Course motivation

The ongoing global climate change, mainly the increase in air temperature caused by human activities since the industrial revolution, is impacting not only natural processes and cycles but also human societies and their economic activities on a global scale. We are witnessing, for instance, unprecedently severe forest fires in the northern America, la Niña induced floods in eastern Australia, extensive thawing of permafrost in Siberia and Alaska, unexpected drying of large water bodies due to the freshwater shortage, and rapid melting of glaciers in the Arctic regions and high mountains. In this project seminar module, we will use optical remote sensing image data acquired from satellites orbiting the Earth (e.g., Copernicus/ESA’s Sentinel-2 and NASA’s Landsat-8 & 9) or from hyperspectral visible, near-infrared, and thermal images from aircrafts (e.g., airplanes) to detect, map, and potentially monitor in space and time the actual impacts of climate change specific, but not exclusive, events on the Earth surface.

Course structure

Participants will form small research teams (groups of approx. 3 students) and work together on one of the climate change-related topics of their own liking or provided by the lecturer. Examples of project topics are:

Drying of the Aral Sea and its consequent impact on local activities/land use,
Outbreaks of insect parasites, e.g., bark beetle, in mid European temperate forests,
Contribution of thawing Arctic permafrost to regional land cover changes,
 Mapping impacts of Monsoon-induced floods at Asian and Australian continents,
 Assessing natural and economic impacts of big forest fires in California,
Cities as summer heat islands – existing causes and potential remediations.
Weekly 4-hour courses will include:

 30-45-minute theoretical lecture introducing the state-of-the-art remote sensing techniques relevant to your projects,
 short presentation by a member of each research team (each week different team member) outlining the status and progress of the project work, and
actual teamwork with hands-on project work supported by the lecturer.
Course outcomes

Upon successful completion of this module, you will know how to:

 find online available optical remote sensing satellite data and process it in the state-of-the-art remote sensing software,
  design and execute a research project, including a proper definition of scientific hypothesis/questions, selection of appropriate optical remote sensing input data and methods, and make synthesis of analytical results answering the research questions, 
write a report in accordance with the scientific standards, including proper presentation of graphical outputs (e.g., maps) and correct referencing of the relevant scientific literature (research papers, books, and conference proceedings), and
work in a team, present your intentions and results in a concise and understandable manner, receive feedback from your peers and disseminate it to improve your work and conduct an evidence-based scientific discussion.
Please note that this module has the following prerequisites: The following modules must be successfully passed before registering for the exam: B2, B6, B7

The last seminar will be devoted to final presentations of teamwork achievements in form of the scientific poster, followed by scientific discussions. Each team is further expected to produce a short final report (maximum of 20 standard A4 pages without the list of references), written in English according to scientific communication standards. The final mark will reflect the quality of the final poster presentation (40%) and report (40%) but also the performance of individual team members during the course (20%).

If you have questions or need further information please contact rsrgedu@uni-bonn.de.

Forests play a crucial role in preserving our planet, serving as carbon sinks that absorb CO2 and regulating the climate. Due to climate change, natural ecosystems on Earth were heavily impacted and forests are more and more threatened by severe wildfires. In 2016 and 2019, Australia, especially the Tasmanian island, was subjected to some of the most widespread and devastating wildfires in recent history. What made these fires so devastating is the particularly ”dense bush” type of Australian vegetation that they affected. In 2016, large parts of the Tasmania World Heritage Area and the Arthur-Pieman Conservation Area were destroyed. These vegetation communities are unique and take thousands of years to regrow. Many affected areas are remote and largely inaccessible, making a ground assessment of the true scale of the fire devastation difficult, in some locations even impossible. In this Geomatic Method seminar, you will use multispectral remote sensing images of Sentinel-2A and Landsat-8 satellites to identify the extent of the wildfires within the Arthur-Pieman Conservation area and estimate the types and amounts of vegetation that were affected by the 2016 burn.

Participants will individually execute 12 assignment tasks. The tasks will be split into two parts:

1.  literature work (2 tasks), resulting in a short (400 words max.) essay describing theoretical bases of forest fire mapping from multispectral space-borne image data (written in English), and
2.  computer work, consisting in 10 practical tasks and several questions about satellite image pre-processing methods (e.g., spatial and radiometric corrections), spectral analyses (e.g., automatic image classifications), and landcover change detection (e.g., basic statistics). The results will be submitted to the lecturer as a report, i.e., *.PDF or *.DOCX digital document written in English.

Each of the 2 x 45 min seminars will consist of:

• 15-minute theoretical introduction related to the assigned task and presented by the lecturer,
•  5-10-minutes of discussion about general issues and problems related to individual tasks, and
• about 65 minutes of individual hands-on computer work under the supervision of the lecturer.

The final mark will reflect the quality of the literature work delivered in form of an essay (30% of the overall mark) and the correctness of the satellite image analyses’ outputs and answers to questions given in the computer work part (70% of the overall mark).

