Latest Projects

Research project (§ 26 & § 27)
Duration : 2023-12-15 - 2024-11-14

Groundwater recharge in forest areas: in parts of Austria - specifically Weilhartsforst - it has been shown that annual precipitation totals are decreasing (e.g. Braunau area). The aim of this study is to analyse the impact of this on groundwater recharge, especially when there is no significant surface water supply. For the future water management utilisation of such groundwater bodies, the complex interaction between percolating precipitation and underground groundwater inflows - taking into account different forms of land use such as forest, meadows and arable land - is to be investigated using a specific area (Weilhartsfort in the Braunau area).
Research project (§ 26 & § 27)
Duration : 2024-01-01 - 2027-12-31

STELLA will develop a real time pest surveillance system. The system will consist of 3 subsystems: 1) an early warning system using novel forecasting models and IoT sensors, 2) a pest detection system using drones, satellites, and a smartphone application, and 3) a pest response system providing data-driven recommendations for containment and counteractive measures. The system will be tested in 6 Use Case Pilots across 5 countries, covering 8 various diseases of importance to the EU. Capacity building activities will be developed with a focus on providing training, education, and resources to farmers, agronomists, and other stakeholders involved in crop protection. These activities will aim to equip stakeholders with the skills and knowledge necessary to effectively use the STELLA system and implement environmentally friendly crop protection alternatives. Policy recommendations generated by the project will aim to support the European Commission's goals of reducing pesticide use and managing priority plant pest outbreaks. The recommendations will be based on the data and insights gathered through the early warning, detection, and response system. A networking strategy will be developed to leverage existing knowledge and enable links with relevant organisations, networks, projects, and initiatives. Collaborating with stakeholders as well as other projects will provide opportunities to exchange ideas and learn from others' experiences.
Research project (§ 26 & § 27)
Duration : 2023-04-01 - 2025-03-31

The project aims to develop suitable methods for the detection of mulitple crop stressors using Earth Observation (EO) data. The synergies between multi- and hyperspectral datasets will be used, and the infomration content of time series leveraged. Besides classical machine learning techniques we will also employ physically-based radiative transfer models - and study the embedding derived from self-supervised learning (SSL) techniques.

Supervised Theses and Dissertations