Subject Datasheet
Completion requirements
Subject Datasheet
Download PDFI. Subject Specification
1. Basic Data
1.1 Title
Mapping Technologies
1.2 Code
BMEEOFTMSFGG02-00
1.3 Type
Module with associated contact hours
1.4 Contact hours
| Type | Hours/week / (days) |
| Lecture | 1 |
| Lab | 2 |
1.5 Evaluation
Midterm grade
1.6 Credits
5
1.7 Coordinator
| name | Dr. Kugler Zsófia |
| academic rank | Associate professor |
| kugler.zsofia@emk.bme.hu |
1.8 Department
Department of Photogrammetry and Geoinformatics
1.9 Website
1.10 Language of instruction
hungarian
1.11 Curriculum requirements
Compulsory in the Land Surveying and Geoinformatics (MSc) programme
1.12 Prerequisites
1.13 Effective date
1 September 2025
2. Objectives and learning outcomes
2.1 Objectives
The main goal of the course is to provide students with in-depth knowledge of modern mapping technologies. Building on the knowledge acquired during the bachelor's degree they can learn about the development directions and application trends of photogrammetric domain (terrestrial, mobile, air) and remote sensing (laser scanning, radar, satellite optical). They will gain comprehensive knowledge of the possibilities of sensor fusion as well as location and positioning solutions for data acquisition from mobile platforms. The basic aim of the course is to make students aware of the limitations and technological capabilities of image and point cloud-based data acquisition methods, including data fusion. During laboratory hands-on training, students learn about the toolkit of point-to-cloud and image-based data processing and learn processing methods with the help of sample data and self-processed data series. In addition to the data provided by basic positioning technologies, students learn the basic processing of data from inertial measuring devices.
2.2 Learning outcomes
Upon successful completion of this subject, the student:
A. Knowledge
1. Have an overview of the main application areas of photogrammetry technologies.
2. Have an overview of the main application areas of remote sensing technologies.
3. Be aware of the technical parameters of photogrammetry and remote sensing technologies.
4. Knows the methods of point cloud, image evaluation and image processing.
5. Knows the possibilities and limitations of satellite mapping tools.
6. Knows the technological background of inertial measuring equipment.
7. Be aware of the resource needs of the mapping technologies learned.
B. Skills
1. Apply the basic methods of point cloud processing, image evaluation, and image processing.
2. Selects and designs the optimal processing chain(s) for the given task.
3. It is capable of performing basic remote sensing processing operations.
4. Pre-process the basic navigation data required by the moving sensors.
5. Describes the main topics of the subject orally and in writing in a concise manner, using technical terms correctly.
C. Attitudes
1. Collaborates with the instructor and fellow students in the process of expanding their knowledge.
2. Strives to produce accurate mapping end products.
3. Arrive at classes on time to prepare for the practice assignments assigned to the classes.
4. During the exercises, the student asks for help from the supervisor to the extent necessary to complete the lesson task.
D. Autonomy and Responsibility
1. Independently performs the tasks assigned as class work.
2. In the event of criticism of the work of teachers and students, the student accepts the well-founded critical remarks and incorporates them into their further tasks.
3. In certain situations, e.g. in practical classes, the student cooperates with his/her fellow students in solving tasks.
2.3 Methods
Lectures and computer-based laboratory exercises. Performance evaluation through exams and homework
2.4 Course outline
1. Mapping technologies. Trends, applications, new research results
2. Aerial laser scanning and its applications
3. Introduction, Advanced Optical Image Processing
4. Satellite SAR data collection, Sentinel-1 sensors, Radar time series analysis
5. Topographic displacement tracking with Radar DinSAR technology
6. Passive microwave mapping,
7. Global Environmental Models, Floods, Soil Moisture, Drought Monitoring
8. Remote thermal sensing: Urban heat islands
9. Big Earth Data, Google Earth Engine
10. The Basics of Kálmán Screening
11. Processing of inertial sensors and their measurements
12. Market Mobile Mapping Systems
13. Autonomous Systems, SLAM
14. Summary
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.
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
Lillasand T. M., Kiefer R. W., Chipman W. J. : Remote Sensing and Interpretation , John Wiley and Sons, Inc., 2015, ISBN: 111834328X
Campbell, J. B. (1996) Introduction to Remote Sensing (2nd Ed), London:Taylor and Francis.
R. Harris, 1987. "Satellite Remote Sensing, An Introduction", Routledge & Kegan Paul.
John A. Richards (2013) Remote Sensing Digital Image Analysis: An Introduction , Spinger
Jensen, J. R. (2000) Remote Sensing of the Environment: An Earth Resource Perspective, 2000, Prentice Hall, New Jersey.
Jensen, J. R. (2005, 3rd ed.) Introductory Digital Image Processing, Prentice Hall, New Jersey. http://www.cla.sc.edu/geog/rslab/751/index.html
Lillesand, T. M., Kiefer, R. W. and Chipman, J. W. (2008, 6th ed.) Remote Sensing and Image Interpretation, John Wiley, New York.
Mather, P. M. (1999) Computer Processing of Remotely‑sensed Images, 2nd Edition. John Wiley and Sons, Chichester.
W.G. Rees, 1996. "Physical Principles of Remote Sensing", Cambridge Univ. Press
2.6 Other information
1. Participation in the exercises is mandatory. A student who misses 70% of the practice cannot obtain credits for the subject. 2. The student could use his or her own computer for the exercises after prior arrangement
2.7 Consultation
Before or after lecture and in official consulation hours
This Subject Datasheet is valid for:
2025/2026 semester II
II. Subject requirements
Assessment and evaluation of the learning outcomes
3.1 General rules
The performances of the present subject (e.g. solving practical tasks) are suitable for the student to demonstrate the acquisition of the knowledge of the civil engineering profession at the end of the entire training. The learning outcomes set out in point 2.2 are evaluated on the basis of a laboratory task performed during the exercises and a 60-minute final exam.
3.2 Assessment methods
| Assessment Name (Type) | Code | Assessed Learning Outcomes |
|---|---|---|
| 1. Test (summary assessment) | T1 | A.1-A.7; |
| 2. Lab assignment (continuous partial performance evaluation) | HW1 | B.1-B.5; C.1-C.4; D.1-D.3 |
The dates of deadlines of assignments/homework can be found in the detailed course schedule on the subject’s website.
3.3 Evaluation system
| Code | Weight |
|---|---|
| T1 | 70% |
| HW1 | 30% |
| Total | 100% |
3.4 Requirements and validity of signature
No signature can be obtained from the subject.
3.5 Grading system
| Grade | Score (P) |
|---|---|
| excellent (5) | 80≤P |
| good (4) | 70≤P<80% |
| satisfactory (3) | 60≤P<70% |
| pass (2) | 50≤P<60% |
| fail (1) | P<50% |
3.6 Retake and repeat
1) Homework can be sent late – subject to the payment of a fee specified in the regulations – in electronic form until 24:00 on the last day of the replacement period.
2.) Test can be completed once.
3.7 Estimated workload
| Activity | Hours/Semester |
|---|---|
| participation in contact lessons | 14 |
| preparation independent acquisition of the written curriculum assigned for performance evaluation | 30 |
| independent preparation of HW | 40 |
| 66 | |
| Total | 150 |
3.8 Effective date
1 September 2025
This Subject Datasheet is valid for:
2025/2026 semester II