P000056, Introduction to GIS for applications in forest and landscape, 3.0 Hp
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Syllabus

Finalized by: FUN, 2023-09-12
Valid from :

Level

Third cycle

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

Objectives

The aim with the course is for the student to get a basic understanding and practical experience in Geographic Information Systems (GIS), specifically within forestry applications and within a landscape matrix context. This will be achieved by theoretical GIS-basics, data sampling and management, map projections and reference systems, spatial analysis and visualization.
After completed course the student should be able to
- understand the basics of GIS theory
- perform editing in different data structures
- perform queries in (non-/spatial) large datasets
- perform basic spatial analysis
- describe fundamental concepts of remote sensing
- describe the landscape and landscape change with the help of GIS
- describe origin and structure of spatial data
- apply quantitative analysis of spatial forest and landscape attributes
- critically assess precision and usage of GIS*.*

Content

The course gives an introduction to GIS systems. This refers to database management, visualisation and processing of spatial data and information. In the course the students will learn about origin and structure of spatial data, in vectorised features and in rasters, and how this information can be assessed and visualized. Current open data sources for forestry attributes and landscape data is part of learning activities and the students have the opportunity to critically assess and use the contemporary used GIS in Swedish forestry. Exercises in GIS is combined with knowledge transfer on how landscape and land use changes over time. The course includes quantitative analysis of forest attributes and how to sample own data in a field mobile application.

The course is organized in four modules. First module introduces the basics of GIS and geospatial data, and outlines main components of GIS interface. Second module addresses main features of vector data, attribute table management, and basics of spatial analysis based on the vector data. Third module introduces raster data and its main sources, basics of satellite imagery, and spatial analysis based on raster data. Fourth module is focused on an applied landscape analysis involving field data collection linked to GIS software.

The course have no mandatory elements but to write and peer review the assignments, which is the basis for examination.

The course will more specifically use ArcGIS PRO and R studio for the exercises as long as the status of licensed ESRI software is maintained for SLU students. For field based data collection, we will introduce ESRIs software ArcGIS online and Field maps, or similar corresponding software if the development changes over time.

Examination Formats and Requirements for Passing the Course

Write and peer review the assignments, is the basis for examination.

Responsible Department/Equivalent

Department of Southern Swedish Forest Research Centre

Supplementary information

Other Information

The course will be given as a distance course, available for all SLU campus PhD students. The course will be given at 50 % pace, over 4 weeks. Two scheduled sessions per week are time set aside for lectures and joint lab work and two scheduled sessions per week are time set aside for individual assistance with the assignments.

If many students from the same campus participate in the course, the scheduled sessions can be arranged as campus based meetings instead of distance, if lecture halls are available.

The course is divided into four modules linked to the learning objectives. Each module ends with an assignment which also will be peer reviewed, so that he students learn and get inspiration from each other.

Canvas will be used as the infrastructure for finding literature and exercises and peer reviews.

Besides scheduled sessions the students will do most of the work individually and can schedule their own time. The course runs over 4 weeks with an intention of 50 % working pace, corresponding to 3 hp (2 weeks full time).

Within each week, 8 hours are arranged for lecture & teaching sessions (2 hours x 2 lecture & seminar sessions, and 2 hours x 2 individual teaching assistance) and 12 hours for individual work.