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.
Landskapets förändring i Båstad över tid
Note: this job requires Swedish language proficiency.
Projektbeskrivning – Landskapets förändring i Båstad över tid
I Båstad ser man en utveckling mot att allt mer jordbruksmark tas i anspråk för bebyggelse. Detta gäller både i tätortsnära bebyggelseutveckling, inom detaljplan, och på landsbygden där det lämnas positiva förhandsbesked för ny bebyggelse.
Att över tid se hur landskapet har förändrats och hur det kan komma att förändras i framtiden. Resultatet kan användas för information och utbildning av tjänstemän och förtroendevalda.
Använda sig av tillgängliga ortofoto från olika årtal för att med fjärranalys komma fram till ett resultat.
Examensarbetet kan ha flera olika utgångspunkter för att belysa problematiken; ekologiskt, ekonomiskt, näringsliv eller teknik.
- Hur har landskapet förändrats sedan 1970-talet? Förändringar i förhållandet mellan öppen mark (åker- och betesmark), skog och bebyggelse. Landskapets fragmentering och dess påverkan på spridningskorridorer.
- Hur mycket jordbruksmark har bebyggts sedan 1970-talet?
- Vad händer med jordbrukslandskapet om nuvarande exploatering fortsätter?
- Varför ska inte mer jordbruksmark tas i anspråk för bebyggelse?
- Hur mycket bebyggelse ”tål” jordbruksmarken?
- Vilken påverkan har bebyggelsen haft på biologiskt mångfald och biodiversitet?
- Finns det alternativa utvecklingar och hur ser dessa alternativen ut?
- Finns det någon jordbruksmark kvar om 50 år?
- Hur värnar man naturens attraktionskraft?
- Sätt in Båstads agerande i ett nationellt perspektiv och den nationella livsmedelsförsörjningen.
- Exploateringens påverkan på livsmedelsförsörjningen?
- Är tillväxten bra för Sverige? Var går gränsen för hållbar tillväxt?
- Kan man använda GIS för att reglera bostadsbyggande på åkermark?
Catharina Arehög, bygglovschef, 0431-774 90, g [at] bastad [dot] se">catharina.arehög [at] bastad [dot] se
Annika Jern, geodatachef, 0431-776 41, annika [dot] jern [at] bastad [dot] se ()
Helena Elvén Eriksson, Institutionen för Naturgeografi och Ekosystemvetenskap (INES) & Lunds universitets GIS-centrum, 0707 49 50 67, helena [dot] elven_eriksson [at] nateko [dot] lu [dot] se ()
Karin Larsson, Institutionen för Naturgeografi och Ekosystemvetenskap (INES) & Lunds universitets GIS-centrum, 046-2224093, karin [dot] larsson [at] nateko [dot] lu [dot] se
Internships are at all levels, but most at the master's and PhD level. Many are lab places but there are also other opportunities such internships at Paris-Saclay's international office in Paris.
If you are interested, please send an email to eugloh[at]er.lu.se
Internship/bywork as Forest data analyst at Katam Technologies
What: Katam Technologies is a team of ambitious startup entrepreneurs who want to revolutionize the forest industry through game breaking technology. They deliver high precision data to the forest sector supporting operational forestry decisions as well as long-term strategic decisions.
Forest data is collected using various tools such as smartphone, drones, and other data sources and transformed into valuable decision-making facts for our customers around the world. This leads to more optimal usage of the global forest land that benefits both society and the climate.
They are now looking for two internships to strengthen their forest data analysis team. For more information see PDF:
Jobb på Länsstyrelsen
Länsstyrelsen har ofta jobb, internships och examensarbeten som handlar om t.ex miljöövervakning, naturvård och GIS. Listan på lediga jobb finns här:
BSc internship or project work: GIS mapping at Ekologigruppen
Ekologigruppen is looking for someone to carry out erosion risk mapping over a suitable catchment area in Skåne according to the ecologist group's model both in Mapinfo and in ArcGIS and compare the results to see if the programs' algorithms differ significantly. Contact wosel [dot] thoresen [at] ekologigruppen [dot] se (Wösel) at Ekologigruppen.
Volunteer and internship opportunities for students of Geography and Environmental Science
Offered by GoEco, note that you may need some funding for their activities.
