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hv.dekanaat [at] ut.ee

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Jakobi 2, rooms 116–121, 51005 Tartu
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Ülikooli 16, 51003 Tartu
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Ülikooli 18–310, 50090 Tartu
College of Foreign Languages and Cultures

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Lossi 3, 51003 Tartu
Viljandi Culture Academy

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Dean's Office

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Institute of Education

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haridus [at] ut.ee

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Johan Skytte Institute of Political Studies

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School of Economics and Business Administration

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J. Liivi 4, 50409 Tartu
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Narva College

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Raekoja plats 2, 20307 Narva
Pärnu College

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Dean's Office

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med [at] ut.ee

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Ravila 19, 50411 Tartu
Institute of Biomedicine and Translational Medicine

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biomeditsiin.ut.ee

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bsmi [at] ut.ee

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Biomeedikum, Ravila 19, 50411 Tartu
Institute of Pharmacy

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pharmacy [at] ut.ee

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Institute of Dentistry

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hambaarstiteadus.ut.ee

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Raekoja plats 6, 51003 Tartu
Institute of Clinical Medicine

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kmi [at] ut.ee

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L. Puusepa 8, 50406 Tartu
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dph [at] ut.ee

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Institute of Sport Sciences and Physiotherapy

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kkdek [at] ut.ee

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Jakobi 5–205, 51005 Tartu

Dean's Office

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ltt [at] ut.ee

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Vanemuise 46–208, 51005 Tartu
Institute of Computer Science

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ics [at] ut.ee

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J. Liivi 2, 50409 Tartu
Estonian Marine Institute

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Mäealuse 14, 12618 Tallinn
Institute of Physics

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chemistry [at] ut.ee

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Ravila 14a, 50411 Tartu
Institute of Mathematics and Statistics

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Institute of Molecular and Cell Biology

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Riia 23, 23b–134, 51010 Tartu
Tartu Observatory

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Institute of Ecology and Earth Sciences

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View all other units

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Thesis topics in the remote sensing department

Remote sensing of vegetation

Estimation of forest structure variables using airborne lidar data and multispectral images for recreation forests
Supervisor Dr Mait Lang (Tartu Observatory and Estonian University of Life Sciences), mait.lang [ät] ut.ee

Forested land near to cities has a potential for recreational activities. Land use planning requires information about forest structure – species composition, stand density, age, etc. Remote sensing data in combination with land information systems can be used to estimate the forest structural variables. The estimates can serve as direct for planning or can be used as a starting point for more detailed field inventories.

Forest clearcut mapping with medium spatial resolution Landsat OLI and Sentinel-2 MSI satellite images in a region in Estonia
Supervisor Dr Urmas Peterson (Tartu Observatory and Estonian University of Life Sciences), urmas.peterson [ät] ut.ee

Forest clearcut mapping with satellite images is part of Estonian national environmental monitoring programme. Tartu Observatory carries out this sub-programme for last ten years. Landsat images from US archives, that have been traditionally used for clearcut mapping for fifteen years, have been supplemented by European Space Agency's Sentinel-2 images in the last years. Landsat images have a 30 m spatial resolution, Sentinel-2 images have a 10 m resolution. The study would help to better understand, what steps in post-classification image treatment would be necessary to yield in similar clearcut mapping results in case where the initial data are from either Landsat or from Sentinel-2 images. The new knowledge obtained will be applicable in Estonian environmental mapping programme. Working package is a GIS package, IDRISI and MapInfo are recommended. Facilities of Tartu Observatory and Estonian University of Life Sciences will be used.

Macrophyte dynamics at coastal areas of Estonia seashore and large lakes, monitored with two medium spatial resolution Landsat OLI and Sentinel-2 MSI satellite images
Supervisor Dr Urmas Peterson (Tartu Observatory and Estonian University of Life Sciences), urmas.peterson [ät] ut.ee

Estonian coastal areas of the Baltic Sea and the two major shallow lakes are overgrown by helophytic macrophyte belt, dominated by common reed (Phragmites australis). Images from two medium spatial resolution satellites, Landsat OLI and Sentinel-2 MSI have been used to monitor the macrophyte expansion. An original non-parametric image interpretation methodology has been applied on late summer images. Results from the two different satellite scanners that have different spatial resolution give slightly different results. A study will be initiated, what steps would be necessary to the data processing flow to fit the results from different satellites into one single time series. Area of interest could be one of the two Estonian large islands, one of the two Estonian large shallow lakes or a stretch of the Baltic Sea coast. Working package is a GIS package, IDRISI and MapInfo are recommended. Field work at lakeshore or at seashore during field work season could be envisioned. Facilities of Tartu Observatory and Estonian University of Life Sciences will be used.

Are satellite phenology metrics influenced by urbanization in the Baltic region?
Supervisor Jan Pisek, Tartu Observatory, mait.lang [ät] to.ee

Urban vegetation provides crucial ecosystem services, such as reducing noise, absorbing pollutants, serving as habitats for some migratory and local birds. Vegetation phenology, the timing of seasonal developmental stages in plant life cycles, can manifest impacts of urbanization on regional-to-global terrestrial ecosystem processes and services. The estimation of phenology metrics utilizes seasonal patterns in satellite vegetation indices. This project will explore how/if the process of urbanization has altered vegetation phenology/satellite phenology metrics in the heterogeneous urban environment of selected cities in the Baltic region. If in interest of the student, the engagement with field work would be possible.

