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I. SUBJECT DESCRIPTION
II. SUBJECT REQUIREMENTS
III. COURSE CURRICULUM
SUBJECT DATA
OBJECTIVES AND LEARNING OUTCOMES
TESTING AND ASSESSMENT OF LEARNING PERFORMANCE
THEMATIC UNITS AND FURTHER DETAILS
Subject name
GEOINFORMATICS
ID (subject code)
BMEEOFTAKM2
Type of subject
Contact lessons
Course types and lessons
Type
Lessons
Lecture
1
Practice
0
Laboratory
1
Type of assessment
mid-term grade
Number of credits
3
Subject Coordinator
Name
Dr. Szabó György
Position
associate professor
Contact details
szabo.gyorgy@emk.bme.hu
Educational organisational unit for the subject
External department
Subject website
Language of the subject
magyar - HU
Curricular role of the subject, recommended number of terms
Direct prerequisites
Strong
None
Weak
None
Parallel
None
Exclusion
None
Validity of the Subject Description
Approved by the Faculty Board of the Faculty of Economic and Social Sciences, Valid from September 1, 2019

Objectives

The objectives for this course include both content and skills of geoinformatics to modeling and analysis of the natural and built phenomena of the environment. Upon completion of this course, students will understand the structure of and be able to design and execute basic GIS analysis projects. In practice, students will be able to collect and assess location based geographic data, organize and store that data, perform basic analysis functions on that data and design effective models to represent built-up and natural environmental phenomena. The course will cover the whole GIS production process from data acquisition to editing, analysis, and visualiza-tion. The course itself is divided into two equally important parts: lectures, which introduce the theory of geoin-formatics, and lab exercises, which help you to familiarize yourself with many aspects of the standardizes GIS software environment. The lectures discuss concepts, data, tools, and major aspects of assignments. The labora-tory sessions introduce the geospatial data and software tools needed for accomplishing the assignments.

Academic results

Knowledge
  1. knows the elements of geoinformatics theory,
  2. the key principles of location based environmental analysis,
  3. knows the procedures on location based intelligence and the ways of their description,
  4. knows the basic steps of digital representation of built-up and natural environment,
  5. knows the basic spatial data capturing, spatial analysis and visualization technic,
Skills
Attitude
  1. open to use geospatial tools,
  2. makes effort to perform relevant decision support analysis.
Independence and responsibility
  1. individually capable of modelling space related phenomena and realizing the dependencies,
  2. individually capable of performing basic spatial analysis,
  3. individually capable of using heterogeneous spatial data bases,
  4. uses systematized thinking approach.

Teaching methodology

Lectures and written communication, use of ICT tools and techniques. In-class discussions, calculations and analyses.

Materials supporting learning

  • Az előadások prezentációinak anyaga, amely a megfelelő időpontban a hallgatók által hozzáférhetővé válik.
  • Slideshows of the lectures which will distributed at appropriate times throughout the semester.
  • Az aktuális irodalmi lista az első órán kerül ismertetésre.
  • The current literature list will be distributed in the first lesson.

General Rules

Assessment of the learning outcomes described under 2.2. shall be based on mid-term grading.

Performance assessment methods

Detailed description of assesments during the term: Students shall submit three lab assignments and one complex project reflecting their knowledge and skills.

Percentage of performance assessments, conducted during the study period, within the rating

  • Lab practice: 30%
  • Written assignment: 30%
  • Semester test: 40%
  • total: 100%

Percentage of exam elements within the rating

  • :

Conditions for obtaining a signature, validity of the signature

Written assignments shall be assessed on a scale of 100, through assigning point scores. The sum of the scores shall serve as the basis for determining the final grade. The final grade shall be determined according to the table below.

Issuing grades

%
Excellent 90-100-100
Very good 80-89
Good 70-79
Satisfactory 60-69
Pass 50-59
Fail < 50

Retake and late completion

Retakes and make-ups are regulated by the university’s Code on Education and Examination. (1) Of the three lab assessments, cannot be retake. (2) These may be made up for or improved on one count, during the make up period. In case of re-submission or late submission, the new score will overwrite any previous scores obtained. (3) Should the student fail to obtain a passing grade as specified in (2), they may once again re-submit one written assignment, which will be evaluated for a fee.

Coursework required for the completion of the subject

Nature of work Number of sessions per term
28
44
18
90

Approval and validity of subject requirements

Consulted with the Faculty Student Representative Committee, approved by dr. Lógó Emma, Vice Dean for Education. Valid from September 1, 2019.

Topics covered during the term

Subject includes the topics detailed in the course syllabus to ensure learning outcomes listed under 2.2. can be achieved. Timing of the topics may be affected by calendar or other circumstances in each semester.

Lecture topics
1. Introduction, Global Overview of GIS Techniques
2. Geographic Data Modeling
3. GIS applications, case studies
4. Practical introduction to the used GIS software
5. Project proposal for the semester project, Managing GIS
6. GIS data collection technologies, spatial data creation
7. Earth observation, Global- , Regional-, National Spatial Data Infrastructure
8. The GeoWEB, World, EU, HU data sources
9. Visualization, Cartography and map production
10. Spatial analysis : Society, Economy, Infrastructure, Environment
11. Spatial analysis : 3D terrain modeling
12. Spatial analysis : Land use, Land cover monitoring
13. Complex spatial analysis, decision support
14. Semester project presentation

Additional lecturers

Name Position Contact details
Mostafizur Rahman PhD hallgató – PhD Student

Approval and validity of subject requirements

Part I-III of the Subject Form is to be approved by the Head of Department named under 1.8.