Basic information
- Field of study
- Geospatial Computer Science
- Major
- Remote Sensing and GIS
- Organisational unit
- Faculty of Geo-Data Science, Geodesy, and Environmental Engineering
- Study level
- Second-cycle (engineer) programme
- Form of study
- Full-time studies
- Profile
- General academic
- Didactic cycle
- 2024/2025
- Course code
- DGEITGS.IIi1.07200.24
- Lecture languages
- English
- Mandatoriness
- Obligatory
- Block
- Major Modules
- Course related to scientific research
- Yes
|
Period
Semester 1
|
Method of verification of the learning outcomes
Completing the classes
Activities and hours
Lectures:
15
Project classes: 30 |
Number of ECTS credits
3
|
Course's learning outcomes
| Code | Outcomes in terms of | Learning outcomes prescribed to a field of study | Methods of verification |
| Knowledge – Student knows and understands: | |||
| W1 | issues of ALS and TLS technology, ALS and TLS conversion, compression and rejestration. | GEI2A_W03 | Test |
| W2 | issues of spatial reference systems, gravimetric and satellite measurements. | GEI2A_W01, GEI2A_W03 | Test |
| W3 | rules and algorithms of processing point clouds like filtering, classification and visualization. | GEI2A_W03, GEI2A_W05 | Test |
| W4 | issues of DTM and DSM. | GEI2A_W04 | Test |
| Skills – Student can: | |||
| U1 | do the conversion and registration of ALS i TLS data. | GEI2A_U01 | Project |
| U2 | do the operations on ALS and TLS point clouds like filtering and classification. | GEI2A_U03 | Project |
| U3 | do the generation of ALS i TLS products. | GEI2A_U03, GEI2A_U05 | Project |
| U4 | do the spatial analyzes on ALS and TLS clouds. | GEI2A_U05 | Project |
| Social competences – Student is ready to: | |||
| K1 | solve problems in an independent and creative way | GEI2A_K02, GEI2A_K03 | Project |
Program content ensuring the achievement of the learning outcomes prescribed to the module
Student workload
| Activity form | Average amount of hours* needed to complete each activity form | |
| Lectures | 15 | |
| Project classes | 30 | |
| Preparation for classes | 18 | |
| Realization of independently performed tasks | 10 | |
| Examination or final test/colloquium | 2 | |
| Contact hours | 2 | |
| Preparation of project, presentation, essay, report | 10 | |
| Student workload |
Hours
87
|
|
| Workload involving teacher |
Hours
45
|
|
* hour means 45 minutes
Program content
| No. | Program content | Course's learning outcomes | Activities |
| 1. |
Preprocessing laser data. |
U1, U2, U3, U4, K1 | Project classes |
| 2. |
Introduction to airborne laser scanning (ALS).: Historical overview, Basics of airborne laser technology. |
W1, W2, W3, W4 | Lectures |
| 3. |
Automatic and manual filtering of laser data.: Automatic and manual filtering of laser data (points classification ground, vegetation, buildings, etc.). |
U1, U2, U3, U4, K1 | Project classes |
| 4. |
Geometric aspects of aerial laser scanning.: Laser flight plan. |
W1, W2, W3, W4 | Lectures |
| 5. |
Spatial reference systems in geoinformatic practice. |
W1, W2, W3, W4 | Lectures |
| 6. |
DTM and DSM generation based on a point cloud.: Integration of photogrammetric and cartographic data. |
U1, U2, U3, U4, K1 | Project classes |
| 7. |
Satellite and gravimetry measurements of GPS / INS, global and local systems. |
W1, W2, W3, W4 | Lectures |
| 8. |
Orthophotomap generation based on point clouds and non-metric images. |
U1, U2, U3, U4, K1 | Project classes |
| 9. |
Basic operation on airborne cloud of points. |
W1, W2, W3, W4 | Lectures |
| 10. |
Three-dimensional modeling of selected objects.: Three-dimensional modeling of buildings, trees, power lines |
U1, U2, U3, U4, K1 | Project classes |
| 11. |
Laser data processing algorithms. |
W1, W2, W3, W4 | Lectures |
| 12. |
Basic operations on TLS data.: Point cloud rejestration variants: open source and commercial software review. |
U1, U2, U3, U4, K1 | Project classes |
| 13. |
TLS technology products generation.: TLS technology products generation: |
