E-2437 - Phd Candidate in Floodwater Mapping Using
il y a 3 semaines
**Temporary contract | 48 months | Belvaux**:
***:
**Are you passionate about research? So are we Come and join us**:
The Luxembourg Institute of Science and Technology (LIST) is a Research and Technology Organization (RTO) active in the fields of materials, environment and IT. By transforming scientific knowledge into technologies, smart data and tools, LIST empowers citizens in their choices, public authorities in their decisions and businesses in their strategies.- Discover our Environmental Research and Innovation department: ERIN Department
Embedded in the department’s Environmental Sensing and Modelling (ENVISION) unit, the ‘Remote sensing and natural resources modelling’ group is carrying out impact-driven research, geared towards monitoring and predicting environmental systems in a changing world. Our research group capitalizes on a blend of remote sensing data obtained from space
- and air-borne platforms, as well as in-situ data measured with Internet of Things (IoT) devices, for producing information on the status of natural resources. Our research and development activities focus on the synergistic use, processing, and interpretation of data from multiple complementary active and passive sensors installed on both space
- and airborne platforms. We rely on competences in environmental sciences, such as hydrology and hydraulics, meteorology, plant physiology, and geography for monitoring variations in Earth’s resources. We integrate remotely sensed information with in-situ data, process-based models and leverage satellite communication, IoT and deep learning technologies in order to provide evidence-based decision support tools in near real time across a variety of thematic domains: disaster risk reduction, precision agriculture/viticulture/forestry, preservation and management of natural resources, maritime surveillance.
***:
**How will you contribute?**:
In the framework of the FNR-funded SWIFT project "Shallow Water Modelling and Satellite Imagery Combination for Improving Flood Prediction", we aim to advance further our capabilities in flood monitoring and modelling through the integration of remote sensing (RS) observations and shallow water modelling. We intend to leverage our expertise in remote sensing, hydraulic modelling, data assimilation, and data fusion to achieve the project's primary objectives:
- Enhance the retrieval of topography data by combining RS-derived information from diverse satellite missions and geographical datasets.
- Improve the accuracy of RS-based flood extent mapping by enhancing existing algorithms.
- Identify systematic errors in RS-derived flood extent maps and improve algorithms for generating ‘exclusion maps’.
- Enhance flood prediction by assimilating various RS-derived flood observations and leveraging improved topography, flood information, and exclusion maps.
- You will:
- Specifically concentrate on the development and validation of novel automated flood mapping systems, based on Synthetic Aperture Radar (SAR) and optical data.
- Further develop a Deep Learning algorithm, designed to detect floodwater in urban areas and over bare soils. A current version of the algorithm uses an urban-aware U-Net model and multi-temporal intensity and coherence data from dual-polarization Sentinel-1. The urban-aware module incorporates a SAR-based probabilistic urban mask to guide the selection of input features crucial for detecting floodwater across specific land cover classes. Our goal is to extend the existing urban-aware module for including vegetated areas, thereby enabling the automated mapping of flooded vegetation.
- Conduct extensive background literature analysis;
- Plan and organise experiments to define and test hypotheses and develop forefront research;
- Publish the results of the study in peer-reviewed journals;
- Present papers at scientific conferences;
- Take part in the PhD and research training.
**Education**
- A MSc degree in e.g. mathematics, remote sensing, machine learning, engineering, computer science
**Experience and skills**
- Some knowledge of programming and processing of remote sensing data would be an advantage.
**Language skills**
- Good level both written and spoken English.
**Your LIST benefits**:
- An organization with a passion for impact and strong RDI partnerships in Luxembourg and Europe that works on responsible and independent research projects
- Sustainable by design, empowering our belief that we play an essential role in paving the way to a green society
- Innovative infrastructures and exceptional labs occupying more than 5,000 square metres, including innovations in all that we do
- An environment encouraging curiosity, innovation and entrepreneurship in all areas
- Personalized learning programme to foster our staff’s soft and technical skills
- Multicultural and international work environment with more than 50 nationalities represented in our workforce
- Diverse and inclusive work environment empow
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