See Study finder

Remote Sensing and Digital Image Processing

The course focuses on up-to-date knowledge and technology in the field of photogrammetry, Remote Sensing (RS) and digital image processing for geo-information extraction and production.

Short course Remote Sensing and Digital Image Processing

Go to registration!

In this course, you will learn the theoretical concepts and practical skills to extract geoinformation in established upcoming techniques and innovative approaches. Besides, you will understand the connection of the acquisition and processing procedures, with the accuracy of the results and its relevancy for various applications. 

Managing land use and the Earth’s resources and facing global challenges is becoming increasingly important due to the rising world population, economic growth, environmental degradation, and climate change, among others. 

The use of available, up-to-date, accurate and well-structured geoinformation is essential for applying various applications and utilizing the data to face global challenges and reach the optimal solutions. Thus,  planners, resources managers and application scientists now make considerable use of frequently acquired high and medium resolutions of multispectral images and other data structure such as 3D point clouds. Multispectral images are captured from various spaceborne and airborne sensors, as well as innovative platforms such as drones, 3D point clouds can be acquired with modern techniques such as laser scanner. 

Thus, it is essential to train the staff to extract both thematic and 3D geoinformation from different sensors or scanners in automated and semi-automated processing environments which are continuously under development. 

 For whom is the course relevant?

  • Staff from government agencies and private companies who have practical professional experience in remote sensing and/or photogrammetry and who wish to become familiar with state-of-the-art knowledge and technology. 
  • GIS specialists who make regular use of digitally acquired spatial reference data and are interested in the source and accuracy of these data. 
  • Staff and researchers from non-geo disciplines, who want to employ geoinformation in their research or work would also significantly benefit from this course.

What is the course content?

The course is structured in 4 sequential modules of 3 weeks each. The first two modules are concentrated on Remote sensing topics and the last two on photogrammetric topics. Learning outcomes are defined per module and evaluated progressively at the end of each one.

  • Module 1: Digital Image Processing

    In this module, you will understand and apply the basic radiometric preprocessing like atmospheric calibration, spatial and temporal filtering and contrast enhancement operations, which is essential in a geospatial problem-solving process. Besides, you will explore the integration of spectral bands in indices and ratios to provide sufficient insight into the information contents of the multi and hyperspectral data sets. 

  • Module 2: Advanced Image Classification

    In this module, Random Forests (RF) classifier will be taught and used to classify both single-date and multi-temporal satellite images. Various strategies for generating samples required to train supervised machine learning classifiers and assess their classification results will be explained in detail.

  • Module 3: Earth Observation Sensors for Mapping Applications

    In this module, you will have a  general overview of the EO sensors. The course will also treat in more focus the new platforms and sensors relevant to large-scale mapping applications such as  Unmanned Aerial Vehicles (UAVs), the aerial oblique digital sensors, and laser scanners. Besides, you will apply Global Navigation Satellite Systems (GNSS) receivers to measure the point coordinates and assess the quality of the results. 

  • Module 4: 3D Data Acquisition from Aerial Imagery

    In this module,  you will learn the geospatial data processing techniques to derive 3D geoinformation from a sequence of overlapping aerial images. Mixing between the digital photogrammetry methods and the advanced methods will be presented. The innovative techniques will be demonstrated using images acquired by a drone. A hands-on experience will be gained using the appropriate software packages to process different data sets: aerial and drone images.

What will be achieved?

Upon completion of the RS modules, you will be able to: 

  • Select appropriate sensors and image data for geospatial problem solving
  • Apply relevant contrast enhancement for visual and digital image analysis
  • Apply spatial and temporal filters to improve image data for visual and digital image analysis
  • Calculate indices and ratios for digital image analysis
  • Apply different strategies for generating training and validation samples for supervised machine learning classifiers
  • Apply various feature selection methods for data dimensionality reduction purposes
  • Summarize the main multi-temporal image analysis steps
  • Apply Random Forest classifier to classify both single-date and multi-temporal images
  • Critically interpret the classification results obtained by applying supervised machine learning classifiers

Upon completion of the photogrammetry modules, you will be able to:  

  • Describe the UAV properties and classifications and distinguish two main applications
  • Describe the sensor properties, output data quality and applications for the aerial oblique digital sensor, laser scanner and mobilemapping systems
  • Explain 3D laser scanner point cloud properties, and apply a survey plan to acquire 3D point clouds using a terrestrial laser scanner.
  • Differentiae the quality of the positional control and utilize Global Navigation Satellite Systems (GNSS) receivers to measure thepoint coordinates and assess the quality of the results.
  • Design flight planning for specific applications.
  • Apply the photogrammetric procedures for digital aerial images for mapping applications.
  • Apply the advanced photogrammetric methods for 3D data acquisition using the designated software for drone images
  • Assess the quality of all the produced data.


This course is eligible for scholarships from the OKP scholarship programme (former NFP) and MENA-MSP scholarship programme.

In case you intend to apply for OKP or MENA-MST please make sure your application for the course is in the ITC system min. two weeks prior to the scholarship deadline. The faculty ITC needs this time to process your academic assessment and provisional acceptance to the course, and scholarship eligibility check.

About your diploma

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, exam date, location and the mark awarded.

Admission requirements

Academic level and background

Applicants for this certificate course should have completed their secondary education in a discipline related to the course specialization and have at least three years of relevant practical experience.


The faculty accepts transcripts, degrees and diplomas in the following 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.

English language

As all courses are given in English, proficiency in the English language is a prerequisite.

If you are a national of one of the countries in this list (PDF), you are exempted from an English language test.

Please note: the requirements when applying for fellowships may vary according to the regulations of the fellowship provider.

English language tests: minimum requirements

Only internationally recognized test results are accepted.

TOEFL Paper-based Test (PBT)


TOEFL Internet-based Test


British Council / IELTS



C2 Proficiency / C1 Advanced

Online English tests during COVID-19

We acknowledge the difficulties experienced worldwide in taking the compulsory language test, due to the Covid-19 situation. Alternative English tests can be:

Please note that other online English language tests (i.e. IELTS Indicator test, Cambridge online test, etc.) will not be accepted.

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

Key information

CROHO code
Geo-Information Science and Earth Observation
12 weeks
100% English taught
Application deadline
31 January 2022
non EU/EEA
31 January 2022
31 January 2022
Starting date
11 April 2022
End date
1 July 2022
Enschede, Netherlands
Tuition fees
Full period 2021 / 2022
full-time, institutional
€ 3.651
Additional costs
Cost of living, full programme
€ 2.494
Insurance, year
€ 149