Latest Projects

Research project (§ 26 & § 27)
Duration : 2024-04-01 - 2024-09-30

Vegetation mapping is an essential component in the domain of nature and environmental protection. Traditional approaches, aligned with current guidelines, necessitate high research specifications typically fulfilled through terrain mapping efforts. Despite its efficacy, this method encounters limitations in terms of seasonality and the timely processing of extensive areas. In contrast, remote sensing-based models offer noteworthy advantages under their season-independence and rapid large-scale processing capabilities. The present initiative seeks to leverage new technologies, such as cloud computing, to augment conventional supervised remote sensing classifications by merging ecological expertise with the sophisticated capabilities of cloud computing technology. For a few years now, the “Google Earth Engine” (GEE) platform has made it possible to carry out geospatial processing data and analyze them based on a huge time satellite imagery series at large study area in combination with multivariate statistical methods. It also enables the integration of location and laser scan data as well as geospatial information systems data. Challenges and Research Requirements in the project: Integrating the processing chain into a cloud platform poses considerable challenges and necessitates extensive research for a coherent, smooth, and consistent adaptation. From the initial model selection to the subsequent post-processing phase, passing through exhaustive feature selection analysis and model evaluation, which are crucial phases of adaptation, require exhaustive research to ensure the accomplishment of expected outcomes in the project. Recognizing the complexity of this task, the Egger Natural Space Planning Company requires the expertise of a remote sensing scientist specializing in cloud computing platforms. The scientist, their expertise in the field, and their scientific input are vital for providing a perspective and conducting the needed research to identify optimal approaches that align with the project's expected outputs.
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.

Supervised Theses and Dissertations