U1, U2, U3, U4, K1 | Project classes |
| 14. |
Introduction to DTM and DSM.: Basic definitions, global and regional projects, algorithms of laser data processing, representations of DTM. |
W1, W2, W3, W4 | Lectures |
| 15. |
Three-dimensional modeling of selected objects.: Three-dimensional modeling of buildings, trees, power lines. |
W1, W2, W3, W4 | Lectures |
| 16. |
Integration of point clouds from ALS and TLS.: Integration of point clouds from ALS and TLS. |
U1, U2, U3, U4, K1 | Project classes |
| 17. |
Three-dimensional modeling of selected objects on TLS data.: Point cloud rejestration variants: open source and commercial software review. |
W1, W2, W3, W4 | Lectures |
| 18. |
TLS technology products.: TLS products. |
W1, W2, W3, W4 | Lectures |
| 19. |
Integration of point clouds from ALS and TLS.: Integration of point clouds from ALS and TLS. Methods and variants. |
W1, W2, W3, W4 | Lectures |
Extended information/Additional elements
Teaching methods and techniques :
Team Based Learning, E-learning, Group work, Discussion, Lectures
| Activities | Methods of verification | Credit conditions |
|---|---|---|
| Lectures | Test | |
| Project classes | Project |
Additional info
- Metody nauczania wykorzystywane podczas prowadzenia zajęć: Praca grupowa, Wzajemne ocenianie (Peer assessment), Uczenie zespołowe (Team Based Leanrnig)
- Przedmiot został ulepszony i rozszerzony dzięki zastosowaniu specjalistycznego oprogramowania zakupionego w ramach programu IDUB D16 „Unowocześnienia laboratoriów i infrastruktury dydaktycznej o wartości jednostkowej nie większej niż 50 tys. zł – II edycja 2024”.
Conditions and the manner of completing each form of classes, including the rules of making retakes, as well as the conditions for admission to the exam
Attendance at lecture – not necessary. Two absence from classes is possible. If more absence occurs a student needs to give an extra paper in order get positive grade.
Method of determining the final grade
The final grade is the weighted average of the final test – FT and project grades – P. Final grade = 0.6*FT+0.4*P The project grade - P is the arithmetic average of all projects, on condition that each project was passed as a positive grade. The student may retake the final test twice. The grade of final test - FT is arithmetic average of all correction terms.
Manner and mode of making up for the backlog caused by a student justified absence from classes
The way to make up the absence of classes: consultations
Rules of participation in given classes, indicating whether student presence at the lecture is obligatory
Lectures: Studenci uczestniczą w zajęciach poznając kolejne treści nauczania zgodnie z syllabusem przedmiotu. Studenci winni na bieżąco zadawać pytania i wyjaśniać wątpliwości. Rejestracja audiowizualna wykładu wymaga zgody prowadzącego. Project classes: Studenci wykonują prace praktyczne mające na celu uzyskanie kompetencji zakładanych przez syllabus. Ocenie podlega sposób wykonania projektu oraz efekt końcowy.
Literature
Obligatory- Shan J., Toth Ch. K., 2009. Topographic laser ranging and scanning. Principles and Processing. CRC Press. Boca Raton, London, New York 2009.
- Kurczyński Z., 2014. Fotogrametria. PWN Warszawa.
Scientific research and publications
Publications- Twardowski M., Marmol U., 2012. Wizualizacja i przetwarzanie chmury punktów lotniczego skaningu laserowego. Archiwum Fotogrametrii, Kartografii i Teledetekcji. vol. 23 s. 457–466.
- Marmol U., Mikrut S., 2012. Attempts at automatic detection of railway head edges from images and laser data. Image Processing & Communications : an International Journal vol. 17 no. 4 s. 151–160.
- Marmol U., 2010. The two-stage filtering of airborne laser data in a frequency domain. Geodesy and Cartography vol. 59 no. 2 s. 83–97.
- Borowiec N.: Polyhedral building model from airborne laser scanning data; Geomatics and Environmental Engineering 4/10, AGH – Kraków 2010.