Individual study contents
The programme consists of four semesters. A total of 30 ECTS shall be completed each semester, consisting of 18 ECTS of mandatory modules and an additional selection of elective modules. Further academic content like specialization modules are eligible recognized by the European Credit Transfer System. This results in a total of 120 ECTS for the master's programme FIT.
Modules per semester
The first semester covers principles of innovative Forest-IT and environmental information technology.
The module consists of the parts Principles of forest data structures and principles of GIS and Remote Sensing 1.
You will gain fundamental knowledge about forest data structures and their spatial and digital representation. You will become familiar with IT based methods and techniques. You get an applied introduction to the use of geospatial data and technology in ecological and sustainable forest management and applied forest technology and more broadly in environmental sciences. You will understand principal methods of geospatial spatial data.
You will deploy algorithms conceptually and implement them using a programming language. You will use computer programming techniques to analyze datasets from practical applications in environmental science and forestry. You will develop programs that handle different data types and structures, perform calculations and represent the results visually.
The module consists of Forestry data structures and spatial data models and Environmental spatial data analysis.
You will know the theoretical fundamentals of data concepts and are able to plan and to implement databases for spatial data processing. You define and describe the important data structures and data types involved in the creation of spatial data models and identify the processing techniques required by different types of data.
You will perform statistical analyses of environmental spatial data. You will be able to select appropriate statistical procedures and tests to find structures and relations in the data and to justify statements.
You will understand the carbon cycle with special reference to forests, soils and forest products. You will be qualified to develop and critically reflect forest growth scenarios and have acquired basic knowledge of the purpose and the implementation of life cycle analysis (LCA), product carbon footprints (PCF) and corporate carbon footprints (CCF).
You will know principal methods and concepts of inventories at different spatial scales and collect comprehensive information about the state and dynamics of forests for strategic and management planning.
You gain an understanding of basic principles of tree growth and physiology in relation to changing environmental conditions. Based on this, outcomes of state-of-the-art forest monitoring systems are used to assess forest productivity, carbon budgets, and forest resilience to changing environmental conditions.
You will critically evaluate the relevance of long-term inventory and monitoring for decision making in forestry and environmental sciences.
After the course, you will have a solid foundation of principal concepts of biomass and carbon quantification and their specific cycles. You will know about the advantages applying remote sensing and modelling techniques for the spatial assessment and modelling of forest biomass at different scales. You will learn about different carbon parametrization, quantification or simulation models for forest biomass on a landscape level and discuss methods to quantify forest biomass and estimate the forest carbon stock and their uncertainty.
You acquire in-depth knowledge of projects, their planning and implementation, of different planning and implementation methods and instruments. Applying: You will be able to plan and implement projects using both classic and nature conservation-specific project planning tools.You can take different roles in project planning and execution. Analysing and evaluating: You can assess and reflect on project success and ways for improvement.
The module consists of Geodata and remote sensing as tools for spatial monitoring and Basics in Monitoring and Research.
You become familiar with fundamental theoretical ideas and practical concepts for long term monitoring in protected areas using geospatial data and remote sensing. You learn methods of quantitative and spatial research, including interdisciplinary approaches, digital tools from citizen science, and social media communication. You apply empirical social research and spatial analysis from the perspective of various stakeholders.
You will understand and apply the principles of academic writing and presenting. You can communicate effectively in an academic context.
The module consists of Sensors for automated measurements and Process modelling methodology.
You identify and describe sensor technologies used in environmental modelling and understand principles of data quality assessment and processing. You gain an overview of ecosystem models and their application, with a focus on carbon dynamics, water and nutrient cycles, and biomass growth. You learn modelling concepts, parameter estimation, model set-up and validation, and design mathematical models for use in environmental science, forestry and ecology.
You deepen your professional knowledge and skills in a specific area. You identify personal focus topics within forest information technology and explore approaches from related study programmes.
The second Semester takes place at Warsaw University of Life Sciences and focuses on the application of information technologies (IT) in forest and environment related subjects and forest management topics. In addition to the three compulsory modules, you choose two further compulsory elective modules.
- Sustainable forestry
- Data Processing and programming
- Data colletion and processing technology
Offers of the University of Warsaw Elective modules
Possible elective modules could be:
- Scientific Principles: Presentation and planning skills
- Scientific Principles: Language and social skills
- Forest biometry, biomass and tree ring analysis
- Principles of landscape ecology
- LiDAR data processing and geostatistical methods in forestry
- Sustainable forest management & forest products
- Specialisation module
During the third semester at either location FIT students pursue an independent research project framed by a range of elective modules. Students choose two elective modules.
The Project consists of a scientific or technical research project and a scientific internet colloquium.
You plan and carry out a research project of moderate scope and consolidate your academic skills in your thematic focus. You expand your abilities in scientific work, including academic writing and reviewing, and explore new areas of IT application in a virtual seminar setting.
Possible elective modules could be:
- Advanced remote sensing innovations (ARSI)
- Advanced LiDAR data analysis
- Big Data Analytics
- Machine Learning and Data-Driven Modelling
- Innovative Forest Management Methods
Possible elective modules could be:
- Innovative economy, policy and social science in forestry
- Natural resources & conservation
- Information & mathematical models
- Environmental monitoring
Possible elective modules could be:
- Learning by doing: Adaptive Management
- Forest Pest & Diseases
- Genetic Resources Conservation an Molecular Markers
Students can also choose modules from other forestry-specific Master's programmes for their individual specialisation, e.g. Forestry System Transformation.
During the fourth semester at either location students work on their Master thesis supplemented by one further elective module.
You acquire further skills in interdisciplinary scientific work. You will be able to evaluate research projects and to communicate results to expert and professional audience.
You will obtain your own research results while solving and discussing a scientific problem.
You will present the research results of your master thesis and will be able to defend its underlying assumptions, methodologies, and robustness of the key findings.
Possible elective modules could be:
- Applied Big Data Analytics
- Advanced Programming
Possible elective modules could be:
- Climate change impacts on plant growth and crop yield: non-invasive monitoring methods
- Advanced data mining techniques
You can also choose modules from other forestry-specific Master's programmes for your individual specialisation, e.g. Forestry System Transformation.
FAQ study contents
During the modules and the research project of the third semester, a practical part is always integrated into the curriculum.
You learn to handle different programmes that deal with FIT topics. The studies are enriched with many excursions to the forest, to the measuring stations or to the marteloscope areas.
Yes, the FIT team provides detailed information on the FIT FAQ page on moodle. After enrolment, students are given access to this page.
The FIT degree programme in Eberswalde and Warsaw combines the acquisition of specialist knowledge and technical skills very skilfully. Especially the practical implementation and the theoretical modules distinguish FIT from other Master's programmes.
Mansour Mahamane
Student Forest Information Technology