Drones and 3D Point Clouds in Forestry (5 cr)
Code: 6M00FW50-3001
General information
Enrolment period
09.05.2022 - 28.08.2022
Timing
29.08.2022 - 16.12.2022
Credits
5 op
Mode of delivery
Contact teaching
Unit
Forestry
Campus
TAMK Main Campus
Teaching languages
- Finnish
Seats
0 - 20
Degree programmes
- Degree Programme in Forestry
Teachers
- Kalle Tammi
- Eeva Sundström
Person in charge
Kalle Tammi
Groups
-
20IM
-
19IM
-
21AIM
-
19AIM
Objectives (course unit)
In the course, you will learn about laser scanning and the data produced with laser scanning, as well as the utilization of drones.
After completing the course, the student:
• knows the sources of open spatial data and the principles of producing airborne laser scanning data
• can integrate open spatial data with self-produced data
• has the basic skills of flying a drone and collecting drone image data
• can use photogrammetry software to produce data from close-range aerial images collected by a drone
• knows the operating principles of a terrestrial laser scanner and the possibilities of using point cloud data collected with it
• can utilize point clouds in open-source spatial data software
• can apply the above-mentioned skills in forestry applications
Content (course unit)
Key open datasets utilized in forestry, methods for collecting point clouds and three-dimensional spatial data, data processing, drones and close-range aerial imaging, airborne and terrestrial laser scanning, commercial and open-source software for data processing, data utilization, and application in forestry, Traficom's open category A1/A3 class drone remote pilot online theory exam.
Assessment criteria, satisfactory (1-2) (course unit)
The student:
-knows the sources of open spatial data
- can moderately combine open spatial data with self-produced data
- has the basic skills of flying a drone and passes the drone remote pilot online theory exam
- can guidedly collect image data with a drone and produce data using photogrammetry software
- knows the principles of a terrestrial laser scanner and the possibilities of using point cloud data
- can guidedly use point clouds in open-source spatial data software.
Assessment criteria, good (3-4) (course unit)
In addition to the above (satisfactory level), the student:
- knows the principles of producing airborne laser scanning data
- can independently combine open spatial data with self-produced data
- can fairly independently make a plan, fly a drone, and collect image data
- can produce data using photogrammetry software from close-range aerial images collected by a drone
- knows the operating principles and possibilities of using a terrestrial laser scanner
- can independently use point clouds in open-source spatial data software
- can identify forestry applications for the skills acquired during the course.
Assessment criteria, excellent (5) (course unit)
In addition to levels satisfactory and good, the student:
- can independently make a plan, fly a drone, and collect image data
- can extensively utilize point clouds in open-source spatial data software
- can apply the skills acquired during the course in a versatile manner in forestry tasks.
Location and time
Autumn semester 2022
Exam schedules
The exam will be arranged in the end of the course.
Assessment scale
0-5
Teaching methods
The teaching includes lectures, exercises and assignments. Exercises and assignments are done both in groups and individually.
Traficom's theory test for drone pilot certification is performed during the course. The certification is one of the course assignments.
The course exam is arranged on Moodle platform in the end of the course.
Learning materials
The study material will be available during the course on the moodle platform.
The self-study material for A1/A3 open category pilot test is provided by Traficom on droneinfo.fi -pages.
Additional recommended literature will be specified during the course.
Student workload
Lectures and exercises 50 hours.
Self-learning (incl. assignments and preparation for tests, etc.) 85 hours.
Content scheduling
Outdoor exercises are mainly during the first period, because of the more favourable weather conditions. During the second period the emphasis is on software exercises.