Derivation of Clumping Index from MODIS BRDF data product over Estonia.
Supervisor Jan Pisek, Tartu Observatory, mait.lang [ät] to.ee

Clumping index quantifies the level of foliage grouping within distinct canopy structures relative to a random distribution. Moderate Resolution Imaging Spectroradiometer (MODIS) observations provide a means to characterize the anisotropy of surface reflectance (Schaaf et al., 2002), which has been shown to contain information on the structure of vegetated surfaces (Chen et al,.2003). The objective of this study would be to test if MODIS kernel-driven BRDF model parameters can be used to compute the clumping index over Estonia.

Characterizing leaf angle distribution function using digital photography.
Supervisor Jan Pisek, Tartu Observatory, mait.lang [ät] to.ee

The leaf inclination angle distribution function (LIAD) describes the leaf inclination angle distribution as the probability density function. Despite its profound importance in the calculation of various canopy parameters, most studies assume spherical LIAD because of the difficulty in estimating leaf inclination angles. Ryu et al. (2010) recently proposed a simple and reproducible method using a digital camera and an angle measurement tool of a public domain image processing software. The objective of this research is to verify the performance of the method with actual direct measurements of leaf angles for different trees in Järvselja.

Remote sensing of water bodies

Validation of the satellite products about suspended sediments distribution in water
Supervisor Mirjam Randla (Tartu Observatory), mirjam.randla [ät] ut.ee

Suspended sediments in water decrease the quality on waters but also influence to the transport of nutrients and chemicals in natural aquatic environment. Particles origins may vary – the large amount is coming from the cities together with waste water but also with rain fall or ressupended from sediments in shallow water. Several may provide such information and the goal of the work is to validate some of these. Use of standard software processing schemes together with field data will be learned during the practical work.

Absorption parameters in Estonian small lakes: variation in seasonal scale
Supervisor Kersti Kangro, Tartu Observatory, kersti.kangro [ät] to.ee

The underwater light climate is affected by particles present in the water column. Boreal small lakes are generally turbid with phytoplankton, suspended matter and coloured dissolved organic matter as the main absorbers. This study focuses on the variation of absorption by those substances, whereas laboratory work is also required. According to European Water Framework Directive there are 8 lake types in Estonia. The purpose of this study is to investigate if and how the absorption parameters vary seasonally in different lake types.

Deriving optical properties of water from remote sensing data
Supervisor Krista Alikas, Tartu Observatory, krista.alikas [ät] to.ee

QAA and GSCM models are widely used in the remote sensing applications to derive bio-optical properties of water. The input for the models is the remote sensing reflectance and output are the absorption and scattering coefficients that describe the optical properties of the waters. These coefficients are in turn the input for higher order algorithms (e.g. chlorophyll a concentration) or are essential parameters for deriving primary production or modelling carbon cycle. Therefore their derivation from remote sensing data is with high importance. The topic involves testing the QAA and GSCM models on the bio-optical and validating the results on the Sentinel-3/OLCI products. The results obtained during this project could be further proceed in the master studies.

Sentinel-3/OLCI possibilities for applying EU Water Framework Directive (2000/60/EU)
Supervisors Krista Alikas and Kersti Kangro, Tartu Observatory, krista.alikas [ät] to.ee

EU Water Framework Directive (WFD) requires all EU member states to monitor and report the ecological status of the waterbodies larger than 0.5km2. To classify the ecological status of the water, the phytoplankton parameters form an essential group, from where the chlorophyll a, phytoplankton biomass, cyanobacterial biomass, the intensity and frequency of the blooms can be monitored by Sentinel-3/OLCI data. The aim of the topic is to derive and compare the WFD compatible products from in situ and Sentinel-3 data and continue the time series that have been already produced earlier.

Mapping of the satellites usable for remote sensing of coastal areas and lacustrine waters
Supervisors Martin Ligi and Krista Alikas, Tartu Observatory, martin.ligi [ät] to.ee

During the thesis, the students has to compile a set of conditions a satellite sensor has to meet in order to use the data for water remote sensing. Afterwards a list of missions that are currently active or planned to the near future are researched in order to find missions that meet the previously compiled criteria. The list must include possible positive and negative aspects of using the sensor under investigation. As the end result - a list of satellites will be created that is currently missing and the scientist of the field can benefit from the research.

Remote sensing of atmosphere

Greenhouse effect - where and why?
Supervisor Dr Erko Jakobson (Tartu Observatory), erko.jakobson [ät] ut.ee

The idea is to "play" with a radiation transfer model to see how concentration changes in different greenhouse gases affect their radiation forcing at different altitudes.

Direct influence of karbon dioxide on Estonian climate
Supervisor Erko Jakobson, erko.jakobson [ät] to.ee

The aim of this project is to investigate changes in temperature due to absorption of infrared radiation for different projectd carbon dioxide concentrations using atmospheric radiative trasfer model FUTBOLIN.

Changes in spectra of diffuse ultraviolet radiation in Tõravere
Supervisor Margit Aun, margit.aun [ät] to.ee

Measurements of diffuse UV radiation started in Tõravere at summer 2016. First analyses of collected spectra will be carried out and changes in spectra due to changes in climate factors will be investigated.

Ultraviolet radiation satellite products and their comparison with Tõravere measurements.
Supervisor Margit Aun, margit.aun [ät] to.ee

The aim of this project is to give an overview of available information on UV radiation for Tõravere and compare the results with spectral measurements carried out at Tõravere.

Ozone over Estonia
Supervisor Margit Aun, margit.aun [ät] to.ee

The aim of this project is to give an overview of information about available ozone products from satellite measurements for Estonia, analyze recent ozone values in Estonia and find larger deflections from the average values (for example 2011).

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Thesis topics in the remote sensing department