Thesis subject
MSc thesis topic: Understanding Land Changes: Uncovering the Drivers of Landscape Transformation
With climate change becoming an urgent global challenge, tracking changes on Earth's surface is more important than ever. Understanding how land is transforming—such as forests turning into urban areas or wetlands drying up—is crucial for identifying the causes (natural or human-made) and making informed decisions for climate adaptation.
With advancements in Earth Observation technology, we can now monitor land changes with incredible detail. National and regional land cover change maps provide valuable insights into how landscapes are evolving. However, the next crucial step is not just tracking these changes but understanding why they occur.
Some land changes, like urban expansion, are clearly human-driven. Others, such as wetland degradation or water body expansion, require deeper investigation. Are these shifts caused by climate variations, human activities, or a combination of both? Identifying these drivers is essential for developing sustainable land management strategies and climate policies.
Climate variations can influence land transitions through changes in precipitation, air temperature, and soil moisture, leading to shifts in vegetation, water availability, and land cover. On the other hand, human activities such as infrastructure development, agricultural expansion, and urban growth are key drivers of land conversion and environmental degradation. Additionally, fire plays a significant role in land transitions, contributing to forest loss, grassland dynamics, and wetland degradation, whether through natural occurrences or human-induced burning.
This research will focus on quantifying land transitions and identifying their underlying causes using geospatial datasets. By integrating land use/land cover (LULC) maps with other geospatial data and in-situ data, we will analyze patterns of change and attribute them to specific drivers. The primary study area is Uganda with the possibility of including other regions based on data availability.
Objectives
- Quantify land transitions based on existing LULC maps and evaluate their reliability
- Identify relevant potential drivers of land transitions
- Relate potential drivers to land transitions
Requirements
- Geodata processing (geoscripting, geotools)
- Statistical skills (e.g. using R or python) or strong motivation to learn it.
Literature
- Remote sensing of land change: A multifaceted perspective
- Lambin et al, 2001, The causes of land-use and land-cover change: moving beyond the myths.
- Global land use transitions and their drivers during 1960-2019.
- Driving Forces behind Land Use and Land Cover Change: A Systematic and Bibliometric Review.
- Analyzing the extent and drivers of land use/land cover change in Southwestern Ethiopia