Digital Image Analysis


The general aim of this course is to provide the students with conceptual and practical knowledge of digital image analysis with focus on modern Remote Sensing techniques.   The specific objectives are: To provide theoretical background in digital image processing and principles of analysis for environmental remote sensing applications ·          To train in using professional digital image analysis software  To train in using professional digital image analysis software 


Confident with mathematics/informatics, basic physics, and general environmental concepts 

Learning Outcomes

  In knowledge and understanding:     Knowledge of Earth Observation imagery basic principles and practice Thorough understanding of principles of digital image processing and manipulation in remote sensing The ability to give examples of and suggest uses for remote sensing in different environmental applications In abilities and skills:     Adequate skills in using image analysis software for environmental remote sensing applications The ability to choose the right data and apply the right methodology in digital image analysis The ability to present and discuss the results of remote sensing in writing and as thematic maps.  


Natural resources managers and environmental application scientists make considerable use of frequently acquired multiple spatial resolution and/or multispectral remote sensing images. However, proper remote sensing applications essentially depends on using reliable technical means for extracting thematic information from remote sensing imagery using both traditional and modern image processing techniques.    The course of ‘Digital Image Analysis’ is designed for the needs of the post-graduate students of the Department of Geoinformation in Environmental Management of MAICh. The course targets to provide adequate background on the principles and practice of image processing and analysis and to train the students in using image processing software for environmental remote sensing applications. The expected general outcome of the course is to render students confidence enough to cope with image analysis projects.    When a digital image is acquired, it needs basically pre-processing including some types of corrections, such as geometric, atmospheric, topographic, or radiometric. Spectral enhancement, such as histogram stretching and filtering may be followed. Consequently, image processing involving quantitative methods of analysis may include multi-band transformations and classification. The processing outputs can then be incorporated into a GIS application, either as input data for spatial analysis or as ready-to-use mapping outputs.    The instruction modes in this course include lectures and practical. More specifically, questions to be answered by the course include: How an image is constructed and displayed? What are the basic properties of an image? How an image can be interpreted by humans and computers? Why a digital image needs pre-processing? What are the available methodologies for digital image analysis and how some of them can be used? What outputs are expected from digital image analysis? How can we evaluate these outputs?  The course is divided into 5 units, with every unit having a theoretical and a practical component. The theoretical components comprise background on fundamental image-processing and analysis concepts, methodologies, and techniques. The practical component comprises demonstration of ERDAS Imagine (version 2013 or newer) and ecognition software in the class and resolving  relevant exercises by the students with the instructor’s supervision. 

Content Delivery

The programme sticks in a unit per day schedule, rendering the weekly teaching sequence as follows: Fundamental considerations (e.g., energy source, sensors, image characteristics and display) Image enhancement (i.e., corrections) Image transformation and interpretation Image classification Geographic Object-Based Image Analysis (GEOBIA) and validation   Linking theory and practice is the corner stone of the course. The offered scientific background is designed to balance effectively with the obtained technical skills of the students. In order to achieve this target, the daily program comprises the following triplet of components:   An adequate theoretical background in digital image processing and analysis A live demonstration of the software Students’ practice through hands-on exercises, supervised by the instructor. Finally, linking the current course with Remote Sensing and GIS background and Remote Sensing applications environment and natural resources is constantly attempted, considering that this course plays an assembling role in the educational mission of the Department.  

Coursework And Assignment Details

The evaluation of the students is based on one written exam (50% of the total grade) to be undertaken the week after the course and one practical exam (50% of the total grade) to be conducted at the end of the course.  The written exam evaluates the level of adoption in digital image analysis theory. The practical exam evaluates the use of both software ERDAS and ecognition for conducting different tasks in digital image analysis.  For the support of the students’ preparation towards examination, the following actions are taken: The essential reading item is provided in electronic form (pdf) The Course Book is provided in pdf format; it summarizes the taught theory and practice and thus can be used as a guide of the examination content The provided digital dataset for the practical exercise Additional supportive material in electronic form Self-paced and real-time support during the course.