Upon successful completion of this module, you will know how to:

•  use scientific literature to search for and process relevant published information,
• apply satellite image processing techniques in the context of forest fire detection and bunt area assessment, and
• extract quantitative and thematic information from satellite multispectral imagery by means of image pre-processing, classification, and change detection techniques.

The professional remote sensing software ENVI will be used in this module for computer-based work. The basic functionality of this software, i.e., loading and displaying an image with different spectral band combinations, image composition contrast enhancement, plotting of spectral signatures, working with regions of interest (ROIs), application of required image analyses, and export of images and plots suitable for inclusion in your assignment report, will be explained during first seminar sessions. Previous knowledge about remote sensing image processing will be to your advantage.

If you have questions or need further information please contact rsrgedu@uni-bonn.de.

Dieses Modul führt in die Geomatik, in Theorie und Anwendung von geo(infor)matischen Methoden ein. Es fasst die komplementä-
ren und für die Geographenausbildung zentralen methodischen Grundlagen, der Arbeit mit geographischen Informationssystemen
(GIS), Kartographie (KART) und der Fernerkundung (FE) zusammen. Es geht dabei um die Erfassung, Analyse, Modellierung und
Visualisierung raumbezogener Informationen. Dabei beschäftigt sich die FE mit der Erfassung und Auswertung von Informationen
über raumzeitliche Prozesse und Strukturen mit flugzeug- und satellitengestützten Sensorssystemen. GIS dient der Analyse und
Modellierung räumlicher Strukturen, Muster und Prozesse. Die Kartographie wird in der Vorlesung unter zwei Aspekten angespro-
chen: einmal als räumliches Bezugssystem von Geodaten und zweitens als ein Methodenbaukasten zur Visualisierung von Daten
mit Raumbezug. In diesem Modul erwerben Sie die erforderlichen theoretischen, methodischen und praktischen Grundlagen, um
mit Geodaten zu arbeiten, diese fachlich kompetent zu interpretieren, zu analysieren und mittels verschiedener Softwarepaketen
die Kenntnisse praktisch anzuwenden.
Die Vorlesung besteht aus zwei parallelen Teilen mit gemeinsamen Übungen. Im ersten Teil werden die Kenntnisse zu GIS und
Kartographie vermittelt, im zweiten die zur Fernerkundung. Die Teilnehmenden bilden Arbeitsgruppen, die Übungsaufgaben ab-
wechselnd aus den Bereichen GIS/Kartographie und Fernerkundung bearbeiten. Dabei werden sie durch die Tutor*innen der Stu-
dierendenwerkstatt Geomatik unterstützt.

Die Klausuren werden voraussichtlich im folgenden Zeitraum geschrieben werden:

1. Termin: 23–27 February 2026

2. Termin: 23–27 March 2026

Bitte beachten Sie, dass die genauen Daten innerhalb der Vorlesung bekannt gegeben werden und diese dann verbindlich sind. 

Die Tutoren unterstützen Sie bei der Lösung der Übungsaufgaben. Sie nehmen auch die Lösungen zu den Übungsaufgaben entgegen und verbuchen den Erfolg. Die Abgabe der Übungsaufgaben ist Voraussetzung für die Zulassung zur Klausur.
Innerhalb der Tutorien bilden Sie bitte fest Übungsgruppen von 2 - 3 Personen (nur mit Teilnehmenden aus dem eigenen Tutorium). Über die Emailfunktion des eCampus können Sie alle Teilnehmenden Ihres Tutoriums einzelnd oder gemeinsam erreichen. Sie vereinfachen die Kommunikation, in dem Sie in Ihren eCampus Profil neben Ihrer Uni-ID auch Ihren Namen eintragen. Ihr eCampus-Profil erreichen Sie, indem Sie ganz oben rechts auf den kleinen Pfeil klicken.
Die Tutoren ereichen Sie per Email. Sie können sich dann für eine Zoom-Sitzung mit Ihrem Tutor verabrden oder erhalten die Antwort per Email. Oder Sie kommen zu den für Übungsgruppen reservierten Zeit Montag (16:15 - 17:45), Dienstag (16:15 - 17:45), Donnerstag (10:15 - 11:45 oder 16:15 - 17:45), in den Ü9 in der Meckenheimer Allee 176. Dort können Sie die Rechner nutzen. 2 Tutoren sind während dieser Zeiten immer anwesend und ansprechbar.

Die Übungsaufgaben
Es werden 11 Übungsaufgaben gestellt. Sie müssen die Ergebnisse 11 Übungsaufgaben abgeben. Die Bearbeitungszeiten für die Übungsaufgaben überlappen sich zum Teil, weil die Übungsaufgaben häufig im Wochenrythmus freigeschaltet werden.
Format und Inhalt der Abgaben