Applied Remote Sensing for Earth Sciences

Learn to explore for earth and geothermal resources to secure future demands for energy and minerals

From the houses that we live in to the meals that we eat and the smart phones that we use: earth resources play a vital part in our daily lives. Earth also contains hidden geothermal systems that can provide energy for the production of electricity. In the search for these earth and geothermal resources, remote sensing technology becomes ever more important. Are you an earth scientist who wants to become a remote sensing expert? Then ITC’s specialization in Applied Remote Sensing for Earth Sciences is what you’re looking for.

In our courses we integrate the use of state-of-the-art digital technology with an earth science perspective. You will study the natural environment using hyperspectral remote sensing, optical and thermal infrared spectroscopy, geophysics and contextual image analysis. In a digital workflow environment, you will learn to combine remote sensing data with laboratory and field measurements, and to extract information from these data. This also involves handling “big” data sets, and using scripting and other digital tools. For your MSc research you’ll have the option of joining forces with ITC’s research group 4D-Earth.


See also the full programme overview and programme structure.

Data Analysis in Earth Sciences (7 credits)

This course gives an introduction to scientific computing, focused on handling data in remote sensing and earth science studies. It is designed for students with a background in earth sciences who have little or no prior experience in handling numerical data. 

The backbone of the course is an introduction to scripting (computer programming): writing own processing scripts allows to create custom solutions, and can also be used to automate the processing of large data sets. You will primarily get to work with open-source software which then can freely continue to use during your career.

A gentle introduction to  statistical concepts is given by practical applications in the chemical laboratory. Computer tutorials are done to gain experience on mathematical dos and don’ts in handling of numerical data. Special attention will be given to creating graphics for data visualization, and to produce print-quality output that can be used directly in written reports.

Spectral Geology (7 credits)

This course teaches the use of spectroscopic methods to obtain geologic information. It is designed for students with a solid understanding of Earth Sciences that want to use state-of-the-art spectroscopic methods to analyse geologic samples for their mineral contents.

The course will cover the interaction of matter with electro-magnetic radiation of different wavelength ranges (e.g., gamma-ray, visible, infrared and thermal infrared). You will be involved in extensive, hands-on laboratory measurements with various imaging and non-imaging spectroscopic instruments. Furthermore, you will be trained in solving instrument problems and in executing the necessary pre-processing steps to calibrate the instruments and ensure the quality of the resulting measurements.

The course further contains a component on statistical data processing and (semi-) quantitative spectral modelling techniques derived from current research. These analytical techniques will lead to information on the mineralogy and mineral chemistry of samples, as well as earth surface parameters. You will experiment, validate and compare multiple approaches, investigate their assumptions and limitations, and deduce their suitability to solve earth science problems.

Geological Remote Sensing (7 credits)

This course gives an introduction to geological, regolith and soil remote sensing in the application of earth resources mapping. It includes the integration of remote sensing imagery with geoscience data sets, regional geophysics (e.g. aeromagnetics, radiometrics) and DEMs for geological interpretation and the generation of geological maps. The course is designed for students with a background in earth sciences and an ability in handling remote sensing and GIS software. 

The course covers a description of the sensor design and resolution issues of operational multispectral, hyperspectral, airborne, and satellite borne sensors measuring optical and thermal infrared responses. Active sensors such as LiDAR and SAR radar are also covered. An introduction to atmospheric and geometric corrections of raw and/or radiance level imagery is provided. Various image processing, data integration and compositional/structural information extraction techniques will be covered for these different remote sensing and geophysics data sets. Examples demonstrating techniques used for the validation of map products will be covered.

The course includes the practical application and generation by students of interpreted geological/regolith/soil map products from available and relevant remote sensing, geoscience and regional geophysical data sets.

Field Methods for Earth Sciences (7 credits)

Field methods play an important role in geological remote sensing studies. These methods are used for validation of desktop interpretations and for characterization of rock outcrop.

This course introduces you to state-of-the-art field methods for characterization of rock and outcrop in geological remote sensing studies. Methods will include measurements of the mineralogical and chemical rock composition and other relevant physical rock properties. Acquisition of field data will be practiced with a variety of field instruments, including reflectance and gamma-ray spectrometers.

During the course you will practice the preparation and execution of a field campaign. Prior to the field work, remote sensing studies are performed and detailed field work plans are prepared. In the field, the students will practice field data collection using different sampling strategies. Important aspect of the training is the assessment of the field data quality. Results of the field campaign will be further analyzed, interpreted and integrated with the results of the desk study.

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