POSTDOC RESEARCHER WILDLAND FUEL TYPE MAPPING 100%

With more than 10,700 students and 1,300 staff members, PXL University of Applied Sciences and Arts is a leading institution in the region. In the dynamic network of PXL, we challenge every partner today to co-create the future. Rooted in identity and practice, we train entrepreneurial, engaged, and creative professionals and artists. We collaborate with organizations to develop solutions in research and services. We uphold a commitment to quality in an innovative and multidisciplinary environment that combines approachability with professionalism.

PXL University of Applied Sciences and Arts has an external vacancy for the expertise centre PXL Bio-Research for a contractual assignment as:

The BIO-Research lab of PXL University of Applied Sciences and Arts and the sGlobe lab of the KU Leuven are seeking a highly motivated postdoctoral researcher to work on the BELSPO-funded FUELFUSION ‘Fusion of multi-scale and multi-sensor remote sensing for fuel type classification’ project.

About the labs
PXL BIO-Research aims to offer practice-oriented solutions in biodiversity policy and (urban) green management. In this context, we are conducting multiple research projects focusing on addressing the increasing demand for tools and expertise related to the inventory of ecosystems and their services using close-range remote sensing (including UAV and mobile platforms) in combination with deep learning.
The sGlobe lab is part of the division Forest, Nature and Landscape of the KU Leuven. We aim to improve our understanding of the effects of global change on biodiversity and the functioning of terrestrial ecosystems. We combine big data with state-of-the-art modelling techniques, fieldwork and drone imagery to extract patterns and answer ecological questions on large spatial scales. More information? See Show websitewww.sglobelab.com

About FUELFUSION
Wildfires have significant socio-economic and ecological impacts, posing risks to human lives, buildings, ecosystem services and biodiversity values. Areas with increased danger are being pushed north by climate change, resulting in an additional exposure of up to 15 million Europeans. However, integrated risk assessment systems for wildfires are still lacking in many industrialized countries. This project aims to facilitate bridging this gap by focusing on the accurate mapping of wildland fuel types in Belgium using diverse remote sensing techniques, exploiting the long experience obtained from similar ecosystems in Greece. Wildland fuels and their status (in terms of structure, vegetation composition, senescence and water content) are a prerequisite for any type of wildfire risk assessment framework, since they represent the biomass available for burning under the current meteorological conditions. Traditionally, fuel types have been estimated through time-consuming field observations, but recent advancements in satellite remote sensing and UAV technology in combination with multi-scale deep learning offer new opportunities. In particular, the design and implementation of novel methodologies for mapping fuel types based on the fusion of 3D point clouds and spectral data derived from UAVs – which is a research area that only recently has started being extensively investigated – offers great potential and will be the main focus of FUELFUSION.


JOB DESCRIPTION
You will closely collaborate with PhD students and research associates of both labs, and the project PI, dr. Sam Ottoy and prof. Koenraad Van Meerbeek. In addition, we foresee close collaboration with the Laboratory of Forest Management and Remote Sensing of the Aristotle University of Thessaloniki, and with prof. Ioannis Gitas and prof. Dimitrios Stavrakoudis in particular. You will collaboration in a dynamic and international scientific team where a healthy life work balance important is.
The position will focus on the integration of data resulting from different sensors (RGB, multispectral, LiDAR) and platforms (satellite, airborne, UAV, mobile) to map wildland fuels at multiple scales. To this end, we will apply novel technologies based on the fusion of spectral and LiDAR data and multi-scale deep learning algorithms. In addition, the postdoc will be involved in capacity building and outreach to stimulate future research towards an integrated fire risk assessment in Belgium.

• You hold a PhD degree in remote sensing (or in a related field) or you will have obtained it by the time you start working;
• You have strong expertise in terrestrial ecology and geospatial modelling;
• Proven UAV skills (flight mission planning, EASA drone pilot training,…) are a plus;
• You are an expert in programming languages such as R or python;
• You have proven abilities to publish at a high international level;
• You have a passion for nature and biodiversity;
• You are fluent in English, both written and oral;
• You are a team player with good communication skills.