, flow processes (lava flows, landslides, debris flows etc.) spread along a certain path. GIS in combination with Remote Sensing (RS) are valuable tools to analyze process behaviour, interactions between systems or spatio-temporal changes of systems.

This course shall give an introduction in how to efficiently use GIS and RS in various fields of Applied Geosciences. The course is focussed on the retrieval, preparation and analysis of remotely sensed datasets, with emphasis on optical and infrared satellite imagery as well as digital elevation models (DEMs). Some basic understanding of the principles of GIS and Remote Sensing is expected from the participants.

The course follows a concept of learning by doing. Specific real-world problems faced by Applied Geoscientists are taken as examples. The various aspects of GIS and RS are conveyed by introducing step-by-step solutions of those problems. The course is not coupled to one specific software package and is not thought to constitute a how-to-do manual. It rather introduces to general GIS-specific functions which can be performed by various packages. However, it also attempts to convey a feeling for which software performs best for which types of tasks. At the end of the course, the participants will be able to

  • decide which methods, data and software are useful for the solution of which type of problem;
  • know where to search for and how to prepare the data;
  • independently, efficiently and creatively perform standard and slightly advanced operations on DEMs and satellite imagery;
  • know about more advanced methods of RS.

The course builds on four comprehensive lessons with a wide range of topics and study areas. Two more lessons are dedicated to practice and to the final exam. Each lesson has a duration of four teaching units.

The course takes place in the GIS/RS laboratory EXNH-02/61 in the Wilhelm-Exner-Haus (Peter-Jordan-Strasse 82).

Further information on the course in BOKU Online

Information on GIS and RS software packages GIS and RS data formats Sources of GIS and RS data

Lesson
Date and time
Instructor(s)
Teaching method
Content
01
January 2018
Martin Mergili
Anna Iglseder
Guided training

Working with terrain data and satellite imagery 1

Medium-resolution (cell size: 10 - 100 m) satellite imagery and DEMs facilitate the visual interpretation of land surface features. But they also allow the derivation of quantitative information of landscape patterns and changes. In this lesson you will learn how to
  • find globally available medium-resolution datasets relevant for the Applied Geosciences
  • prepare these datasets for analysis
  • derive simple terrain characteristics from the DEMs
  • combine various channels of satellite images for visual interpretation and quantitative analysis

The training area for this lesson is Hawaii.

Download training data for Hawaii

02
January 2018
Martin Mergili
Anna Iglseder
Guided training

Working with terrain data and satellite imagery 2

DEMs and RS are extremely useful for the quick assessment of various types of geohazards. In this lesson you will
  • deepen the knowledge obtained in the previous section
  • learn how to combine raster maps by arithmetic algorithms
  • learn how to extract hydrologic information from digital elevation data
The training area for this lesson is the Hunza Valley in Pakistan.

Download training data for the Hunza Valley

03
January 2018
Martin Mergili
Anna Iglseder
Guided training
Lecture

GIS-supported modelling of mass movements

Mass movements (landslides, debris flows, snow avalanches etc.) can be dangerous phenomena threatening people and infrastructures. In order to take adequate mitigation measues it is essential to have an idea where mass movements can occur, but also about their travel distance and possible impact area. In this section you will
  • learn some general aspects about GIS-based modelling of mass movements
  • perform simple slope stability calculations
  • learn about more complex methods of slope stability analysis
  • get an idea how to apply computer modelling for estimating the impact area of mass movements
The training area for this lesson is the Mendoza Valley in Argentina.

Download training data for the Mendoza Valley

04.01
January 2018
Anna Iglseder
Guided training

Open GIS

In this session you will learn how to use open source GIS software applications for the analysis of spatial data. The training area is the Doren Landslide in Vorarlberg, Austria.

Download training data for the Doren landslide

04.02
January 2018
Martin Mergili
Anna Iglseder
Guided training

Advanced remote sensing methods

In the previous lessons, you have learned quite a bit on how to apply GIS and RS methods for different purposes in Applied Geosciences. However, this was only a small spectrum of what can be done with remotely sensed data. Now you will learn how to:
  • create a digital elevation model from stereo pairs of satellite imagery
  • perform a pixel-based image classification
  • generate 3D views of landscapes
The training area for this lesson is the Pamir of Tajikistan.

Download training data for the Pamir

05
January 2018
Martin Mergili
Anna Iglseder
Guided training

Practice of the methods learned in the previous lessons

06
January 2018
Martin Mergili
Independent work

Final exercise

The final exercise will consist of two independent tasks which can be solved easily given that the methods learned during the course are known. There will be no theoretical questions.