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Spatial Ecology and Remote Sensing (University of Zurich)
Last Updated: 2026-02-05 16:30:27
Abstract
This lecture focus on quantitative methods and data to study spatial ecological processes. Computing work includes an introduction to ArcGIS, remote sensing data handling, and spatial analyses. Students can bring their own data for the self-run project in the second part or use provided data.
Content
This course is an introduction to scientific concepts and methods in spatial ecology. Spatial ecological patterns and processes are discussed and methods to assess and analyze spatial relations are introduced. The course has a focus on satellite-derived environmental and ecosystems data and their spatial analysis with respect to vegetation distribution and activity, and animal movement. The course includes lectures, hands-on computer labs, and a literature study relating to the theory. The lectures introduce the spatial component of ecological questions and methods to assess spatial patterns and relationships with processes. During computer labs, the students will run exercises to introduce them to ArcGIS and get first skills in handling spatial data (including remote sensing data) and analyses. Towards the end of the course, students do their own project based on provided or potentially own scientific data sets. The aim of the course is to develop knowledge and spatial analytical and mapping skills that can be applied in the master or PhD thesis to solve ecological questions and present results meaningfully.
General Information
- Language
- English
- Levels
- MSC
- Frequency
- Yearly recurring
Examination
- Type
- graded semester performance
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture | Spatial Ecology and Remote Sensing | No time listed | 60 h semesterly |
Offered In
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Deep Track Courses (At least 20 credits must be completed within the deep track courses. Surplus credit points can be counted towards the electives.)
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Deep Track Earth Observation (These courses can be credited either as a specialization subject or as an elective subject.)
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