Examples of our Courses
Various courses are offered on different levels of expertise and focusing on different fields of applications.
Please find a selection below:
This training addresses advanced persons interested in the analysis of satellite imagery and spatial datasets and is dedicated to the provision of the principles of Google’s cloud infrastructure Earth Engine for earth science data and analysis. The training aims at enhancing the knowledge for developing and implementing a workbench (e.g., download of data, pre-processing, derivation of indicators and phenological indices, analysis, spatial prediction, mapping, and interpretation) for spatially analysing and visualizing remote sensing data.
This training addresses beginners to intermediated users and provides basics of the open-source geographic information system Quantum GIS (QGIS) for developing and implementing a workbench (e.g., download of data, pre-processing, derivation of indicators and phenological indices, analysis, spatial prediction, mapping, and interpretation) for spatially analyzing and visualizing remote sensing data. Monitoring and Evaluation (M&E) in the sense of derivation, analysis, and interpretation of time series is part of this training.
Introduction of Earth Observation theory and applications. Overview of fundamental principles, potentials and limits.
Overview of Remote Sensing applications ranging from polar to tropical examples. This courses provides insights into the potential of Remote Sensing for specific research fields.
Python is a powerful language for analyzing large amounts of data. The first steps up to complex implementations into other software systems are covered.
Agricultural monitoring using remote sensing data is an established process. Providing an overview of methods and real-world examples, as well as hands-on exercises are covered in this course.
This training addresses beginners and is dedicated to the basics, analysis, quality assessment, and visualization of satellite remote sensing data using QGIS and Google Earth Engine. Monitoring and Evaluation (M&E) in the sense of derivation, analysis, and interpretation of time series are part of this training. The nexus climate change – adaptation to climate change – land cover and land use – will be addressed in targeted examples and taken up in an exchange with the participants and the GeoSens team.
R is the most powerful language for data analysis and statistics. Daily data handling up to automated processing chaings executing complex statistical models are covered.
Coding or programming is a powerful tool once it has been mastered. This course covers the first steps in a coding environment up to writing a first script for a specific application.
Spatio-temporal analysis of landscape properties that are relevant for ecological research are covered in theory and practice. From converting field data to a spatial format up to fragmentation analysis are covered.
Remote Sensing is a powerful tool for conservation research and application. Content ranges from fundamental analysis using Open-Source software such as QGIS up to more complex analysis using QGIS or other software solutions.
Graphics outlining the results of the remote sensing research and presenting them is of importance for many projects. Discussing and creating graphs and presentations for a scientific audience is content of this course.
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