Job tips, internships & thesis suggestions
Here you will find job tips, thesis and project suggestions and internships, both with our own researchers and from outside the department.
Esri Sweden is looking for a GIS Ambassador
See job announcement (in Swedish). Note that this job requires proficiency in Swedish.
Date added: 2021-04-29
Scholarships abroad for geography & environmental science students
Offered by GoEco, who describe themselves as a "leading eco-tourism company with a varied selection of affordable, ethical volunteer projects abroad".
MSc project: How do forests respond to drought? Merging models and satellite observations
When: Anytime, please contat the coordinator
What: Droughts driven by climate change are being linked to increasing levels of tree mortality 1. To understand how our forests will change in the future we need to be able to accurately simulate the response of forests to drought. But this is a big challenge for ecosystem modellers. One problem has been the lack of observations of forest water status on scales that are comparable to those at which we make simulations of forest, however, with new remote sensing techniques that is changing. Vegetation Optical Depth (VOD) observations have now been processed from satellite remote sensing data for the whole world, for a timescale covering the last 30 years 2. VOD is well established to be very sensitive to vegetation water content and has been linked with forest functioning relevant to drought 3,4.
This project will use the LPJ-GUESS vegetation model to try and explain variations in plant water content caused by drought, as captured by VOD observations. For instance:
Do the spatial and temporal variations in forest water status simulated by the model correspond to those in the VOD dataset? I.e. can we explain the observations based on modelling from first principles?
To what extent are these drought events expected to cause tree mortality, based on the model? Can we link this to observed hotspots of tree mortality?
There is flexibility in the focal region(s) and exact formulation of the research questions.
The project will contribute towards a wider development agenda working to improve our ability to simulate tree mortality (http://more.bham.ac.uk/treemort), linking with researchers across Europe, in the case of this project, especially from Munich.
Advanced programming skills are not a pre-requisite, but ability to analyse datasets using a programming-based software such as Matlab or R will be fundamental to the project, as well as a basic understanding of the concepts of ecosystem modelling.
Contact: Thomas Pugh
Hartmann, H. et al. Research frontiers for improving our understanding of drought-induced tree and forest mortality. New Phytol. 218, 15–28 (2018).
Moesinger, L. et al. The global long-term microwave Vegetation Optical Depth Climate Archive (VODCA). Earth Syst. Sci. Data 12, 177–196 (2020).
Rao, K., Anderegg, W. R. L., Sala, A., Martínez-vilalta, J. & Konings, A. G. Remote Sensing of Environment Satellite-based vegetation optical depth as an indicator of drought-driven tree mortality ☆. Remote Sens. Environ. 227, 125–136 (2019).
Konings, A. G. & Gentine, P. Global variations in ecosystem-scale isohydricity. Glob. Chang. Biol. 23, 891–905 (2017).
Pan, Y. et al. A large and persistent carbon sink in the world’s forests. Science (80-. ). 333, 988–93 (2011).
Internship in research groups abroad
Are you considering a career in research? If so, you might want to make your internship in a research group. Here you'll find information on how to proceed.
Thesis suggestions from Miljöbron
Internships and student jobs in sustainability via Sustainergies
Sustainergies keeps an eye open for student opportunities at many interesting employers in Sweden:
Sustainabilities student jobs page (in Swedish)
Swedish environmental protection agency has many openings for students
Internships, summer employments, and thesis suggestions. Many student opportunities in climate, communication, environmental protection, environmental law and more.
To the Naturvårdsverket jobs page (in Swedish)
Mapping distribution and density of coconut farm in Indonesia (Bachelor Thesis suggestiion)
Are you looking forward to take part of a project in the other side of the world? Then, join our Coco Husk Team and you will not regret it!
We are working to improve the life of local villages in coconut plantations in Riau province in Indonesia.
In particular, we are trying to say stop burning coco husk and figure out other ways of using this raw material with the help of Design Centrum and Mechanical Engineering here in Lund.
But now we also need the help of Geographers that are willing to help us in mapping the area where we are planning to introduce our new eco-sustainable system of treating coco husk.
