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Process Modelling Methodology

Sensors for Automated Measurements

Environmental spatial data analysis

 

 

 

Forestry data structures and spatial data models

 

 

 

Principles of GIS and Remote Sensing

Students get an applied introduction to the use of geospatial data and technology in ecological and sustainable forest management and applied forest technology and more broadly in environmental sciences. Students understand principal methods of geospatial data. They deploy essential and state of the art geospatial technology and are able to analyse and interpret geospatial data collected primarily in forest ecosystems.


Principles of forest data structures

Students gain fundamental knowledge about forest data structures and their spatial and digital representation. They become familiar with IT based methods and techniques of relevance for forest science analysis and management.

The course makes a link between forest and environmental measurements and processes and the data structures most appropriate to represent them. Addressed are basic (e.g. arrays, lists, matrices) and complex (e.g. databases, georeferenced data, metadata) structures, as well as their digital representation in the computer. Concrete examples from forestry and environmental sciences are used, including imagery, categorical variables, images and video.

Programming 1

Programming 1 includes the fundamentals of coding and currently uses the scripting language python for exercises and demonstrations.

Programming 2

Programming 2 shows libraries and techniques for data manipulation and visualization, using python 3.