Subject Datasheet
Completion requirements
Subject Datasheet
Download PDFI. Subject Specification
1. Basic Data
1.1 Title
Adjustment Calculations MSc
1.2 Code
BMEEOAFMSFGG01-00
1.3 Type
Module with associated contact hours
1.4 Contact hours
| Type | Hours/week / (days) |
| Lecture | 1 |
| Seminar | 2 |
1.5 Evaluation
Exam
1.6 Credits
5
1.7 Coordinator
| name | Dr. Tóth Gyula Károly |
| academic rank | Associate professor |
| toth.gyula@emk.bme.hu |
1.8 Department
Department of Geodesy and Surveying
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 aim of the course is to provide the student with knowledge of modern procedures for solving common measurement processing tasks in the field of surveying and geoinformatics. Students will be able to choose the appropriate methods for their own tasks and apply the computer tools learned in the subject in a creative way. The course also aims to introduce students to the specifics of each measurement processing procedure through some specific examples.
2.2 Learning outcomes
Upon successful completion of this subject, the student:
A. Knowledge
1. know the most important metrics (mean, mode, median, most common value, standard deviation, uncertainty, dihesion, interquartile and intersextile half-width) used to describe the characteristic value and uncertainty of measurement data,
2. be familiar with methods of determining the distribution of measurement data, the concepts and significance of statistical efficiency, robustness and resistance of estimates,
3. is familiar with the relationship between the standard error in geodesy and the uncertainty of measurement in metrology, and with the principles and tools for determining uncertainty of measurement according to the GUM (Guide to the Expression of Uncertainty in Measurement),
4. understand the basic concept of Kalman filtering and its potential applications in geodesy,
5. understand the basic concept of RANSAC (random sample consensus) estimation and the main steps of the procedure,
6. is familiar with the main cases of function definition and its applications in the processing of geodetic measurements,
7. is familiar with the main methods of adjustment of deformation analysis of geodetic networks and is able to interpret the results correctly,
8. be familiar with the main procedures for the precision design of geodetic networks.
B. Skills
1. be able to determine the most characteristic value of data and the most important metrics characterising the uncertainty of the data (mean, mode, median, most frequent value, standard deviation, uncertainty, dihesion, interquartile and intersextile half-width),
2. be able to examine the type of distribution of any data system and correctly interpret the result of a statistical test,
3. be able to determine the uncertainty of measurement in simple cases according to the GUM specifications, using appropriate software for the task,
4. be able to perform independently the adjustment of a simple deformation detection network using appropriate software and to make a statistical analysis of the results,
5. be able to perform independently the Kalman filtering using a simple system model,
6. be able to determine simple models from point cloud data using the RANSAC procedure,
7. be able to carry out the precision design of geodetic measurements and networks in some simple cases,
8. be able to determine functions for linear and non-linear cases based on geodetic measurements.
C. Attitudes
1. seek to assess the advantages and disadvantages of different adjustment and data processing procedures
the advantages and disadvantages
2. is open to the use of information technology tools,
3. is receptive to learning and applying modern, efficient data processing techniques,
4. tries to perform his/her tasks to the best of his/her ability and to a high standard.
D. Autonomy and Responsibility
1. independently analyse simple tasks and problems in geodetic and geoinformatics data processing, and solve them on the basis of given sources and patterns,
2. is open to well-founded critical comments,
3. uses cognitive skills to make decisions and to move logically from one idea to another.
4. independently makes professional decisions in simple design, construction, maintenance-operations, contracting and technical tasks in the field of civil engineering.
2.3 Methods
Lectures, computational exercises, written and oral communication, use of IT tools and techniques, self-completion of computational exercises and interactive web-based verification of the same. Exploring the topic using notes, online and offline materials - at home; interpreting and relating knowledge to other previous areas in contact lessons - with tutor guidance; exploring the application of knowledge.
2.4 Course outline
1. Determination of most characteristic value and measurement uncertainty
2. Examination of the distribution of measured data, application of statistical tests
3. Monte-Carlo procedures, measurement uncertainty based on GUM
4. Kalman filtering in the linear case
5. Kalman filtering in the non-linear case
6. Concepts and role of robustness and resistance
7. Outlier filtering procedures
8. Data processing with RANSAC
9. Determination of functions, processing of point cloud data
10. Adjustment of free networks
11. Baarda S-transformation
12. Adjustment of deformation detection networks
13. Precision design of geodetic measurements
14. Processing of continuously varying quantities
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
a) Downloadable materials:
Manuals for applied programs, web help, forums ... etc.
Interactive workbooks on the subject's github page (https://github.com/gyulat/adjustment_computations)
b) presentations, descriptions, tasks in the educational framework
c) other materials:
Vanicek P., Krakiwsky E. J.: Geodesy: The Concepts, Part III: Methodology (North-Holland, 1986)
Steiner F. (ed.): The most frequent value. Introduction to a modern concept of statistics. Akadémiai Kiadó, Budapest, 1991. ISBN-10: 9630556871
Steiner F. (ed.): Optimum Methods in Statistics. Akadémiai Kiadó, Budapest, 1997. ISBN 10: 963057439X
2.6 Other information
We only use free software to teach and learn the subject
2.7 Consultation
As indicated on the department's website, or by prior arrangement in person or by e-mail: toth.gyula@emk.bme.hu, foldvary.lorant@emk.bme.hu
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 assessment of the learning outcomes in 2.2 is based on one midterm test and two homework assignments, and
a written examination.
3.2 Assessment methods
| Assessment Name (Type) | Code | Assessed Learning Outcomes |
|---|---|---|
| written exam (summary performance evaluation) | EX | A.1-8; B.1-8; C.1-4; D.1-4 |
| midterm test (partial performance evaluation) | MT | A.1-4; B.1-3; C.3-4; D.1-3 |
| homework 1. (small homework, partial performance evaluation) | HW1 | A.4; B.5; C.2-4; D.2 |
| homework 2. (small homework, partial performance evaluation) | HW2 | A.7; B.4; C.2-4; D.2 |
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 |
|---|---|
| EX | 50% |
| MT | 30% |
| HW1 | 10% |
| HW2 | 10% |
| Total | 100% |
3.4 Requirements and validity of signature
In order to obtain a signature, the student must complete all the tasks to be completed during the semester according to point 3.3 at least at the satisfactory level (50%). We do not prescribe a condition for the success of the midterm test.
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 - in addition to paying the fee specified in the regulations - can be submitted late until 16:00 on
the last day of the delayed submission week or sent electronically until 23:59.
2) The submitted and accepted homework can be corrected free of charge till the deadline and in the manner
specified in point 1.
3) The midterm test has a retake possibility.
3.7 Estimated workload
| Activity | Hours/Semester |
|---|---|
| participation in contact classes | 14x3 = 42 |
| preparation for test | 20 |
| preparation of homeworks | 5x2 = 10 |
| preparation for the exam | 48 |
3.8 Effective date
1 September 2025
This Subject Datasheet is valid for:
2025/2026 semester II