In December, went to Sungai Guntung and Tembilahan and saw local villages in coconut plantations and saw how people harvest coconut and process its derivatives like copra, shell and husk.
Therefore, we need to map the distribution and density of coconut farms in Indonesia.
We also need to investigate how much Indonesia peat land contributes to global warming, and eventually, if you get passionate about it, map the distribution of different types of bio masses that grow in Indonesia starting from coconut plantations :)
Contact: sara.mazzuoli92 [at] gmail.com
Monitoring clear cuts of old forests
What: Preliminary analysis suggests that a large share of forest harvest (clear cuts) in Sweden is harvest of old forest stands that have never been clear cut before. There is however no official data on what types of forests are being cut, but we do know the location of past cuts for the last 10 years and planned cuts for each coming year. We have made the first steps towards a homepage that indicate when panned cuts are cuts of old forests, but our estimates are surrounded by large and unquantified uncertainties.
Our ambition is to create a high-quality webpage that tracks planned cuts of old forests that store much carbon and may have high biodiversity and recreational values. Our current estimate is based on a forest age map from year 2010, but it has not been evaluated and the uncertainties increase with forest age (i.e. it is difficult to distinguish an 80 year old forest from a forest that is 200 years old).
There are multiple projects that may contribute to this goal, ranging from technical and visual developments of the webpage to scientific predictions of forest age and diversity. Multiple datasets are available on forest type, species composition, tree height from airborne laser scanning, and around 100 thousand ground plots. There are also a multitude of other maps available.
To summarize, there are multiple projects available for driven and independent students that want to contribute to the project. These include:
- Technical implementations that may involve automatic updates of the map or adaptations for users to find potentially old forests that are reported to be cut.
- Developments of the visual appearance of the homepage.
- Evaluation and corrections of the existing forest age map using plot data.
- Creation of a new forest age map and/or an index indicating the age and values of forests marked for harvest.
We are in the beginning of this work, and other ideas are welcome.
Please contact me if you are interested.
Contact: Anders Ahlström
Date added: 2021-04-27
Master thesis project - Remote sensing of trends in pristine forests in Western Russia
Pristine forests are rare in boreal Eurasia and it is debated if they sequester carbon or if they are in equilibrium with no net growth. One way to investigate that is to use remote sensing to investigate trends in vegetation indices from the 1980s until present. We have done this for Swedish pristine forests and found strong trends, in this project a similar study would be done for western Russia.
We have a copy of the original GIS files used for the map and the report (http://old.forest.ru/eng/publications/intact/). It was first produced around the turn of the century but it isn’t fully clear what is included and what definitions were used. The first part of this project would be to read up on the production of the map and compare to other available datasets on intact forests. Most information is probably given in the publications for which the map was used. When that is done trends can be extracted from e.g. Google Earth engine to investigate if these forests has become greener and if productivity has increased.
The project is suited for a driven student with very good skills in GIS and some programming.
Please contact me if you are interested.
Contact: Anders Ahlström
Date added: 2021-04-27
Implications of activation energies for the fate of organic matter in a changing climate
What: BSc thesis
When: Spring 2021
Due to the present corona restrictions, no laboratory or field-based BSc can be done with the aquatic biogeochemistry group in spring 2021. However, a possibility is to do a literature review that has a quantitative meta-analysis component, e.g. as follows:
The Arrhenius equation describes reaction rates as a function of temperature, encounter frequency, and reaction activation energy (Ea). This applies to dissolved organic carbon (DOC) reactions with enzymes, but the same framework can also be used to describe temperature dependency of sorption of DOC onto mineral surfaces, or reactions with photochemically produced reactive oxygen species. This thesis will compile literature data on Ea to test the following ideas:
1. Biological degradation of DOC has stronger temperature dependency compared with photochemical degradation or sorption/flocculation.
2. Terrestrially-derived DOC requires a higher activation energy for biodegradation, compared with algal-derived DOC.
Results will be used to discuss the fate of organic matter in aquatic systems in the face of a changing climate. Which DOC removal process will dominate in a future warmer climate? How would increased loading of terrestrially-derived DOC to aquatic systems change this? What are the consequences for aquatic generation of greenhouse gases?
