Topic : Spatio-temporal patterns of suspended particles in coastal waters under large river-controlled from high resolution imagery. An application to rich turbid system: Lower Mekong Basin.

Key-words : Remote Sensing, SPM, Lower Mekong Basin, Tonlé Sap Lake, time series analysis.

We are seeking an enthusiastic and highly motivated M2 student to undertake a fully-funded Master-PhD project investigating the “Spatio-temporal patterns of suspended particles in coastal waters under large river-controlled from high resolution imagery. An application to rich turbid system: Lower Mekong Basin”.
The project will involve working with a team of ‘remote sensing scientists’ from the University of Littoral Côte d’Opale (ULCO), the Oceanology and Geosciences Laboratory research (LOG), France. In the frame of the VolTransMESKONG project we can offer to the student a French academic grant (~560€/month) with a duration of 6 month.

Supervisory Team
Principal Supervisor: Associate Professor Dr Charles Verpoorter, LOG/ULCO, France.
Co-supervisors: Pr Hubert Loisel, LOG/ULCO

Context for the project
The availability of High Resolution Imagery (spatial, spectral, and radiometric) with an increased time revisit (Landsat-8 and now Sentinel-2) opens the way to a more detailed observation of coastal zones and inland waters (large rivers, lakes and reservoirs) and offers an incomparable tool for water composition monitoring such as the suspended particulate matter (SPM). Quantifying the SPM budget in coastal zones from remote sensing analysis constitutes an important challenge as SPM is a key parameter in numerous economic and societal aspects such as coastal management, navigation ability, erosion and accumulation of sediments, transport of pollutants, fisheries productivity, and drinking water resource, etc. However, this budget is still not properly understood. The main reasons are that: 1) most of standard atmospheric corrections over coastal and inland waters failed and 2) coastal and inland waters are optically complex; as a consequence it impacts the accuracy of SPM algorithms and therefore the retrieval of accurate SPM values from satellites.
The main objective of the VolTransMESKONG (CNES/TOSCA) and TransMESKONG (THEIA/CNES) projects consists in improving our understanding of the spatio-temporal patterns of SPM in coastal zones under large river networks and thus from high resolution remote sensing data series analysis over the Lower Mekong Basin (LMB) including the Mekong river, the Tonlé Sap lake and the Bassac delta.
For this study, the remote sensing technique used allows us to integrate: 1) spatial differences for rich turbid systems ranging from oligotrophic waters to ultra-turbid environments exceeding 1000 NTU and 2) the temporal evolution of SPM rates in relationship with the monsoon activity over three different river network systems. Indeed, an important part of the study is based on high resolution datasets for which satellites Landsat-8, Sentinel-2 observing the coastal zones from land are available. We propose to develop, test, implement and validate methods for deriving accurate SPM concentrations above coastal and inland waters. Additionally, in all likelihood a field trip will be performed at the beginning of 2018 with the intention to consolidate our in situ data set, validate algorithm and generate new algorithm (PIM-POM).

The student will play a key role in the project coordinating the various aspects of the research, and addressing the following key research questions:
– What are temporal and spatial patterns by considering suspended particulate matter variations?
-Is SPM fluxes are decreasing or not over time?
– What is the role of the Tonlé Sap Lake in the Lower Mekong Basin hydrology?
– Does there is an anthropogenic impact over the sediments fluxes?
-What are autochtonous and allochtonous contributions (PIM Particulate Inorganic Carbon/POM Particulate Organic Carbon).

Details of scholarship
The project is mainly based on Sentinel-2 and Landsat-8 images analyses. Applicant has to be in master Ph.D. or an equivalent. We seek applicants with an interest in applying their skills in environmental sciences and preferably with good experiences in programming and modelling in imagery Applicants with a strong background in the remote sensing analysis, geosciences, ecology or a related environmental discipline, and with demonstrated academic and research excellence at the Bachelor (Honours) or Masters level 1, are encouraged to apply. The successful candidate must be able to work both independently and in a team, and be prepared in computing large amount of remote sensed data, time series analysis. Additionally, if the field trip become a success the student might have to work in laboratory conditions with the intention to generate PIM/POM algorithm and then apply it to S2 satellite data (e.g., HCN analysis, XRF, etc.). Laboratory analysis can be coach by our team.
Applicants should submit a cover letter with a statement of research interests and experience, a complete CV (including academic transcripts), and the names and contact information of at least two referees in a single pdf file, as well as a copy of their postgraduate thesis, by e-mail to Dr Charles Verpoorter (E: [email protected]).
Lastname, firstname : Charles Verpoorter Grade : MCF 36
Adress : 32 avenue Foch
Phone : 0321996406 Mail : [email protected]

Applications received on or before 22 December, 2017 will be considered for this position. Contact Dr Charles Verpoorter for further information about the project.

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