PSīfiakī fōtogrammetría

Course Information
TitleΨηφιακή φωτογραμμετρία / PSīfiakī fōtogrammetría
Code05YB032
FacultyEngineering
SchoolRural and Surveying Engineering
Cycle / Level1st / Undergraduate
Teaching PeriodWinter/Spring
CoordinatorApostolos Axenopoulos
CommonNo
StatusActive
Course ID600025751

Programme of Study: PPS Tmīmatos Agronómōn kai Topográfōn Mīchanikṓn (2025-sīmera)

Registered students: 0
OrientationAttendance TypeSemesterYearECTS
Core CoursesCore Courses535

Class Information
Academic Year2025 – 2026
Class PeriodWinter
Faculty Instructors
Class ID
600292873
Mode of Delivery
  • Face to face
Digital Course Content
Erasmus
The course is also offered to exchange programme students.
Language of Instruction
  • Greek (Instruction, Examination)
  • English (Examination)
Prerequisites
General Prerequisites
Elements of Photogrammetry, Linear Argebra and Matrix Calculus, Adjustment Methods Basic programming skills in python
Learning Outcomes
Familiarity of related theoretical aspects of Analytical Photogrammetry (aerial and terrestrial) for the comprehension and the development of capability to applying theoretical knowledge in practice. All the methods of Analytical photogrammetry are analysed in theoretical and practical training. Familiarity of the area of Digital Photogrammetry (algorithms, methods) for the production of medium and large-scale photogrammetric products and their evaluation. The laboratory classes aim at bringing theory into practice and enhancing the students' problem solving ability.
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Adapt to new situations
  • Make decisions
  • Work autonomously
  • Work in teams
  • Design and manage projects
  • Appreciate diversity and multiculturality
Course Content (Syllabus)
Mathematical Models used in Analytical Photogrammetry as Colinearity,Complanarity, Epipolar Geometry. Fundamental problems (intersection, exterior, relative, absolute orientation). Aerotriangulation: Bundle and Bundle adjustment with additional parameters. Automated production of DTM, Image matching, The methods of rectification and orthorectification. Accuracy and reliability, measuring instruments, calibration and data reduction. Automated processes, operators, image pyramids, dense matching. Laboratory exercises in python.
Educational Material Types
  • Notes
  • Slide presentations
  • Book
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Laboratory Teaching
  • Use of ICT in Communication with Students
  • Use of ICT in Student Assessment
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures
Laboratory Work
Interactive Teaching in Information Center
Total
Student Assessment
Description
Technical Report for the laboratory's exercises Written examination
Student Assessment methods
  • Written Exam with Short Answer Questions (Summative)
  • Labortatory Assignment (Formative)
Bibliography
Course Bibliography (Eudoxus)
Α. Δερμάνης, ΑΝΑΛΥΤΙΚΗ ΦΩΤΟΓΡΑΜΜΕΤΡΙΑ, Εκδόσεις ΖΗΤΗ, Κωδικός Βιβλίου στον Εύδοξο: 10969
Last Update
19-02-2025