This thesis subject is suited to a student who is up to searching and skimming large amounts of literature. Some creativity and mathematical skills may be needed to extract Ea values from the data in different studies.
Alternative suggestions are also welcome, if the above is not a good fit.
Contact: Martin Berggren
Master thesis suggestion: Developing methods for linking precipitation time-series data in hydrological models
What: If you have good programing skills, and want to try solving one of the hottest problems in hydrological modelling then maybe this is a good opportunity for you.
Rainfall-Runoff hydrological models are very important tools for accurate prediction of the time and location of floods and droughts as well as spatiotemporal variation of water quality and other hydrologically factors that are crucial for our life and the environment. Moreover, a good Rainfall-Runoff model helps saving the environment but also reducing the costs. All Rainfall-Runoff hydrological models (e.g. HYPE, SWAT, MIKE basin, etc.) need precipitation observations as input data to run and produce results. One of the main problems in catchments modeling is the method used for linking model forcing climate data (precipitation & Temperature timeseries data) to sub catchments. HYPE (Hydrological Predictions for the Environment) is a widely used hydrological model developed at the Swedish Metrological and Hydrological Institute (SMHI) is to be used in this research project (https://www.smhi.se/en/research/research-departments/hydrology/hype-our-hydrological-model-1.7994).
The main aim of this research project is therefore to test new methods utilizing e.g. time series analysis and machine learning methods) for linking precipitation observations to sub-catchments in hydrological models. The developed methodology may improve the performance of all Rainfall-Runoff hydrological models, which will lead to more accurate flood forecasting, drought analysis, water quality assessments, as well as all other modeling results.
Arheimer, Berit ; Pimentel, Rafael ; Isberg, Kristina ; Crochemore, Louise ; Andersson, Jafet ; Hasan, Abdulghani ; Pineda, Luis. / Global catchment modelling usingWorld-Wide HYPE (WWH), open data, and stepwise parameter estimation. In: Hydrology and Earth System Sciences. 2020 ; Vol. 24, No. 2. pp. 535-559.
Contact: Abdulghani Hasan (abdulghani [dot] hasan [at] nateko [dot] lu [dot] se), Sadegh Jamali (sadegh [dot] jamali [at] tft [dot] lth [dot] se)
BSc/MSc project: Can we detect tree mortality using high resolution satellite data?
There is increasing evidence that tree mortality rates are increasing in many regions, but ground-based monitoring of tree mortality is expensive and not available for much of the world. High resolution satellite datasets offer the potential to provide virtual inventory plots, distributed in the locations where they are needed, rather than just where funding can be found. The recent opening of a huge database of high resolution satellite observations opens up the opportunity to explore their use for monitoring tree mortality.
This project will investigate the potential to assess tree mortality in a case study approach using Planet data in an area of forest in boreal Russia, a region for which data is particularly lacking. You will develop a sampling strategy to characterise your area of interest via a series of virtual “plots”. Then create a dataset of tree mortality events by comparing satellite images over time. Finally, these events can be converted into mortality rates and linked to potential drivers. There is potential here to give exciting insights into the tree mortality rates in these remote regions, where we know relatively little about the natural dynamics. Furthermore, your work will feed into a wider project coordinated by the International Tree Mortality Network (www.tree-mortality.net), which seeks to fill in black spots in our ability to monitor rates of tree mortality.
Contact: Thomas Pugh
BSc/MSc project: Can we simulate the giants of the rainforest (and all the little trees as well)?
When: Spring / autumn 2021
What: Tropical rainforests not only have an almost mystical allure, but also an enormous impact on the world's climate, taking up as much as a quarter of annual anthropogenic carbon emissions 1. Much of the carbon that they hold is stored within the trunks of the largest trees 2. This means that being able to correctly simulate the range of tree sizes and types within the rainforest is fundamental to being able to predict how the ability of the forest to take up carbon might change in the future. The LPJ-GUESS vegetation model developed at INES is regularly used to make assessments of forest carbon uptake across the world 3,4. LPJ-GUESS is, in principle, capable of capturing the structural complexity of rainforests, but new observations offer the opportunity to improve our ability to simulate these fascinating ecosystems.