Internship in research groups abroad
Are you considering a career in research? As a current student at Lund University, you can do a research internship at one of the LERU universities that is part of the STREAM project programme, on a full-time basis, for anything from one month up to a whole semester. STREAM (STudent REseArch Mobility) is a project aiming to facilitate research exchange opportunities for current students at institutions within LERU (the League of European Research Universities).
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. They also organise case study workshops and courses.
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)
Undergraduate thesis projects: Elemental analysis of atmospheric
particles at Hyltemossa forest site through X-ray fluorescence
You'll find all information here: Xact_Exjobb_2022_Hyltemossa.pdf (PDF, 75 kB).
MSc project with focus on deforestation and remote sensing
When: fall 2022
In 2016 the historic peace accord between the Colombian government and the Revolutionary Armed Forces of Colombia (FARC), had no strong mechanism of managing changes to land use and the environment. Since the end of a 60-year conflict in Colombia, large areas of forest have been rapidly converted to agricultural uses, most recently cattle ranching, suggesting the peace agreement presents a threat to the conservation of the country’s rainforest. As a result, deforestation inside Colombian Protected Areas (PAs) and the surrounding buffer areas has accelerated with the onset of peace.
The extensive cattle ranching activities are a major land use in the Amazonian region of Colombia. Even though the livestock sector is responsible for a large part of the environmental footprint of anthropogenic activities in Colombia, it offers significant socioeconomic benefits to rural populations. Therefore, the promotion, restriction or exclusion of extensive livestock practices must be analysed in the socio-ecological context in which this activity occurs.
For this master thesis project, you will collaborate with the analysis of remote sensing data, to verify and quality check the data, to compare with other data sources and true geolocation of the data. The scope is to identify and map the area and number of deforested hectares caused by the presence of cattle ranching in the tropical savannas of Yarí, which are surrounding the biggest tropical forest protected are in the world, the Chiribiquete National Natural Park (NNP), located in the northwest territory of the NPP which has been declared as the Colombian arc of deforestation.
It is recommendable if your background is in remote sensing and GIS. The results will lead to a high impact international publication.
If you are interested, please contact lars [dot] eklundh [at] nateko [dot] lu [dot] se (Lars Eklundh) and jesica [dot] lopez [at] cec [dot] lu [dot] se (Jesica López).
Analysis of organic matter composition using fluorescence
What: MSc thesis
When: autumn 2022 and/or spring 2023
Optical characterizations of colored dissolved organic matter, including fluorescence Excitation-Emission Matrix analysis (EEM), offers a breadth of information about the source, bioavailability, diagenetic state and chemical composition of dissolved compounds in both soil and water. It is an established tool to study carbon dynamics in response to changes in vegetation, hydrology, cryology and other factors.
The aquatic biogeochemistry group at INES is currently generating more EEM samples than we have time to analyze using our “Aqualog” instrument. This brings a golden opportunity for Master’s projects to utilize these samples to address links between organic matter optical characteristics (EEM) and e.g. the cycling of organic carbon and nutrients.
Samples have been collected from natural streams, soils with different fire history, and experiments in soils, wetlands and coastal waters. There is up to ~1000 frozen/conserved or recently collected samples that can be analyzed and used for a wide range of thesis topics that relate to organic matter cycling or water quality.
Contact us to discuss possibilities.
Contact: Martin Berggren
MSc Project: Arctic amplification in the past and future
What: In the recent decades, the Arctic has warmed more than twice as fast as the global average, a phenomenon known as Arctic amplification. This amplified Arctic warming is associated with drastic shifts in the Arctic climate system, including decreased sea ice extent and changes in the carbon cycle, and has further been linked to more frequent extreme weather in the mid-latitudes. Despite the serious ramifications of Arctic amplification, many things are unknown about the phenomenon.
In this Master’s project you will use observations and/or model output to study Arctic amplification. Here are some examples of questions to investigate:
- How has Arctic amplification varied in the past? Do different observational datasets and model simulations agree?
- How do models project that Arctic amplification will change in the future? How does it depend on the climate forcing?
- Arctic amplification is usually defined as the ratio of Arctic temperature change to the global or hemispheric temperature change, which requires a spatially complete temperature dataset. Is it possible to find a simpler definition that only requires observations at a few points?
- How do different definitions of Arctic amplification affect the interpretation of its variations and trends?
You are of course more than welcome to formulate your own research questions based on your interests.
This project will train you in analyzing large datasets, interpreting observations and model results, and applying statistical methods to understand climate change. Basic knowledge about scripting languages like Python or MATLAB is helpful, but more importantly you should be willing to learn how to use such tools to analyze data and visualize results.
