4-year PhD position in space research and technology: Retrieval of leaf angle distribution information from multi-angle remote sensing data
Leaf angle distribution (LAD) is a key parameter in models useful for understanding vegetation canopy processes of photosynthesis, evapotranspiration, radiation transmission, and spectral reflectance. Yet, despite the strong sensitivity of many models to variability in LAD, the difficulty in measuring LAD causes it to be one of the most poorly constrained parameters. Satellite remote sensing is currently the only technology able to provide consistent data over large areas and longer periods of time. Multi-angle remote sensing enables us now to describe surface properties by means that are not possible using mono-angle data.
This doctoral thesis will devise, test, and implement a novel methodology exploiting multi-angle sensors to retrieve LAD. First, the doctoral student shall investigate the impact of LAD on select spectral indices (NIRv) and their angular variation in the principal plane. Different LAD shall lead to different NIRv angular variations, especially in the hot spot region where viewing and illumination directions coincide. The LAD information shall be extracted from this NIRv angular variation. The proposed modelling framework will be then validated over RAMI and select ICOS sites with airborne, multi-angular observations using our UAVSpec sensor (Kuusk 2011; Pisek et al. 2015).
Once thoroughly tested and validated, the approach will be applied at a global scale using the sub-hourly high temporal frequency EPIC observations. Improving information about LAD is essential for advancing ecological understanding of its role within the biophysical interaction of sunlight and the vegetation canopy, and would improve prediction and forecast horizons of vegetation dynamics globally.
The PhD student will be working in Tartu Observatory of the University of Tartu.
Core tasks
- Literature review of the state-of-the-art
- Exploring the potential of canopy near-infrared reflectance for retrieval of leaf angle distribution information with a canopy radiative transfer model
- Testing the methodology/concept with available airborne multi-angle data
- Applying the methodology and retrieving the leaf angle distribution information with DSCOVR EPIC data
Requirements
Master’s degree in remote sensing, geography, geoinformatics, quantitative ecology, physics or wider spatial and natural sciences.
The ideal candidate has proven experience in following essential skills:
- previous work with satellite remote sensing data
- data analysis with Python or R
- confident in English language spoken and written. See more info about language requirements. English language test must be submitted by 15 of May
Desired knowledge
Priority will be given to candidates with experience in remote sensing, programming knowledge, especially in Python or R.
Funding and Health Insurance
The position is fully funded. Full-time PhD student will be on a junior researcher position with gross salary of 1830 EUR (net approx. 1450 EUR) with expected increase of 5-10% per year. Living costs in Estonia are very reasonable and the allowance can cover your living costs.
All PhD are provided with Estonian national health insurance. Health insurance coverage is available for the full nominal study period of PhD studies (4 years). University is also covering regular health checks and some health improvement (e.g. gym, swimming) costs for the staff members.
Living in Estonia
In Estonia you will be living in a highly connected society, with free wireless Wi-Fi almost everywhere. Many everyday activities are made easier with various IT solutions: register a company with as little as 18 minutes, park your car with phone, register courses online etc. Entrepreneurship and innovative solutions are highly welcomed in Estonia, which has a strong start-up community and has also become known as the Silicon Valley of Europe. Student life in Estonia is full of activities and events. There are many organizations and events that help foreign students to settle into Estonian life and create a social network in the country. For more information about living in Estonia.
Start of the studies: 2 September 2024
To apply
Please submit the following materials via email to jan.pisek@ut.ee by 20 March:
- • A one-page letter of motivation explaining how your prior research experience qualifies you for the position and why you would like to work on this topic.
- • Copies of both bachelor's and master's diplomas, and diploma supplement (bachelor's and master's transcript/mark sheet, including the description of the grading scale). Applicants graduating in 2024 and having their diplomas issued later than the application deadline, should electronically submit their most recent official Transcript of Records by the required deadline along with the rest of the required documents. Please note that you must have graduated from your master´s studies by 1 August, 2024.
- • A two page (max.) CV (including publications if available).
- • Names and contact details for at least two references.
- • Shortlisted applicants will be contacted before the end of March 2024.