This project will use observations of tropical tree allometry 5,6 to update how tropical tree species are simulated in LPJ-GUESS and evaluate the resulting size structure against observations from forest inventory plots. Sensitivity studies, changing the values of difficult-to-observe parameters, such as vulnerability to mortality, can be used to give insight into how differences in the strategies of tropical trees can lead to the complex size structures found in reality.
There is scope to adapt the project to focus on particular aspects of forest dynamics or particular forest regions.
The project will contribute towards a wider development agenda working to improve our ability to simulate tree mortality (http://more.bham.ac.uk/treemort), linking with researchers across the world.
Advanced programming skills are not a pre-requisite, as the LPJ-GUESS modelling can be done without changing the underlying C++ code (only requiring some basic commands in Linux). But ability to analyse datasets using a programming-based software such as Matlab or R will be fundamental to the project, as well as a basic understanding of the concepts of ecosystem modelling.
Contact: Thomas Pugh
- Pan, Y. et al. A large and persistent carbon sink in the world’s forests. Science (80-. ). 333, 988–93 (2011).
- Bastin, J. F. et al. Seeing Central African forests through their largest trees. Sci. Rep. 5, 1–8 (2015).
- Friedlingstein, P. et al. Global Carbon Budget 2019. Earth Syst. Sci. Data 11, 1783–1838 (2019).
- Pugh, T. A. M. et al. Role of forest regrowth in global carbon sink dynamics. Proc. Natl. Acad. Sci. U. S. A. 116, 4382–4387 (2019).
- Feldpausch, T. R. et al. Height-diameter allometry of tropical forest trees. Biogeosciences 8, 1081–1106 (2011).
- Blanchard, E. et al. Contrasted allometries between stem diameter, crown area, and tree height in five tropical biogeographic areas. Trees - Struct. Funct. 30, 1953–1968 (2016).
Master thesis suggestion: Analyzing urban trees in Helsingborg with Sentinel-2 satellite data
When: as soon as possible
What: Spectral remote sensing can be used to discriminate between different types of forest. The optical characteristics of trees are determined by properties such as the canopy arrangement, and the sizes, shapes and internal structures of their leaves. Many of these properties vary between tree species, which makes it possible to map different tree species with remotely sensed spectral data. However, because many tree species have relatively similar optical characteristics, there is a high risk of confusing species, particularly if only one remotely sensed image is used.
Tree species also differ in their phenological characteristics, such as the dates of bud burst in the spring, and the change in coloration and the dropping of leaves during autumn. These phenological characteristics of trees influence their physical appearance, and can be monitored with the help of earth observation data, if the data has short revisiting intervals such as those acquired by the Copernicus Sentinel-2 satellite mission.
In order to compare the spectral reflectance of different tree species, field-collected validation data are needed. A common limitation in remote sensing studies is a lack of high quality validation data. Luckily, some cities regularly make inventories of trees in parks, along streets, and other urban areas. In Helsingborg, the municipality have stored data at the level of individual trees, including information on the species identity of several thousands of trees, and in some cases also information on the tree height and crown width. Can these data be used to increase our knowledge about the spectral characteristics of different tree species, or to monitor changes in the status of individual trees over time?
Contact: Oskar Löfgren
Master thesis: Comparison of SWAT and HYPE hydrological models in streamflow simulation in Tigris–Euphrates river basin
When: Autumn 2020 or Spring 2021
What: Streamflow in rivers represent potential water resource in a region. It is important to know how much, when and how long water is available for many applications such as water management. Unfortunately, many areas in the world are poorly gauged or ungauged with limited or no availability of streamflow data. Hydrological modelling offers a feasible way to extrapolating limited available data in space and time. Many different hydrological models have been developed and reported to have good capability of simulating various hydrological processes in certain river basins or regions. It is interesting and relevant to compare the performance of different hydrological models in the same study area. Comparison of multiple models help to identify issues for improvements and increase the confidence of simulated hydrological processes.