Please contact me if you are interested. If you want to learn more about Arctic amplification and the current state of research, this preprint provides a good starting point: https://doi.org/10.31223/X5VS6C
Contact: Hans Chen
MSc Project: Projected future climate zones and their uncertainties
What: The Earth can be divided into different climate zones depending on the regional climate. One of the most commonly used climate classifications is the Köppen classification, which uses monthly temperature and precipitation to classify the climate into five major types and several minor subclasses. Past studies have shown that the dry climate type has expanded and the polar type has shrunk under anthropogenic climate change, and these trends are projected to continue into the future according to climate models. However, there is still a lack of understanding of the uncertainties of these changes.
In this Master’s project you will use climate model projections to investigate the changes in the Earth’s climate zones. Some questions that could be addressed include:
- How well do different models agree? How do they compare with observations in the recent decades?
- What are the major uncertainties in the projections – uncertainty due to the use of different models, different climate forcings, or different initial conditions?
- Are the uncertainties in future climate zones related to uncertainties in another variable, for example the degree of global warming? If so, is it possible to reduce the uncertainties using a so-called “emergent constraint” based on current observations?
You are of course more than welcome to formulate your own research questions based on your interests.
In this project you will learn how to work with model output, classify the climate according to different criteria, derive uncertainty information from ensemble/multi-scenario/multi-model simulations, and interpret trends and variations. Basic knowledge about scripting languages like Python or MATLAB is helpful, but more importantly you should be willing to learn how to use such tools to analyze data and visualize results.
Please contact me if you are interested. If you want to learn more about the Köppen climate classification, see this website: http://hanschen.org/koppen
Contact: Hans Chen (https://www.nateko.lu.se/hans-chen)
Estimating biomass and phenology in African Rangelands using Earth Observation
Background: INES (Lars Eklundh and Jonas Ardö) recently got a contract for a project (RAMONA, staring in December 2021) with the European Space Agency (ESA). This project aims to develop and apply methodology to assess grazing resources in African Rangelands using (mainly) data from the Sentinels (Sentinel 1,2, and 3 in this case). The project includes assessment of rangeland type and extent, herbaceous biomass, biomass anomalies and rangeland phenology.
Thesis topics: As a party of this project we provide opportunity for 2-3 master thesis projects during 2022 (both spring an autumn) focusing on
- estimation of herbaceous rangeland biomass,
- assessment of rangeland phenology and
- quantification of biomass anomalies.
In the document below you will find descriptions of these three topics from the original project plan. Based on information below we will define suitable topics, subtopics, study regions, study periods etc. and develop testable hypotheses, in cooperation with interested students.
When: Spring semester 2022 (potentially autumn semester 2022 as well).
Contact: Jonas Ardö, jonas [dot] ardo [at] nateko [dot] lu [dot] se, 072-2025028 or Lars Eklundh, Lars [dot] Eklundh [at] nateko [dot] lu [dot] se for more information
Bark Beetles Attack predictive risk mapping using machine learning
This master thesis topic is in line with a project related to monitoring and risk mapping of Bark Beetle attacks in Southern part of Sweden.
The aim of this master thesis is to model the association between Bark Beetle attacks with the environmental factors using Machin Learning. The contribution of the study is to study how spatial auto-correlation and spatial errors can be integrated into the ML modeling and if the new developed model increases the accuracy of Bark Beetle attack prediction.
The topic is suitable for students who like to research and learn more about Geo-data Science and Machin Learning. A good knowledge of Python programming is required for the implementation of the model, while available ML libraries will be used.
Contact Ali Mansourian if you are interested in the topic.
Master thesis proposal: Garland-shaped vegetation patterns
Analyzing Alpine fine scale vegetation pattern with respect to slope and aspect
While vegetation typically grows as a mat covering the ground, sometimes it develops specific geometric patterns like the wave forms that can be seen in the image below, which are called garland-shaped grass patterns (‘Girlandenrasen’). This particular pattern is assumed to be generated by reoccurring thawing and freezing cycles together with the steep slopes.
It is generally assumed that steeper slopes will lead to larger waves of vegetation. In this thesis you will perform an analysis of what causes the wavelength and will try to generate a model of these particular vegetation patterns. Currently a dataset has been collected in the Swiss Nationalpark comprising of high resolution photos from several locations as well as GPS coordinates which will allow to generate a 3D model of the area as well as an orthophoto in which the vegetation can be classified.
