Information Package / Course Catalogue
Unmanned Aerial Vehicle Technology in Agriculture
Course Code: TMT257
Course Type: Area Elective
Couse Group: Short Cycle (Associate's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 2
Prt.: 0
Credit: 2
Lab: 0
ECTS: 2
Objectives of the Course

The objective of this course is to teach the basic operating principles of unmanned aerial vehicles (UAVs), their application areas in agricultural production, sensor technologies, image processing applications, precision agriculture techniques, and relevant legal regulations; and to enable students to gain the ability to use UAV technologies effectively and safely in agricultural production.

Course Content

History and classification of unmanned aerial vehicles, UAV system components, flight principles, navigation systems (GNSS), flight planning, agricultural sensors and cameras (RGB, Multispectral, Thermal), remote sensing, image processing, plant health analysis, NDVI and other vegetation indices, precision agriculture applications, spraying drones, fertilization and seeding applications, data analysis, decision support systems, UAV legislation, flight safety, and agricultural application examples.

Name of Lecturer(s)
Learning Outcomes
1.Explains the basic operating principles, system components, and agricultural usage areas of unmanned aerial vehicles.
2.Defines the sensors, cameras, and data collection systems used in agricultural UAVs and evaluates their purposes of use.
3.Interprets plant growth, disease, stress, and yield status by analyzing images obtained via UAVs.
4.Effectively evaluates UAV technologies in precision agriculture applications, specifically in spraying, fertilization, seeding, and field monitoring processes.
5.Develops solution proposals by considering flight planning, legal legislation, occupational health and safety, and environmental sustainability principles in agricultural UAV usage.
Recommended or Required Reading
1.Unmanned Aerial Vehicle Applications
Weekly Detailed Course Contents
Week 1 - Theoretical
Introduction to unmanned aerial vehicles, history, and usage fields in agriculture
Week 2 - Theoretical
UAV classification, basic system components, and flight principles
Week 3 - Theoretical
GNSS, autopilot systems, and flight planning
Week 4 - Theoretical
Agricultural sensors, RGB, multispectral, and thermal cameras
Week 5 - Theoretical
Remote sensing and image processing techniques
Week 6 - Theoretical
Vegetation indices (NDVI, NDRE, etc.) and plant health analyses
Week 7 - Theoretical
UAV applications in precision agriculture
Week 8 - Theoretical
Data analysis
Week 9 - Theoretical
Agricultural spraying drones and application techniques
Week 10 - Theoretical
Fertilization, seeding, and field monitoring applications
Week 11 - Theoretical
Integration of UAV data with GIS and decision support systems
Week 12 - Theoretical
Civil Aviation legislation, flight safety, and ethical rules
Week 13 - Theoretical
Artificial intelligence-supported UAV systems and autonomous applications in agriculture
Week 14 - Theoretical
Current applications, case studies, and term evaluation
Assessment Methods and Criteria
Type of AssessmentCountPercent
Attending Lectures1%5
Assignment1%5
Midterm Examination1%30
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory140228
Assignment1505
Individual Work5015
Midterm Examination1505
Final Examination1617
TOTAL WORKLOAD (hours)50
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
PÇ-10
PÇ-11
PÇ-12
OÇ-1
4
4
4
4
4
4
4
4
4
4
2
2
OÇ-2
3
3
3
4
4
3
4
3
4
4
3
2
OÇ-3
3
3
3
4
4
4
4
4
4
4
2
2
OÇ-4
3
3
3
3
4
4
5
3
4
3
2
2
OÇ-5
3
4
4
4
4
4
4
4
4
4
2
2
Adnan Menderes University - Information Package / Course Catalogue
2026