Thesis supervision
Ideas for topics
Environmental monitoring of:
- Forest disturbance plots - Interactions biophysical parameters in the context of management and reforestation
- Interaction of snow dynamics and vegetation development
- Renaturation measures in rewetted peatlands - Interrelationship water level and vegetation development
- Forest fire areas - vegetation and development of deadwood
Methods:
- Remote sensing and GIS
- Sensors: Microclimatic measurements, Wireless Sensor Networks, Remote Sensing (optical/thermal/lidar) with satellites & UAV
Actual topics
There are currently no open topics.
Bachelor theses
Winter term 2023/24: UAV-based monitoring of a rewetted peatland with thermal imagery and ground reference measurements.
Winter term 2023/24: Assessment of the reforestation potential in standing deadwood using a Wireless Sensor Network to measure the Fraction of actual Photosynthetically Active Radiation (FAPAR). --finished
Summer term 2923: Detection of thermal anomalies in thermal UAV images by analysis and interpretation with Python. --finished
Summer term 2023: Assessing spatio-temporal consistency of Sentinel-2 and Sentinel-3 FAPAR (fraction of absorbed photosynthetically active radiation) products and validation with DHP (digital hemispherical photography) - a case study in the southern Harz mountains. --finished
Winter term 2022/23: NDVI comparison of Landsat-8 and Sentinel-2-data based on land use classes in the Harz region --finished
Winter term 2022/23: Characterization of microclimatic differences using high-resolution UAV data on forest disturbance plots in the Southern Harz mountains --finished
Summer term 2022: UAV-based mapping of succession on forest calamity areas in the southern Harz --finished
Winter term 2021/22: GIS-based risk assessment of site-specific water budget under extreme rainfall events – a case study in Mosbach, Thuringian Forest (cooperation with P. Koal, FFK Gotha/ThüringenForst) --finished
Master theses
Summer term 2024: Remote sensing analysis of spatial variability in European beech vitality in the Harz mountains during drought conditions in 2018 - 2022.
Winter term 2023/24: Quantitative vegetation analysis of biophysical variables with high-resolution remote sensing on forest disturbance plots in the Southern Harz Mountains.
Winter term 2023/24: Monitoring forest disturbance plots in the Southern Harz mountains – a comparison of Sentinel-2 and UAV-derived FCOVER.
Winter term 2023/24: Monitoring of succession on forest disturbance plots using and validating Sentinel-2-derived biophysical variables.
Winter term 2023/24: Assessment of post-fire standing deadwood dynamics in the Harz National Park with UAV lidar and digital hemispherical photography. --finished
Summer term 2023: Towards an automated workflow for assessing effets of forest disturbance on land surface temperature in low mountain ranges of Central Germany using GEE and the Landsat archive. --finished
Winter term 2022/23: Assessing accuracy of Sentinel-2 derived LAI time series with direct LAI measurements and hemispherical photography in a beech forest stand in the context of actual drought phenomena --finished
Winter term 2021/22: Monitoring of multitemporal changes in Land Surface Temperature on degrading forest stands in the Southern Harz region based on Landsat8 satellite imagery --finished
Summer term 2021: Comparison of biophysical products of Sentinel-2 for the detection of changes in the spruce and beech stands in the southern Harz --finished
Summer term 2021: GIS based change detection analysis in beech and fir forest stands - impact assessment of environmental and location factors using forest stands in Northern Thuringia (Germany) as an example --finished
Summer term 2021: Vitality monitoring of beech-dominated forest stands with varying forest management intensity from Sentinel-2 images and laser scanning --finished
Summer term 2021: Spatiotemporal patterns of forest change from Sentinel-2 imagery in Thuringia between 2017 and 2021 and their relationchips to forest site factors (cooperation with Dr. A. Tischer, Geography/FSU Jena) --finished
Summer term 2021: Machine learning based mapping of forest types based on scikit-learn by using random forest and gradient boosting - a comparative study --finished