Additional data can be collected within the project if this is of interest.
Contact: Veiko Lehsten
MSc project: Chanterelle GIS - where are they?
Chanterelles are a common and popular edible fungus in many countries. In Sweden, it is perhaps the mushroom that is most sought after. Increasing the probability of finding chanterelles would be positive for many mushroom pickers.
To investigate whether searching for chanterelles can be made more efficient using geodata and climate data.
The first step is to characterize the environments (both in time and in space) where chanterelles grow, thrive and are picked through to collect data on existing "chanterelle places", theory from mushroom literature etc.
The second step is to use existing geodata (Lantmäteriet, skogsstyrelsen, SLU with several suppliers) and climate data (SMHI) to identify areas with an increased probability of finding chanterelles based on these geodata. This can be done with various overlay operations, fuzzy-GIS methods or deep learning (however, this requires large amounts of training data).
In the third step, Chanterelle-GIS performance is evaluated empirically through a number of standardized mushroom picking sessions, with and without the support of Chanterelle-GIS.
When: Autumn 2022 (should include the mushroom season)
Contact: Jonas Ardö
MSc project: Spruce bark beetle - remote sensing and/or modelling
The hot drought in 2018 triggered a large spruce bark beetle outbreak in south Sweden. The outbreak has killed several million m2 of spruce trees and is still ongoing. We have recently started a project to develop methods to monitor spruce bark beetle attacks with Sentinel-2 data.
In the project we have work packages focusing on:
- studying risk factors for bark beetle outbreaks,
- detection of bark beetle attacked trees in Sentinel-2 data and
- modelling of bark beetle phenology.
We welcome master students to work in the project and have different suggestions for thesis topics. The thesis can be focusing on remote sensing, how can we detect bark beetle outbreaks in remote sensing data?
It is also possible to write a thesis directed towards modelling e.g. bark beetle phenology or with a focus on management strategies. A thesis can also be more related to GIS with a focus on risk factors for outbreaks.
Contact: Per-Ola Olsson
Master thesis: 3D city models - the "new" CityGML version 3.0
The number of 3D city models in the Worlds is growing and the most common standard for 3D city models is CityGML. A new version, CityGML 3.0 (Conceptual model) was recently approved as an official OGC Standard with several changes compared to CityGML 2.0 that opens up for interesting studies. Some changes are that the core-, building- and transportation modules are updated and that a module for versioning of city models is introduced. One major difference compared to CityGML 2.0 is the space concept that is used to "build" the objects in the city model. Spaces can be either physical spaces or logical spaces. For example the physical parts of a building (building, building parts) consists of physical spaces but there is also a possibility to divide the building into logical spaces based on e.g. ownership or function. One thing to study is if the logical spaces can be used to divide a building into different (logical) parts based on the function. This is something that will be tested in 2022 by Lantmäteriet for a new national specifications for buildings.
There are also other aspects of CityGML 3.0 that can be studied, related to transportation and versioning of city models.
Contact: Per-Ola Olsson
Will elevated CO2 help us feed the world?
An increasing global population, combined with the effects of climate change, are expected to put extreme stress on the global food system over the coming decades. One piece of good news, amidst the bad, is that elevated atmospheric carbon dioxide concentrations have been shown in field experiments to increase crop yields substantially. A big challenge for scientists is to take this information from experiments and translate it to projections of yield change across whole regions or the globe. Over the last few years, we have developed a novel process-based crop model designed to do exactly this scaling. However, initial projections of future yield with this model appear extremely optimistic and to better understand if they are realistic, careful evaluation of the model against observations is required.
In this Master’s project you will work with the latest development version of the LPJ-GUESS crop model, running simulations of historical and potential future crop yields, evaluating them against observations and investigating the reasons behind the simulated strong increases in yield. You will receive training in running a state-of-the-art scientific model and in data processing. In the process you will also learn about the processes that govern how crop yield is likely to change in the future. Your research will contribute towards improving the LPJ-GUESS crop model, itself an international collaborative effort between institutions in Sweden and Germany, and which contributes to a range of international assessments on the future food system (Alexander et al., 2018; Rabin et al., 2020).
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. Key references: Rosenzweig et al. (2014), Olin et al. (2015).
Contact: Thomas Pugh
Can we simulate the giant trees of the rainforest?
