Semantic analysis of gradual tree vitality loss using Sen2Cube.at

 Suggested by: Martin Sudmanns, Dirk Tiede

Abrupt changes in vegetation are easy to spot, gradual changes; however, such as those resulting from disease are difficult to identify.

Short description

Understanding the gradual loss of tree vitality is essential for sustainable forest management, particularly in the face of climate change and other environmental stressors. Long-term trends in forest health can be analysed using Earth observation data. Sen2Cube.at is a semantic EO data cube, that enables the analysis of large volumes of Sentinel-2 data semantically enriched over extended periods to monitor changes in forest vitality.

The goal of this master thesis is to develop a workflow for detecting and analysing temporal changes in forest vitality using the Sen2Cube.at . This study, to be conducted in collaboration with the “Bundesforschungszentrum für Wald” will focus on making use of spectral indices and semantic layers to assess vitality loss in forests, with a specific focus on gradual changes.

A specific forest area will be selected as a case study, with results validated using in-situ measurement. The outcomes of this thesis are expected to enhance the understanding of long-term forest health trends and support evidence-based forest management strategies.

Suggested reading

Sudmanns, M., Augustin, H., van der Meer, L., Baraldi, A., & Tiede, D. (2021). The Austrian semantic EO data cube infrastructure. Remote Sensing, 13(23), 4807. https://www.mdpi.com/2072-4292/13/23/4807

Start

As soon as possible

Prerequisites/qualification

• Remote Sensing & GIS
• Basic Scripting/Programming (e.g., Python)
• Interest in the topic