Two widely used hydrological models, SWAT (Soil & Water Assessment Tool, https://swat.tamu.edu/) and HYPE (Hydrological Predictions for the Environment, https://www.smhi.se/en/research/research-departments/hydrology/hype-our…) will be used and compared to simulate hydrological processes in Tigris–Euphrates river basin. The HYPE model has already been setup for this river basin. The necessary data have been collected and are available for this project.
The prospective student will (1) setup the SWAT model for Tigris–Euphrates river basin; Digital Elevation Model (DEM), land use, soil map with properties, climate data (rainfall, air temperature) are available and they need to be processed to the SWAT required format. (2) perform model calibration of SWAT and HYPE using measured streamflow; Automatic calibration is preferred to be performed, software or R packages for automatic calibration are available. (3) compare performance of two models in simulating streamflow in terms of standard metrics (e.g. Nash Sutcliffe Efficiency). (4) analyze simulated water balance components in this river basin.
The student should be familiar with ArcGIS/QGIS, basic data processing, and basic programming for data analysis and visualization. Regarding programming, experience in any of Matlab/Python/R would be great, although R would be preferred as many available packages are ready and easy to use for this project.
This thesis will be co-supervised by Dr. Zheng Duan (for SWAT modelling and analysis) and Dr. Abdulghani Hasan (for HYPE modelling and analysis) at INES, Lund University.
- Duan, Z., Tuo, Y., Liu, J., et al. (2019). Hydrological evaluation of open-access precipitation and air temperature datasets using SWAT in a poorly gauged basin in Ethiopia. Journal of Hydrology, 569, 612-626.
- Arheimer, B., Pimentel, R., Isberg, K., Crochemore, L., Andersson, J., Hasan, A., & Pineda, L. (2020). Global catchment modelling usingWorld-Wide HYPE (WWH), open data, and stepwise parameter estimation. Hydrology and Earth System Sciences, 24(2), 535-559.
MSc Project: Breakpoints in global vegetation productivity during recent decades
Gross primary production, the uptake of CO2 by the vegetation, is an essential climate variable for monitoring of the terrestrial biosphere and its response to climate change. We recently produced a novel satellite based product on global-scale gross primary production of the vegetation 1982-2015. However, the dynamics of this data set have not yet been fully analyzed. Recent advances in time-series and breakpoint analysis open new possibilities, as they allow for the detection of nonlinear trends and turning points in these data. Hence, the overarching objective of this thesis is to apply novel time-series analysis to study dynamics and possible reasons for trends and breakpoints in the vegetation productivity 1982-2015.
Contact: Torbern Tagesson
Master thesis: Monitoring wetlands in Sweden using multi-source satellite data
When: Spring 2021
What: Wetlands are important components in the Environment, see https://en.wikipedia.org/wiki/Wetland for an overview of wetlands. Timely and accurate monitoring of wetlands is very important. The Swedish Environmental Protection Agency has been working on mapping wetlands using mainly Landsat data to produce the Swedish National Wetland Inventory, and the latest version is available at https://gpt.vic-metria.nu/vmi/.
Sentinel-1 and -2 satellite missions by European Space Agency (ESA) complements Landsat satellite data with optical and synthetic aperture radar imagery data at higher temporal and spatial resolutions. Various machine learning or deep learning algorithms have been demonstrated to show great potentials in improving accuracy of satellite-based land cover classification including mapping wetlands. In addition, the powerful cloud computing platform such as Google Earth Engine makes processing of large volume satellite data much easier. It is interesting and the right time to test if using multiple-source satellite imagery data with machine learning or deep learning algorithms and Google Earth Engine platform can generate better Swedish National Wetland Inventory, which motives the announcement of this Master thesis.
The prospective student will (1) apply machine learning (or deep learning) algorithms (the algorithms will be selected based on literature review) to multi-source satellite data (particularly optical imagery data from Landsat and Sentinel-2, and SAR data from Sentinel-1) to map wetlands in Sweden; (2) perform accuracy assessment of derived wetlands and comparison with existing products including e.g. Swedish National Wetland Inventory; (3) analyse spatial and temporal changes in Swedish wetlands.
The student should be familiar with processing of satellite data, machine/deep learning algorithms, and programming (Python or R). Experience in using Google Earth Engine would be ideal.
