Develop technologies required for analyzing, distributing and visualizing geospatial data

Geo-spatial data is the major driver of today’s information society. Smartphones, satellites, and sensors are creating more Big Geo Data than ever. This data is used for an increasing number of scientific purposes that aim to benefit the world. It’s a matter of gathering, analyzing, distributing and visualizing the data to make it fit for specific use, e.g. in systems for improving agricultural practice or creating healthy cities. The technologies supporting these processes are at the core of geoinformatics.

Effectively acquiring and efficiently managing these amounts of data takes more than skills. It also requires keeping pace with ongoing technological developments and understanding how to interpret them. The course Advanced Geoinformatics offers you the possibility to expand your competencies and skills in advanced data acquisition and information extraction methods or focus more on the integration of state-of-the-art methods in geospatial workflows. You will learn to design and develop algorithms, models, and tools to process geo-spatial data into reliable, actionable information.

For whom is the course relevant?

This course builds on already acquired competences concerning geospatial data acquisition and geo-information processing, and science. Thus, it is envisaged that you have relevant working experience in geo-information science and earth observation, focusing on its technological side, following graduation from a relevant BSc.

Course content

For didactic and scheduling reasons, the course requires to choose one of two specializations. A combination of courses from both specializations is NOT possible. The two specializations are earth observation science and geo-information processing, to be chosen upon registration.

Specializations

Choose one upon registration.

Earth Observation Science
Image Analysis
In this course, you will be introduced to advanced image analysis methods enabling to enrich your geoinformation problem solving abilities. Non-linear filters will be introduced for reduction of noise while preserving the boundaries. In addition, interest operators will be introduced to detect stable structures in images that are invariant to scale and rotation transformation. Various methods for dealing with objects in images will be studied. Fuzzy and sub-pixel classification will be introduced to deal with uncertainty and to increase the information content extracted from the imagery. For multisource classification decision trees will be introduced. To automatically detect corresponding image positions, the image matching techniques will be introduced. In particular, area-based matching and feature-based matching will be investigated in this course.
Laser Scanning
Airborne, terrestrial and mobile laser scanning are modern technologies to acquire and monitor the geometry of the Earth's surface and objects above the surface like buildings, trees and road infrastructure. This course provides an overview on the state of the art of these techniques, potential applications, like digital terrain modelling and 3D city modelling, as well as methods to extract geo-information from the recorded point clouds.
Geo-information Processing
Integrated Geospatial Workflows
Thanks to the digital, mobile and IT revolutions, massive amounts of data are nowadays collected at unprecedented spatial, temporal, and thematic scales by both physical and human sensors. For most applications, data availability is less of an issue. What remains an issue is how to convert this data into usable and actionable geo-information that supports decision-making at various scales and that can be further processed to generate knowledge. As a consequence, scientific workflows and scientific workflow management systems become more important for knowledge sharing and ensuring reproducibility.
Selected elements of an integrated workflow are introduced. Methods and techniques that can process massive amounts of spatio-temporal data in (quasi-)real time by using cloud computing technologies will be discussed. This course combines and extents knowledge on semantics, linked data, machine learning and distributed databases, and interactive dashboards presented online.
Spatio-temporal modelling and Analytics
Processes relevant to system Earth, whether natural or man-affected, commonly display variations in space and over time, yet our understanding of their behaviour remains limited. The increase in available monitoring data provides handles for detailed study of these processes. Unravelling the way these processes function and having a mechanism to test hypothesis as well as the possible impacts of interventions is key to contribute to a more sustainable development. At course end, you will have learnt to make use of the available data in process studies, by a variety of computational techniques.

Learning outcomes

Earth Observation Science
Upon completion of this course, you will be able to:
- Develop an image processing chain using non-linear filters and mathematical morphology operations for automatic information extraction from images in context of a given problem.
- Choose and apply a segmentation method to a given image and describe the uncertainty of the obtained result.
- Make informed decisions on the best classification method for a given set of images and a specific problem.
- Apply orthorectification to derive orthophoto.
- Make informed decisions on appropriate image matching method for a given type of data and problem.
- Evaluate attribute and scale uncertainty and relate it to the quality of derived orthophotos, accuracy of resulting image classification and matching.
- Explain how point clouds are generated from GNSS, IMU, and range finder measurements and relative sensor registration.
- Assess the applicability of laser scanning for various tasks, like surface reconstruction and 3D modelling.
- Design survey plans to acquire point clouds taking into account the accuracy and point density requirements.
- Evaluate the quality of laser scanning datasets.
- Determine and apply optimal point cloud processing methods to extract surface descriptions for geometric modelling and point cloud classification.
- Interpret and analyse point cloud processing results.
Geo-information Processing
Upon completion of this course, you will be able to:
- Analyse the quality of structured and semi-structured data sources and apply coding solutions for the storage, querying and curation of this data, appropriate for specific application contexts.
- Apply semantic information integration through knowledge formalisation, semantic enrichment, exploratory querying and data mining.
- Construct interoperable and reproducible geospatial workflows based on process modelling methods and workflow languages.
- Make informed decisions on the infrastructural system design for enabling meaningful data integration on the web.
- Discuss the main spatio-temporal modelling paradigms.
- Design a conceptual model for a spatiotemporal ABM using UML and the ODD protocol.
- Implement a basic ABM model, and calibrate this model using behavioural space.
- Explain to peers the main advantages and limitations of using geo-computational methods.
- Choose and integrate appropriate geocomputational methods to study a simple spatiotemporal problem.
- Organize and conduct the modelling and analysis phases required by a simple spatiotemporal project.
- Apply cloud computing approaches to support and/or realize the main modelling and analysis phases.
- Evaluate the innovation and societal relevance and impact of the project.