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 (Pan et al., 2011). Much of the carbon that they hold is stored within the trunks of the largest trees (Bastin et al., 2015). 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 (Pugh et al., 2019; Friedlingstein et al., 2020). We have updated LPJ-GUESS with a novel new scheme that allows it to simulate tree size structure within a forest in a simplified way. What is unclear is whether the updated model is actually able to successfully capture the dynamics and structure of real forests.
Your challenge in this project will be to use observations of forest structure from across the tropics to evaluate this new version of LPJ-GUESS and explore its behaviour. 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.
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.
How do forests respond to drought?
What: When trees die, they stop absorbing carbon. Tree mortality is increasing and linked in parts to droughts, driven by climate change (Hartmann et al., 2018).
With more trees dying, less carbon will be absorbed, exacerbating climate change impacts (such as droughts!) - and more trees will likely die.
More accurate simulations on forest responses to drought, are urgently needed to decrease uncertainty in climate change projections. However, key questions on mechanisms that govern tree death remain unknown to ecosystem modellers.
Until now, most models have lacked of one of the crucial processes that govern tree mortality - failure of the tree’s hydraulic system.
Our research group has addressed this issue and recently added this crucial process into the state-of-the-art LPJ-GUESS model. However we don’t yet know whether the model is able to provide improved representations of larger scale key ecosystem processes such as primary productivity and evapotranspiration.
We need someone to evaluate the new model against observations. Your role in this project will be to use observations from eddy-covariance flux towers in the FLUXNET network to evaluate this new version of LPJ-GUESS and explore its behaviour. You will be able to explore how different functional strategies employed by trees affect the function of the forest. There is flexibility to focus on a world region of your choice, dependent on the availability of suitable FLUXNET data.
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.
Co-design your own thesis project on forests using modelling or data analysis?
What: We have available a range of possibilities for projects related to understanding the form and function of the world’s forests, from local to global scale. Possible techniques include:
- Process-based ecosystem modelling using our state-of-the-art global vegetation model, LPJ-GUESS.
- Empirical analyses of observations of trees from forest research and inventory plots.
- Inference of ecosystem properties and behaviour from remote-sensing products.
Contact: Thomas Pugh to discuss your interests and match to possibilities.
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
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
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)
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
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
Understanding spatiotemporal dynamics of E-scooter sharing in different urban contexts: A tale of Stockholm and Lund
In recent years, E-scooter sharing services have been commonly adopted in many cities around the world, which are supportive to alleviate traffic congestion and greenhouse gas emissions. As an environmentally friendly, economical, and convenient transport mode, E-scooter sharing services have been considered as an effective way for those short-distance trips.
The existing studies on micro-mobility are still focused on docked and dockless bike-sharing systems. Understanding spatial and temporal dynamics of E-scooter sharing services, especially in different urban contexts, has been paid little attention. Considering that E-scooter sharing mobility patterns are dramatically influenced by the built environment (e.g. land use, public transportation, road network) in urban context, it is significant to understand spatiotemporal dynamics of E-scooter sharing in different urban contexts.
Motivated by this, the goal of the thesis is to explore and understand the spatiotemporal dynamics of E-scooter sharing in different urban contexts by implementing a case study on Stockholm and Lund.
Challenges to be addressed include:
- Exploring spatiotemporal patterns of E-scooter sharing services from massive E-scooter trip data.
- Quantifying the urban built environment characteristics by collecting the related geographic data.
- Examining the spatial associations between E-scooter sharing ridership and the built environment characteristics.
The student should be familiar with spatial data analysis and mining. Programming skills (Python or R) are beneficial.
A more specific introduction to the topic will be given by the supervisors upon request. We are open for MSC projects in several topics concerning spatiotemporal analysis of micro-mobility towards smart cities.
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
Three positions at the Centre for Biogeochemistry in the Anthropocene, an interdisciplinary centre that involves the departments of biosciences, geosciences and chemistry at the University of Oslo: https://www.mn.uio.no/cba/english/
- PhD in microbial ecology: https://www.jobbnorge.no/en/available-jobs/job/219766/phd-research-fellow-in-microbial-ecology
- PhD in aquatic carbon cycling in the boreal region: https://www.jobbnorge.no/en/available-jobs/job/219767/phd-research-fellow-in-biogeochemical-processes-govering-boreal-c-cycling
- PhD in the modelling of soil carbon processes: https://www.jobbnorge.no/en/available-jobs/job/219806/phd-research-fellow-in-modelling-of-carbon-cycling-in-boreal-soils