Amani, M., et al. (2019). Canadian wetland inventory using Google Earth engine: the first map and preliminary results. Remote Sensing, 11(7), 842.
Weise, K., et al. (2020). Wetland extent tools for SDG 6.6. 1 reporting from the Satellite-based Wetland Observation Service (SWOS). Remote Sensing of Environment, 247, 111892.
Yang, X., Pavelsky, T. M., & Allen, G. H. (2020). The past and future of global river ice. Nature, 577(7788), 69-73. [the methods and Landsat data processing on Google Earth Engine are relevant and beneficial for this Master thesis, although this paper was focused on river ice]
Contact: Zheng Duan
Optimizing the locations of bike sharing stations based on spatio-temporal demand coverage
As an environmentally friendly, economical, and convenient transport mode, bikes have been considered as an effective means for those short-distance automobile trips. In recent years, bike sharing systems (BSS) have been commonly adopted in many cities around the world, which are used to solve the first- and last-mile problem, and alleviate traffic congestion and air pollution.
However, the site selection of bike sharing stations is still one of the main problems under the construction and operation of BSS. The locations of bike sharing stations determines the performance and service level of BSS.
Theoretically, the site selection of stations relies heavily on people’s cycling demand, which has been paid little attention in previous studies. Especially, the demand is heterogeneous and dynamic in time and space.
Motivated by this, the goal of thesis is to develop an approach on optimizing the locations of bike sharing stations based on spatio-temporal demand coverage. Challenges to be addressed include:
- extracting spatio-temporal demand from massive bike GPS data,
- designing a spatial optimization method based on the extracted demand information, and
- evaluating the performance of the optimization model.
A more specific introduction to the topic will be given by the supervisors upon request.
Interest in spatial data analysis and mining. Knowledge of Python is beneficial.
M.Sc. Project: Linked geospatial data
When: Spring 2022
Semantic web techniques and linked data (knowledge graphs) are increasingly used in the geospatial domain and are interesting for e.g. the next generation of spatial data infrastructure. At the department, we have conducted some research in linked geospatial data and are open for master thesis in the topic. The thesis could either be devoted technical issues (ontologies, RDF stores, etc.) or have a more applied focus.
Contact: Lars Harrie
Fragmentation of snow in collisions with graupel/hail observed in a lab experiment
The ice phase of storms is the cause of many aspects of severe weather. Freezing rain, hail and lightning from ice in clouds together cause many billions of euros of damage per year in Europe and USA. Yet the processes of ice initiation in storm clouds are still uncertain. There is evidence from aircraft observations that fragmentation of ice somehow can generate most of the ice particles in such clouds. Thus, lab experiments are required to quantify some mechanisms of fragmentation.
The prospective student will perform an experiment in our laboratory at INES to characterise one such mechanism. The student will create apparatus to observe collisions between a graupel particle grown by riming and a snow particle from by accretion of crystals using a cold box in an open-top freezer. Video imagery will be analysed computationally so as to count the numbers of fragments from snow-graupel collisions in the cold-box at various temperatures. An existing theoretical formulation will be adapted to fit the results (e.g. for application in a numerical model of clouds). The student should have an interest in the physics of materials and have experience in programming and in practical experimentation.
Contact: Vaughan Phillips
MSc Project: Generating a state-of-the-art satellite product of vegetation productivity
Given the importance of gross primary production (GPP) for monitoring of the terrestrial biosphere and its response to climate change, a consortium earth observation-based GPP products is of high societal relevance. Today, the publicly available satellite based products derives from just a few satellite sensors. In order for spatially explicit GPP to be properly assessed, it is extremely important that monitoring products are independent and based on different input data. Sentinel is a series of newly launched satellites having global coverage of reflectance in high spatial and spectral resolution, but there are still no GPP products generated from the Sentinel data. The overarching objective of this thesis is to combine information from the Sentinel-3 satellite with light use efficiency estimates from a dynamic global vegetation model to generate a state-of-the-art satellite product of GPP. The product will thereafter be evaluated against ground observations.
