Forest Information Technology
The studies are conducted in English. The studies start from winter semester, last for 4 semesters (2 years) and end with a vocational Master’s degree.
The Forest Information Technology (FIT) is a Master’s study programme implemented in cooperation between the Eberswalde University for Sustainable Development, and the Warsaw University of Life Sciences.
Digital, smart, and innovative technologies have found their way into forestry and natural resource management, and are there to stay. Therefore, FIT focuses on fundamental and applied knowledge of environmental information technologies and Green Information Technologies (Green IT) applications in the global forestry context.
Graduates are experts in the application of modern information technologies in the forest and environmental sector and can solve problems in silvicultural practice as well as spatial information and data management. The certificates of degree are issued by the two enrolling partner universities.
Both diplomas enable entering various European and international job markets with a focus digital technologies or sustainable natural resource management and empirical ecological research using digital data and forest and environmental management, ecological consultancy and others. Master certificates issued by the two universities are an accepted prerequisite for continuing your studies as a PhD student or entering any other doctoral degree programme.
By the end of the first semester, students are required to complete health and safety training, library training and training on discrimination and its prevention. All training is provided using distance learning techniques, on a platform: https://szkolenia.sggw.edu.pl
| Subject | Number of hours | ECTS points | Form of verification | |
|---|---|---|---|---|
|
OHS training:
4 |
- | Pass | O | |
|
Principles of forest data structures
|
Lecture:
15 Laboratory exercises: 15 |
3 | Pass | O |
|
Principles of GIS and Remote Sensing
|
Lecture:
15 Laboratory exercises: 15 |
3 | Pass | O |
|
Applied Programming in Forestry
|
Lecture:
24 Laboratory exercises: 36 |
6 | Pass | O |
|
Forestry data structures and spatial data models
|
Lecture:
12 Laboratory exercises: 18 |
3 | Exam | O |
|
Environmental spatial data analysis
|
Lecture:
12 Laboratory exercises: 18 |
3 | Exam | O |
|
Faculties I
|
Lecture:
120 |
12 | Pass | G |
| Sum | 304 | 30 |
| Subject | Number of hours | ECTS points | Form of verification | |
|---|---|---|---|---|
|
Close to Nature Silviculture & Nature Conservation
|
Lecture:
12 Laboratory exercises: 28 |
2 | Pass | O |
|
Forest engineering and utilization
|
Lecture:
10 Laboratory exercises: 20 |
2 | Pass | O |
|
Forest policy and economics
|
Lecture:
15 Laboratory exercises: 25 |
2 | Pass | O |
|
Applied GIS programming
|
Lecture:
12 Laboratory exercises: 18 |
2 | Pass | O |
|
Environmental data analysis and modeling
|
Lecture:
9 Laboratory exercises: 21 |
2 | Pass | O |
|
GIS in forest practice
|
Lecture:
12 Laboratory exercises: 18 |
2 | Pass | O |
|
Forest Photogrammetry
|
Lecture:
6 Laboratory exercises: 24 |
2 | Pass | O |
|
Digital Processing of Remotely Sensed Data
|
Lecture:
15 Laboratory exercises: 15 |
2 | Pass | O |
|
Forest inventory and modelling
|
Lecture:
6 Laboratory exercises: 24 |
2 | Pass | O |
|
Faculties II
|
Lecture:
120 |
12 | Pass | G |
| Sum | 410 | 30 |
| Subject | Number of hours | ECTS points | Form of verification | |
|---|---|---|---|---|
|
Scientific Internet Colloquium
|
Laboratory exercises:
30 |
3 | Pass | O |
|
Scientific or technical research project
|
Laboratory exercises:
90 |
15 | Pass | G |
|
Faculties III
|
Lecture:
120 |
12 | Pass | G |
| Sum | 240 | 30 |
| Subject | Number of hours | ECTS points | Form of verification | |
|---|---|---|---|---|
|
Research colloquium
|
Laboratory exercises:
30 |
4 | Pass | O |
|
Faculties IV
|
Lecture:
60 |
6 | Pass | G |
|
Master thesis
|
Diploma thesis:
0 |
20 | Exam | G |
| Sum | 90 | 30 |
