Here are listed some possible themes for a master or bachelor thesis. Own proposals are welcome. For more topics visit the German version of this site!
Digital elevation Models (DEMs) have been used as terrain surrogates in order to derive topographical parameters for different applications including hydrological modeling and soil erosion modeling. With advances in remote sensing technologies, high resolution LiDAR and RADAR data has become available, which have markedly improved the spatial resolution of DEMs which can now be obtained at sub-meter scales. As against that the most widely used SRTM and ASTER GDEMs have 90m and 30m spatial resolutions respectively. Objective: To analyze whether SRTM or GDEM dataset is more representative of a terrain model or a surface model and consequently to analyze whether it can be used reliably to extract topographical information related to surface characteristics for erosion and hydrological modeling. Methods: Processing of DEMs in ArcGIS, terrain analysis in ARCGIS and statistical analysis using Rstatistics.
Detecting dynamic changes in vegetation patterns in areas of semi-natural Vegetation in southern Chile
The objective of the Master-Thesis is to classify a series of historical aereal photographes due to vegetation cover and to analyse temporal changes in vegetation patterns. These information should be used to identify areas of progressive degradation of forest to shrubland, areas of forest succession due to abandonment, and aereas with a dynamic conversion between shrubland and human-induced types of land cover, in particular pastures.
Description: Multispectral satellite images of tropical forests are often difficult in use due to frequent and heavy cloud coverage. You will produce a sequence of preprocessing steps for common and most recent satellites which provide best possible data for further interpretation. The processing includes techniques like cloud masking or radiometric and atmospheric correction. The study sites are located in the Democratic Republic of Congo and Fiji.
Description: The classification of tropical forests is an important basis to derive further information like biomass or carbon sequestration. You will develop automated or semi-automated methods using image processing software to classify forests on our study sites in the Democratic Republic of Congo and Fiji. Knowledge of tropical forests is therefore of advantage.
The mapping of forest biomass is of great interest for several reasons. Forest biomass plays an important role in the development of global Carbon-cycling models as well as for regional bioenergy production. In the proposed thesis the student will develop species-specific biomass models based on previously-existing biomass formulas. The remote sensing data will be used to derive height and density information of the forest stands as well as tree species classifications. This information serves as input to the abovementioned existing biomass formulas on single tree level and will be then extrapolated to stand level.