Contact: Torbern Tagesson
M.Sc. project: Impact of ecosystem properties of semi-arid savannas on dynamics in ground surface reflectance
The Dahra field site in Senegal, West Africa, was established as an in-situ research site to improve our knowledge regarding properties of semi-arid savanna ecosystems and their responses to climatic and environmental changes. A strong focus of the instrumental setup is to gain insight into the relationships between ground surface reflectance and savanna ecosystem properties for earth observation upscaling purposes using satellite data. This master thesis will make use of a unique in-situ data set of reflectance between 350-1800 nm and investigate how ecosystem properties of semi-arid savanna ecosystems influence the reflectance from the ground surface.
Contact: Torbern Tagesson
M.Sc. Project: Modelling long-term carbon dynamics for High-Arctic dry and wet ecosystems
The ongoing rapid warming over the Arctic has caused dramatic changes in environmental conditions (e.g. snow cover thickness and duration, active layer depth and soil moisture and temperature) and ecosystem dynamics. The carbon cycle in dry and wet ecosystems may respond to climatic warming in contrasting ways.
This project aims to elucidate the long-term dynamics of CO2 fluxes for the neighboring High-Arctic dry and wet ecosystems respectively and identify their biotic and abiotic drivers. The results will improve our understanding or prediction on how dry and wet Arctic ecosystems contribute to greenhouse gas emissions due to the present or future climate change.
The main research work will be based on an integration of a process-oriented model and fluxes measurement data sets (the method is similar to Zhang et al., 2018).
This project should not necessarily require the candidate to have advanced programming skills, but the candidate should know about ecosystem modelling and be able to make statistical analysis and plotting using Matlab or R or other similar tools.
Contact: Wenxin Zhang
M.Sc. Project: Cartography and text setting to promote urban walking
When: Spring 2022
High quality maps are indispensable for wayfinding in e.g. urban environment. Therefore, main cities (such as London in the example below) are setting up maps within the city to inform citizens and tourists with navigation information to promote urban walking. To create this high quality maps there is a need for better methods to automate the cartographic work, especially in text setting. So, if you are interested in promoting urban walk in London, NY, Tokyo and other main cities this is a master thesis for you. You should ideally be a geomatics student or LTH student or LUMA student with interest in maps and programming. The thesis is a cooperation with the company T-kartor with its head office situated in Kristianstad, Skåne, but with activities all around the world.
Contact: Lars Harrie
M.Sc. Project: Building and city models
When: Spring 2022
There is an increasing amount of 3D building models (BIM) and 3D city models. There are currently several research and innovation projects of the usage of these models in the digitalization of planning and building processes in the society, concentrating on issues such as automation of building permits, 3D cadaster issues and environmental modeling. The department is involved in several of those projects (many as part of the Smart Built Environment program – see http://www.smartbuilt.se/). We are open for M.SC. projects in several topics concerning the usage of BIM and city models connected to our projects.
Contact: Lars Harrie
Internship at Hyltemossa and Norunda Research Station (http://www.icos-sweden.se).
The Internship offers the opportunity to learn about greenhouse gases measurements within ICOS but also to get involved within field work of the various projects running at each of the Stations. The internship is organized in the course NGEA51 (https://www.nateko.lu.se/education/courses-basic/physical-geography-and…), timing of the course is flexible and can also be taken over the summer. Even though it is a Bachelor level course it can be taken during the Master as well, especially as the internship offers the opportunity to produce a data set that can later be analyzed within a thesis.
For further information contact the respective Station personnel:
Hyltemossa: michal [dot] heliasz [at] cec [dot] lu [dot] se (Michal Heliasz)
Norunda: Meelis Mölder
Master thesis work: Carbon storage and ecosystem functioning in old-growth forests
Do you want to help us understand old-growth forests in Sweden (gammelskogar)? This project is suitable on for both MSc and BSc level. It can start at any time.
We have recently produced a digital (GIS) map of old-growth forests in Sweden. In a larger long term project we aim to investigate if old-growth forests store more carbon than production forests do. In the suggested project the student would perform carbon inventory in a single or a few old-growth forests and in the surrounding managed ecosystems (forest plantations, pastures or croplands). The work would be performed in collaboration with a PhD student. Several old-growth forests are located in Skåne and in Southern Sweden, but there are sites all over the country.
