Subject Datasheet
Download PDFI. Subject Specification
1. Basic Data
1.1 Title
Digital surface modeling
1.2 Code
BMEEOFTDT83
1.3 Type
Module with associated contact hours
1.4 Contact hours
| Type | Hours/week / (days) |
| Lecture | 2 |
1.5 Evaluation
Exam
1.6 Credits
3
1.7 Coordinator
| name | Dr. Attila Juhász |
| academic rank | Associate professor |
| juhasz.attila@emk.bme.hu |
1.8 Department
Department of Photogrammetry and Geoinformatics
1.9 Website
1.10 Language of instruction
hungarian and english
1.11 Curriculum requirements
Ph.D.
1.12 Prerequisites
1.13 Effective date
1 May 2021
2. Objectives and learning outcomes
2.1 Objectives
The course consists the theorethical knowledge of digital terrain / surface modeling and analysis in depth. After completing this course, the students will understand the details of data acquisition procedures and sources used in digital elevation modeling (DEM), the structure of the databases, interpolation and analysis methods. The mathematical background of these methods will also be presented. In practice, the students will be able to collect relevant elevation data, perform spatial analysis functions, create and visualize appropriate digital elevation model in connection with environmental phenomenas of natural and built-in areas. The course reviews the entire process of elevation data acqusition, the DEM's structures, interpolation, analysis and visualization.
2.2 Learning outcomes
Upon successful completion of this subject, the student:
A. Knowledge
- The elevation data acquisition methods (operational principles, groups, characteristics)
- Elevation data preprocession, filtering
- Knowledge of DEM structures
- Interpolation methods
- Technological background of DEM analysis and visualization
B. Skills
- Ability of creating a strucured DEM
- Preprocessing and filtering the raw data
- Selection of relevant interpolation method
- Creation of static and dynamic data visulization
C. Attitudes
- Openmind to the usage of GIS tools and solutions
- Systematic thinking
D. Autonomy and Responsibility
- Independent work
- Ability in organizing and managing
2.3 Methods
Lectures, oral and written communication, usage of IT tools and technologies, Discussions, analysis and calculations during the courses.
2.4 Course outline
| Hét | Előadások és gyakorlatok témaköre |
| 1. | Basics of the digital elevation modeling. |
| 2. | DEM structures |
| 3. | Elevation data acqusition sources I. |
| 4. | Elevation data acqusition sources II. |
| 5. | Interpolation methods I. |
| 6. | Interpolation methods II. |
| 7. | Interpolation methods III. |
| 8. | Data quality |
| 9. | Mathematical background of 3D analysis |
| 10. | Static and dynamic visualization |
| 11. | DEM exercise (consultation) |
| 12. | DEM exercise (consultation) |
| 13. | DEM exercise (consultation) |
| 14. | DEM exercise (consultation) |
The above programme is tentative and subject to changes due to calendar variations and other reasons specific to the actual semester. Consult the effective detailed course schedule of the course on the subject website.
2.5 Study materials
- Documents on the homepage of the subject.
- Web documents.
2.6 Other information
2.7 Consultation
The consultation times are listed on the department's homepage.
In e-mail: juhasz.attila@emk.bme.hu
This Subject Datasheet is valid for:
2023/2024 semester II
II. Subject requirements
Assessment and evaluation of the learning outcomes
3.1 General rules
The evaluation of the students knowledge (listed in 2.2) is based on a complex practical task and an oral exam.
3.2 Assessment methods
| Teljesítményértékelés neve (típus) | Jele | Értékelt tanulási eredmények |
| Complex task | T | A.1-A.5; B.1-B.4; C.1-C.2; D.1-D.2 |
| Oral exam | E | A.1-A.5 |
The dates of deadlines of assignments/homework can be found in the detailed course schedule on the subject’s website.
3.3 Evaluation system
| Jele | Részarány |
| T | 50% |
| E | 50% |
| Összesen | 100% |
3.4 Requirements and validity of signature
The criteria of getting signature is to acquire the 50% of the potential points during the semester.
3.5 Grading system
| Érdemjegy | Pontszám (P) |
| jeles (5) | 80<=P |
| jó (4) | 70<=P<80% |
| közepes (3) | 60<=P<70% |
| elégséges (2) | 50<=P<60% |
| elégtelen (1) | P<50% |
3.6 Retake and repeat
The complex task can be replaced till the last day of the repeat week. In written form unti 16:00 or in e-form until 23:59.
3.7 Estimated workload
| Tevékenység | Óra/félév |
| Attendance on the contact lectures | 28×1=28 |
| Praparation to the task | 10 |
| Creating the task | 30 |
| Preparation to the exam | 10 |
| Sum | 78 |
3.8 Effective date
1 May 2021
This Subject Datasheet is valid for:
2023/2024 semester II