Seminar: Land System Science 1: Global Environmental Change - Details

Seminar: Land System Science 1: Global Environmental Change - Details

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General information

Course name Seminar: Land System Science 1: Global Environmental Change
Subtitle Land surface dynamics on agricultural land, focus: Remote sensing of bare soil
Course number GEO.07212
Semester SoSe 2025
Current number of participants 26
Home institute Geoökologie
Courses type Seminar in category Offizielle Lehrveranstaltungen
First date Thursday, 03.04.2025 08:00 - 10:00, Room: SR 4 1.34 [VSP 4](Geowiss.)
Type/Form Seminar with Practical Part (R)
Performance record Hausarbeit
Lehrsprache(n) Deutsch
SWS 4
ECTS points 5

Rooms and times

SR 4 1.34 [VSP 4](Geowiss.)
Thursday: 08:00 - 10:00, weekly (9x)
Friday, 13.06.2025, Friday, 20.06.2025, Friday, 27.06.2025, Friday, 04.07.2025 08:00 - 10:00
PC 4 3.32 [VSP 4]
Thursday: 10:00 - 12:00, weekly (9x)
PC 4 3.34 [VSP 4]
Friday, 13.06.2025, Friday, 20.06.2025, Friday, 27.06.2025, Friday, 04.07.2025 10:00 - 12:00

Module assignments

Comment/Description

Global Environmental Change – Land surface dynamics on agricultural land, focus: Remote sensing of bare soil

In this module, we will address remote sensing analysis of ecosystem functions in agricultural landscapes in the field of Land System Science / global environmental issues. The focus is on soil, which acts as a nutrient reservoir and binds carbon, and vegetation cover. If, for example, the soil lies bare for months, for example on slopes or over large areas, it can be at risk of erosion from wind or water. Many living organisms are also deprived of their habitat during this phase of exposure, as there is no protective vegetation covering the areas and food is difficult to find.
For remote sensing studies, bare soil or a low degree of vegetation cover is sometimes beneficial. For example, this situation is good for deriving soil moisture patterns or soil organic content (in the topsoil). Based on the top soil information models allow for estimating deeper layers in the soil profile.
Regardless of the perspective from which the topic is viewed, the questions regarding remote sensing data are the same:
- How can remote sensing technology be used to identify open soil over a wide area, the time of occurrence of open soil or residuals in the terrain well?
- How can existing remote sensing methods be better understood, assessed and, if necessary, optimized?

In the theoretical part, we would like to look at the following aspects:

1. Background information (briefly)
a. Land System Science
b. Influence of agricultural land use on soils
c. Soil erosion risk

2. Collaborative analysis of scientific articles on remote sensing of exposed soil and vegetation cover (focus 1 - should also impart skills for literature work with English-language scientific articles)
a. Use of AI tools for searching and analyzing scientific articles
b. Elaboration of differences in objectives, approaches, results and their interpretation
c. Getting to know the variety of methodological approaches and the visualization of results

3. Theoretical background for deriving the degree of vegetation or open ground from remote sensing data (focus 2 - based on literature work in the course)
a. Spectral patterns, remote sensing indices (vegetation and soil)
b. Threshold analysis and classification
c. Recognize challenges and problems in open ground detection: Sampling and accuracy studies (confusion matrices)

The practical part is dedicated to the analysis of Sentinel-2 with R in the area of southern Saxony-Anhalt. On the basis of empirical work, we will learn methods for recognizing and distinguishing exposed soils. It is about the technical skills for the derivation and use of:
a) Vegetation and Soil Indices
b) Empirical Soil Line derivations
c) Classification and Regression Trees
d) Random Forest
e) Sampling methods / Autocorrelation
f) Confusion matrices and accuracy analyses

The results will be refined and processed for different soil types on agricultural field blocks and fields.

An excursion day, which will bring us to an agricultural area near Halle, will help us to map the problem in the field.