A5028709413- 3D Surveying and Cultural Heritage
- Remote Sensing and LiDAR Applications
- Robotics and Sensor-Based Localization
- Geodetic Measurements and Engineering Structures
- GNSS positioning and interference
- UAV Applications and Optimization
- solar cell performance optimization
- Inertial Sensor and Navigation
- Species Distribution and Climate Change
- Chalcogenide Semiconductor Thin Films
- Solid-state spectroscopy and crystallography
- Remote Sensing in Agriculture
- Land Use and Ecosystem Services
- Calibration and Measurement Techniques
- Ecology and Vegetation Dynamics Studies
- Impact of Light on Environment and Health
- Rangeland and Wildlife Management
- Hydrology and Sediment Transport Processes
- Soil erosion and sediment transport
- Forest Ecology and Biodiversity Studies
- Hydrology and Watershed Management Studies
Federal Institute of Hydrology
2020-2023
University of Bayreuth
2017
Riparian zones fulfill diverse ecological and economic functions. Sustainable management requires detailed spatial information about vegetation hydromorphological properties. In this study, we propose a machine learning classification workflow to map classes of the thematic levels Basic surface types (BA), Vegetation units (VE), Dominant stands (DO) Substrate (SU) based on multispectral imagery from an unmanned aerial system (UAS). A case study was carried out in Emmericher Ward river Rhine,...
Up-to-date information about vegetation types and hydromorphological structures features are essential for the management of waterways. They e.g. used monitoring reporting riparian statuses their changes after river restoration consequently, numerous man-days spent on field surveys. To allow an effective survey hydromorphology in large or even inaccessible areas, a data acquisition processing workflow is being developed complementing in-situ methods with remote sensing techniques. This part...
Sustainable management of riparian zones requires detailed spatial information about vegetation and hydromorphological properties.Uncrewed aerial systems (UAS) or gyrocopters equipped with multispectral cameras yield imagery small to intermediate scale areas.Machine learning classification workflows (object based, random forest) including additional geodata trained in-situ data allow map classes substrate types different level detail.A case study was carried out in a floodplain area along...