Why choose this course?

If you are currently working with geospatial data and information and have curiosity in recent developments in the acquisition and analysis of high-quality primary data or the integration and modelling of geospatial workflows to make business processes more efficient, this course offers an overview of opportunities.

About your certificate

Upon successful completion of this course, you will receive a Certificate which will include the name of the course.

Along with your Certificate you will receive a Course Record providing the name, and if applicable, all the subjects studied as part of the course. It states: the course code, subject, EC credits, exam date, location and the mark awarded.

This certificate course is part of the accredited Master’s Geo-information Science and earth Observation at ITC. If you decide to take the full Master’s Geo-information Science and Earth Observation at ITC, the Examination Board will give you in principle exemption from the course you followed successfully as a certificate course.

Admission requirements

Academic level and background

Applicants for the Certificate programme should have a bachelor's degree or equivalent from a recognised university in a discipline related to the course, preferably combined with working experience in a relevant field.

Some courses in the Certificate programme or separate modules require knowledge of, and skills in, working with GIS and/or digital image processing of remotely sensed data.

Skills in taught or related subjects are a prerequisite for some courses in the Certificate programme or separate modules. Even if the applicant satisfies the overall admission requirements, acceptance is not automatic.

Documentation

The faculty accepts transcripts, degrees and diplomas in the languages: Dutch, English, German, French and Spanish. It is at the discretion of the faculty to require additional English translations of all documents in other languages as well.

Language skills

Success in your studies requires a high level of English proficiency. Therefore, prospective students with an international (other than Dutch) degree must meet the English language requirement. As proof that you meet this requirement, you will be asked in the application procedure to upload one of the requested language certificates:

IELTS (academic) with an overall band score of at least 6.0 (with a minimum sub-score of 6.0 for speaking and writing) and certificates not older than two years.
TOEFL iBT (internet-based) with an overall score of 80 (with a minimum sub-score of 20 for speaking) and certificates not older than two years. Please note that the University of Twente does not accept the MyBest scores of the TOEFL test.
Cambridge C1 Advanced Formerly known as; Cambridge English Advanced (CAE), obtained with an A, B or C grade.
Cambridge C2 Proficiency Formerly known as; Cambridge English Proficiency (CPE) obtained with an A, B or C grade.

Only these internationally recognised test results are accepted. Without a valid certificate, we cannot process your application.

Other requirements

Ensure you have obtained a valid English test result before the application deadline. If your application is accompanied by a language test score report with a test date after our application deadline, we will not process it. Therefore, make sure to do the test in advance, as it will take time for you to get the official certificate.
When applying for a scholarship, the language requirements may be different because scholarship providers may have different requirements.

Exemptions
You are exempted from the English language requirement if you hold:

a relevant bachelor's degree from an accredited academic institution in the Netherlands
if you are a national of one of the countries in this list (PDF)
a three-year bachelor's degree in Australia, Canada (English-speaking part), Ireland, New Zealand, UK or USA. When your awarding institution is in one of these countries, but your teaching institution was not, you are not exempted. The same rule applies to distance (online) education.

Computer skills

If you lack computer experience, we strongly advise you to follow basic courses in your home country.

Notebook requirements

When you study in an ITC programme, you should have a notebook computer that meets ITC's technical notebook requirements.

Working experience

You should have working experience in a geospatial technology domain. In particular, knowledge of and skills in working with GIS and/or digital image processing of remotely sensed data and algorithmic thinking and programming are prerequisites. Fulfilment of these requirements must be shown through course records and/or project/working experience.

Computer skills

The course assumes that participants have programming skills in at least one of the following: R, Python, SQL, C++, Matlab; so that they can easily adapt to different programming environment/scripting languages.

Key information

Certification
certificate
CROHO code
75014
Duration
10 weeks
Language
100% English-taught
Application deadline
EU/EEA
15 February 2025
non EU/EEA
15 February 2025
Dutch
15 February 2025
Starting date
28 April 2025
End date
4 July 2025
ECTS
14
Tuition fees
Full period 2023 / 2024
full-time, non-EU/EEA
€ 3,906
full-time, EU/EEA
€ 3,906
2024 / 2025
full-time, non-EU/EEA
€ 3,962
full-time, EU/EEA
€ 3,962
Additional costs
Cost of living, full programme
€ 3.300
Insurance, full programme
€ 154
Please note
Additional costs are subject to change, depending on the duration of your stay.
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