Master's Thesis Project Topics

Mapping the ecological footprint of wind-energy expansion

Renewable energy is central to reducing greenhouse-gas emissions and achieving climate-neutrality targets. However, wind-energy development also creates local and regional pressures on ecosystems. Beyond the land directly occupied by turbines, associated infrastructure—including access roads, construction areas and transmission facilities—may cause vegetation loss, deforestation, habitat degradation and landscape fragmentation. Understanding these ecological footprints is essential for planning wind-energy expansion while minimizing risks to biodiversity.

This thesis will investigate the spatial and temporal expansion of wind-energy infrastructure between 2017 and 2026 in a selected study region. The student will use an algorithm (Global Renewables Watch) developed by the Microsoft AI Team together with Sentinel-2 satellite imagery and other geospatial datasets to identify wind turbines, estimate their construction years, and map associated access-road development.

The student will then quantify the ecological footprint of this expansion by assessing land-cover conversion, vegetation loss and habitat fragmentation around newly constructed turbines and roads. Depending on the student's interests and data availability, the project may also examine whether wind-energy infrastructure overlaps with forests, protected areas, important habitats or other biodiversity-sensitive landscapes.

The project will provide practical experience in remote sensing, GIS, time-series analysis and environmental-impact assessment. It is particularly suitable for a motivated student interested in renewable energy, biodiversity conservation and spatial data analysis. Experience with GIS, Google Earth Engine, Python or remote-sensing data is advantageous, but the precise analytical workflow will be developed together with the supervisors.

Supervisors: Zhanzhang Cai, Hongxiao Jin and Zheng Duan
Project period: 2027
Number of students: 1–2, each working on a different study region

Assessing landscape changes associated with solar PV expansion

What kinds of land are being converted into solar farms, and how does vegetation change after development? Utility-scale solar photovoltaic (PV) facilities contribute to the transition away from fossil fuels, but their land requirements raise important questions about habitat conservation and competing land uses. Their ecological footprint depends on both the landscapes they replace and how sites are developed and managed.

In this thesis project, the student will reconstruct the expansion of solar farms in a selected study region using a tool developed by Microsoft’s AI team (Global Renewables Watch), satellite imagery and complementary geospatial data. The work will involve mapping solar-farm boundaries, estimating construction years and identifying associated infrastructure, including access roads.

By comparing conditions before and after construction, the student will determine which land-cover types have been converted and assess vegetation changes within and around solar farms. The analysis may also explore habitat fragmentation or the distribution of solar development across agricultural land, grasslands, forests and biodiversity-sensitive areas. The aim is to provide evidence that can inform more environmentally sensitive siting of future solar projects.

Students interested in land-use change, vegetation monitoring and the environmental dimensions of solar energy are encouraged to apply. The project combines AI-assisted mapping with GIS and satellite time-series analysis. Experience with GIS, Google Earth Engine, Python or remote sensing is helpful, and the specific research focus will be tailored to the student’s interests with supervisory support.

Supervisors: Hongxiao Jin, Zhanzhang Cai and Zheng Duan
Project period: 2027
Number of students: 1–2, each working on a different study region

Mapping submerged cultural landscapes: A century of hydropower development in northern Sweden

Hydropower has supplied Sweden with low-carbon, dispatchable electricity for more than a century. At the same time, dams, reservoirs, and water-level regulation have profoundly transformed river valleys in northern Sweden. Settlements, travel routes, fishing and harvesting areas, archaeological remains, and culturally significant landscapes—including landscapes used by Sámi communities—have been submerged, fragmented, or otherwise altered.

This thesis will reconstruct and quantify cultural-landscape changes associated with one selected hydropower reservoir in northern Sweden. The student will integrate historical maps and documents, aerial photographs, satellite imagery, elevation data, hydropower records, and registered cultural-heritage sites within a GIS and remote-sensing framework.

The study will:

• reconstruct the landscape before reservoir development;
• estimate the former terrestrial area affected by inundation and water-level regulation;
• identify affected settlements, routes, cultural remains, and land-use areas; and
• assess how the surviving cultural landscape has become fragmented or disconnected.

Particular attention may be given to Sámi cultural landscapes, including historical settlements, reindeer-migration routes, fishing and harvesting areas, and other places associated with traditional land use. Where relevant, this component will be developed through respectful engagement with the appropriate Sámi community and careful treatment of culturally sensitive information.

Requirements: Proficiency in GIS; an interest in historical landscape reconstruction and remote sensing; ability to work with historical Swedish-language sources; and willingness to engage respectfully with local Sámi communities and other relevant stakeholders.

Supervisors: Per-Ola Olsson, Hongxiao Jin, and Zheng Duan

Project period: 2027

Number of students: 1