Evaluating the Impact of Directional Effects on Land Surface Temperature for Improved ET estimates
il y a 2 semaines
About UM6P:
Located at the heart of the future Green City of Benguerir, Mohammed VI Polytechnic University (UM6P), a higher education institution with international standards, is established to contribute to the development of Morocco and the African continent. Its vision is honed around research and innovation at the service of education and development. This unique nascent university, with its state-of-the-art campus and infrastructure, has woven a sound academic and research network, and its recruitment process is seeking high quality academics and professionals in order to boost its quality-oriented research environment in the metropolitan area of Marrakech.
About CRSA:
CRSA is a transversal structure across several UM6P Programs. Research within the center is organized around several major areas that aim to ensure the challenging Food and Water security goal in Africa, with a special focus on developing methods/tools that use multi-source remotely sensed data. The research aims to improve our understanding of the integrated functioning of continental surfaces and their interaction with climate and humans, with emphasis on sustainable management of natural resources (soil, land, water, agriculture) in the context of Climate Change. One of center's goals is to provide a set of services and operational products to users (local, national and international) that aid in the decision support of water and food systems.
Job description
Evapotranspiration (ET) is a key component of the land surface energy balance and plays a critical role in both hydrological and agricultural systems. Among the various remote sensing approaches, land surface temperature (LST)-based methods for ET retrieval have gained popularity due to their physically based nature, minimal input requirements, and suitability for large-scale applications. However, the accuracy of these methods is highly dependent on the quality of LST measurements. LST is inherently a directional variable, and its remote sensing retrieval can be significantly influenced by viewing and illumination geometries. This study aims to investigate the impact of directional effects on LST and, consequently, on ET estimates. Specifically, we propose to use high-resolution thermal imagery acquired from drones equipped with thermal cameras at multiple viewing angles to characterize the angular variability of LST. A simple empirical or semi-empirical model will be developed and calibrated to describe this directional dependence. The corrected LST values will then be integrated into an ET retrieval framework to assess the influence of angular correction on ET estimates and evaluate the potential improvements in accuracy.
Criteria of the candidate
Master's or engineer degree in earth, environmental, remote sensing sciences, physics, or applied mathematics.
Skills
Candidate should be/have:
- Familiar with remote sensing techniques and data series analysis.
- Good skills in computer programming tools (e.g., Matlab, python, R), GIS techniques and mathematical modelling.
- Goode knowledge data analysis, image processing, and geospatial analysis
- Experience in handling and analyzing large amounts of complex data.
- Knowledge in applying machine learning approaches.
- Field work experience and monitoring.
UM6P
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