Because there are multiple forests there are multiple projects, and two or more students could collaborate. Because the project involves field work the ideal candidate(s) would be willing to organize and perform field trips and measurements. The project also involves analysis of collected data and existing inventory data.
We also welcome other ideas that are related to this topic.
Please contact Anders Ahlström if you are interested.
Master thesis work: Detection and analysis of e large scale ecosystem functional relationships
Functional relationships are powerful tools to analyze large datasets, from dynamic models and from upscaled observations. The aim of the project would be to find new regions where a functional relationship between environmental drivers and ecosystem response can be found. Suitable regions vary mainly along a single environmental variable, such as water availability or temperature, but not both. That way the ecosystem response to a single environmental driver can be analyzed.
The proposed workflow involves scientific programming to identify potential regions, regions that mainly vary in one variable across space. The second step would be to compare the functional relationships of empirical datasets on ecosystem carbon cycle (GPP, NPP, biomass, soil carbon etc) as well as outputs from climate models and ecosystem models. The project therefore involves handling of large datasets, something that is common in global analysis and climate change research.
The ideal candidate has some knowledge in scientific programming and spatial data.
For more information see our previous publication on a functional relationship in Amazonia (https://www.nature.com/articles/s41467-017-00306-z)
Please contact Anders Ahlström for more information.
Master thesis work: Map and analyze pristine ecosystems in various regions
This project is suitable on for both MSc and BSc level. The project also works for E-learning program theses. Any semester, there are multiple projects that can start at any time.
There are still large uncertainties on how land use, such as forestry and agriculture affects the carbon cycle and biodiversity. A larger long term project at the department aims to further our knowledge on this by contrasting pristine ecosystems (ecosystems that are more or less natural, such as old growth forests) to surrounding ecosystems under land use. Right now we have produced a digital map (GIS map) of old growth forests in Sweden, but we are also interested in expanding the map to more countries. Data also exists for European Russia, but we have not analyzed it.
This project can therefore take many shapes, e.g.;
- Produce a map for an unmapped region. This can be done by collecting information from known sources, digitizing older maps or using remote sensing information such as aerial or satellite images to digitize known forests. Our long term aim is to build a global map, you would contribute to this.
- Analyze our already mapped old-growth forests in Sweden. There are several questions here; (a) if old-growth forests differ in terms of their topography or soil characteristics from surrounding ecosystems. This is important to know when performing paired analysis, if the old growth forest has been left unused because it is a mountain or a wetland, then the paired analysis of that forest will need to be modified. This mainly involves GIS analysis. (b) Use forest inventory data or remote sensing data to compare carbon storage between the old growth forests and surrounding ecosystems under land use.
- Perform the first analyses on old growth forests in European Russia, all of the above types analysis can be performed.
- A topic of your own that uses our new old growth forest map.
The student will work with our project on these questions. There are many things to do, the projects can be varied to focus on carbon cycle, ecology or technical GIS / remote sensing aspects.
The scope of the project and analysis can be adjusted to the type of thesis (bachelor or master) and it is also possible to divide the work between multiple students. The project is not limited to the allocated time allocated for the thesis; it could start earlier and continue after. Multiple students are also welcome, working in groups or focusing on different regions.
Please email Anders Ahlström if you are interested.
Charge separation in ice-ice collisions in the absence of liquid: simulations of published lab experiments
When: any time
What: Lightning in storms is caused by electric fields arising from charge separation in re-bounding ice-ice collisions. The project aims at evaluating laboratory observations of charge separation in ice-ice collisions in the absence of liquid. This is a weaker form of charging than that usually studied but may be significant owing to the prevalence of ice-only cloud in storms.
The prospective student will simulate the ice crystal growth and collisions in a specific experiment observing charging that was performed years ago and described in a published paper in 2016. The student will create a simple model to replicate the experiment and then do variational analysis to deduce a formulation for the charge separation that can be applied in cloud models. The student should have an interest in computer modelling and programming (Fortran or C) and should be familiar with a LINUX-based operating system.
Contact: Vaughan Phillips