SV0065, Remote Sensing and Inventory, 15.0 Hp
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Syllabus
Finalized by: Ordföranden för programnämnden för utbildning inom skog (PN-S), 2023-12-22
Valid from : Autumn semester 2025 (2025-09-01)
Level
Second cycle
(A1N)
Main field of study
Forestry Science, Biology
Biology Area
Other biology courses
Sub-area forestry science
Other within forestry science 15 hp
Grading Scale
The grade requirements within the course grading system are set out in specific criteria. These criteria must be available by the course start at the latest.
Course language
English
Entry Requirements
The equivalent of
120 credits
60 credits within one of the following one of the following subjects/main fields of study
- biology
- natural resources management
- environmental sciences
- soil science
- physical geography
- forestry science
- forest science
- forest management
- forest and wood engineering
5 credits within geographic information systems (GIS)
and English 6.
Objectives
The aim of the course is for the student to acquire theoretical and practical knowledge in data collection through remote sensing and field inventory, and how these are combined to address issues related to forestry and forest ecosystems.
After completing the course, the student should be able to
- describe the aims and methods of data collection through remote sensing and field inventory to address forestry and forest ecosystem issues
- explain the physical basis of remote sensing of vegetation in general and forests in particular
- justify and apply the steps of processing in remote sensing-based data collection and mapping
- select and justify appropriate data sources and methods with respect to application, scale, data quality and cost and critically evaluate the information produced
- independently plan, carry out and analyze inventories suitable for organizations and companies active in forestry and nature conservation
- discuss development trends for remote sensing and forest inventory both in Sweden and internationally.
Content
The course covers current theories used in remote sensing and forest inventory, how these data sources are integrated, and their use in various applications from forest company inventories to global greenhouse gas inventories. Common remote sensing data are aerial images, satellite images and laser scanner data. The focus of the course is on the needs of forestry and society for forestry data and information as a planning basis for various types of decisions on forestry measures. Applications and the role of remote sensing data in continuous environmental analysis and as a tool for achieving sustainability goals are considered. The course also includes processing of remote sensing data and data collection for ecological and environmental applications, linked to Sweden's environmental monitoring program. The course ends with group project work where remote sensing and field inventory are combined to produce information to shed light on specific issues.
Implementation:
The course utilizes various teaching methods to promote student learning and discussion through lectures, literature seminars, computer exercises and project work.
The course focuses on the following general competences:
Information literacy, critical thinking, problem solving, scientific methods, digital literacy, use of technology, oral communication, written communication, independence.
The following elements are compulsory:
Exercises, project work and some seminars.
Cooperation with the surrounding society takes place through working life/vocational connections in program/course development together with an external program council of employer representatives, as well as through guest lectures.
Examination Formats and Requirements for Passing the Course
Approved oral and written presentations.
Approved participation in compulsory parts.
Responsible Department/Equivalent
Department of Forest Resource Management
Supplementary information
Module set
| Title |
Credits |
Code |
| Remote Sensing |
7.0 |
0001 |
| Inventory |
5.0 |
0002 |
| Project |
3.0 |
0003 |
The Course Replaces
SG0227