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701-1634-00L 5 Credits MSC D-USYS

PReSens: Proximal and Remote Sensing For Soil and Vegetation

Lecturers & Examiners: Dr. Mirela Beloiu Schwenke, Dr. Fanny Petibon, Dr. Patrick Duddek
VVZ CR n/a

Last Updated: 2026-06-03 00:13:57

Abstract

The course introduces imaging and spectroscopy techniques spanning spectral and spatial scales: from UV–visible and near-infrared to X-ray methods, and from microns to entire landscapes. Using ground, drone, and satellite platforms, students gain hands-on experience acquiring, processing, and interpreting data on soil and vegetation in environmental and agricultural systems.

Objective

Through lectures, data analysis, and field projects, students will be able to: o Explain energy–matter interactions o Acquire and pre-process spectral (imaging) datasets o Analyse and interpret spectral (imaging) datasets o Report and critically assess the advantages and limitations of spectroscopy techniques

Content

In the first half of the semester, students are introduced to a series spectroscopy and imaging processing techniques. Each weekly module consists of a two-hour theoretical lecture establishing the scientific foundations of the method, followed by self-guided exercises (with dedicated support hours) focusing on data processing and analysis using real datasets drawn from the lecturers’ research. Students progress from analysing individual spectra, to applying classical and advanced image processing techniques, through the following modules: o The Leaf Spectrum; o The Soil Spectrum; o Imaging Spectroscopy: Classification and Temporal Change Analysis; o Seeing Soil from the Sky: Remote sensing of soil properties; o Deep Learning for Tree Species Identification; o X-ray tomography: Image Segmentation of Soil Microstructure; o Drone-based Imaging: from Canopy to Landscape Structure In the second half of the semester, students work in groups on a project focused on one technique of their choice. They design and implement a sampling strategy, collect and acquire their own data in the field, and apply the analytical approaches learned earlier in the course. Building on these skills, they process, interpret, and critically discuss their results to address a specific research question. The course is held at the ETH Eschikon-Lindau Campus, offering an immersive learning experience that combines classroom learning with hands-on field projects. The unique setting enables students to develop practical skills and apply the methods learned directly in both forest and agricultural systems.

General Information

Language
English
Levels
MSC
Frequency
Yearly recurring

Examination

Type
graded semester performance
40% Exercises,40% Project report, and20% Project presentation

Registration & Places

Max Places
25
Signup End
16.02.2026
Priority: Registration for the course unit is until 16.02.2026 only possible for the primary target group

Course Components

Type Title Time & Place Hours
lecture with exercise PReSens: Proximal and Remote Sensing For Soil and Vegetation
First half of the semester: Practical (8:15-10:00), Lecture (10:15-12:00) Eschikon, FMG B17.1 / 2. Second half of semester: Project (8:15-12:00) The course is held at the ETH Eschikon-Lindau Campus, offering an immersive learning experience that combines classroom learning with hands-on field projects. The unique setting enables students to develop practical skills and apply the methods learned directly in both forest and agricultural systems. The schedule is compatible with Project Week in Landscape Development, allowing students (FLM major) to commute to the Hönggerberg Campus in the afternoon. The course provides a complementary and methodological foundation for Crop Phenotyping (MSc Agricultural Sciences).
  • Fri 08:15-12:00 (IFW A 34)
4 h weekly

Offered In