GMT655 - 3-D SPATIAL MODELING
| Course Name | Code | Semester | Theory (hours/week) |
Application (hours/week) |
Credit | ECTS |
|---|---|---|---|---|---|---|
| 3-D SPATIAL MODELING | GMT655 | Any Semester/Year | 2 | 2 | 3 | 7 |
| Prequisites | ||||||
| Course language | English | |||||
| Course type | Elective | |||||
| Mode of Delivery | Face-to-Face | |||||
| Learning and teaching strategies | Lecture Question and Answer Preparing and/or Presenting Reports Drill and Practice | |||||
| Instructor (s) | Prof. Dr. Cevdet COÅžKUN AYDIN | |||||
| Course objective | The aim of course is to educate engineers with capabilities of advanced engineering skills and give detailed information on fundamentals, applications and methods of three dimensional geospatial modeling and three-dimensional data analyses in Geomatics Department. | |||||
| Learning outcomes |
| |||||
| Course Content | Three dimensional geospatial modeling and visual representation. Interpretation and analysis of geospatial data in 3D models. Integration of geospatial data from homogeneous and heterogeneous data sets. 3D city modeling. Urban models. Multi-scale modeling and generalization. 3D cartographic visual representation. Realistic 3D scenario simulation. Integration of virtual reality and cartographic representation schemes. | |||||
| References | Kennedy, H. (2010). Introduction to 3D Data: Modeling with ArcGIS 3D Analyst and Google Earth. Germany: Wiley. | |||||
Course outline weekly
| Weeks | Topics |
|---|---|
| Week 1 | Three dimensional geospatial modeling and visual representation |
| Week 2 | Interpretation and analysis of geospatial data in 3D models |
| Week 3 | Interpretation and analysis of geospatial data in 3D models |
| Week 4 | Integration of geospatial data from homogeneous and heterogeneous data sets |
| Week 5 | 3D city modeling |
| Week 6 | Midterm exam |
| Week 7 | Multi-scale modeling and generalization |
| Week 8 | 3D cartographic visual representation |
| Week 9 | 3D cartographic visual representation |
| Week 10 | Realistic 3D scenario simulation |
| Week 11 | Midterm exam |
| Week 12 | Cartographic representation |
| Week 13 | Cartographic representation |
| Week 14 | Virtual reality applications |
| Week 15 | Final preparation |
| Week 16 | Final Exam |
Assesment methods
| Course activities | Number | Percentage |
|---|---|---|
| Attendance | 16 | 5 |
| Laboratory | 14 | 5 |
| Application | 0 | 0 |
| Field activities | 0 | 0 |
| Specific practical training | 0 | 0 |
| Assignments | 5 | 5 |
| Presentation | 1 | 10 |
| Project | 0 | 0 |
| Seminar | 0 | 0 |
| Midterms | 2 | 25 |
| Final exam | 1 | 50 |
| Total | 100 | |
| Percentage of semester activities contributing grade succes | 38 | 50 |
| Percentage of final exam contributing grade succes | 1 | 50 |
| Total | 100 | |
WORKLOAD AND ECTS CALCULATION
| Activities | Number | Duration (hour) | Total Work Load |
|---|---|---|---|
| Course Duration (x14) | 16 | 2 | 32 |
| Laboratory | 14 | 2 | 28 |
| Application | 0 | 0 | 0 |
| Specific practical training | 0 | 0 | 0 |
| Field activities | 0 | 0 | 0 |
| Study Hours Out of Class (Preliminary work, reinforcement, ect) | 14 | 5 | 70 |
| Presentation / Seminar Preparation | 1 | 16 | 16 |
| Project | 0 | 0 | 0 |
| Homework assignment | 5 | 4 | 20 |
| Midterms (Study duration) | 2 | 14 | 28 |
| Final Exam (Study duration) | 1 | 16 | 16 |
| Total Workload | 53 | 59 | 210 |
Matrix Of The Course Learning Outcomes Versus Program Outcomes
| D.9. Key Learning Outcomes | Contrubition level* | ||||
|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |
| 1. Define problems in Geomatics Engineering and use Information Technology effectively in order to solve these problems. | X | ||||
| 2. Learn basic Mathematics, Science and Engineering formations and use them productively in professional life | X | ||||
| 3. Choose, use and improve recent technology and methods that needed for Geomatics Engineering applications | X | ||||
| 4. Earn the ability of producing new spatial products with data coming from international Geomatics application by using his/her qualification of obtaining, interpretation and analyzing of spatial data and by adding personal viewpoint | X | ||||
| 5. Estimate geodetic and geodynamic parameters with geodetic observations and use kinematic and dynamic functional models effectively in studies | X | ||||
| 6. Know advanced national and international applications in areas of Photogrammetry and Laser Scanning and contribute to the development processes of these applications | X | ||||
| 7. Develop strategies for data collection from space/aerial images and aerial/terrestrial laser scanning data; define the most appropriate methods for data extraction from collected data; process, analysis, integrate data with other spatial data, develop models; attend to field works and present results and outputs visually, statistically and thematically | X | ||||
| 8. Develop case / aim specific static or dynamic online systems, design spatial database management systems and produce visual products by following recent developments in GIS environment | X | ||||
| 9. Find solutions for aim relevant data obtainment by being familiar with working principle of scanning devices and sensors and their usage areas | X | ||||
| 10. Design systems which are considering scientific facts for more economically and more reliable management of industrial and infrastructure applications | X | ||||
| 11. Consider factors of social, environmental, economic, health and job security in professional life. | X | ||||
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest