Remote Sensing Technology Institute
Area of research:
Scientific / postdoctoral posts
At the Remote Sensing Technology Institute several projects are carried out using high-resolution optical data from satellites. For example, the processing of Sentinel-2 data developed so far has led to new developments of algorithms that allow an automatic analysis of certain coastal waters for the detection of seagrass. The aim now is to design and modify the algorithms and software components to enable worldwide mapping of seagrass beds and to develop a cloud based online service that enables automated, scalable and efficient seagrass mapping and monitoring over large temporal and spatial dimensions using satellite data.
Your tasks are in detail:
intensive literature research and critical evaluation of scientific publications to develop new solutions for the automated mapping of seagrass populations from satellite data use of the Google Earth Engine for the design and further development of methods and algorithms from machine learning (classification, semantic segmentation) for seagrass mapping. Above all, the robustness of the methodology has to be considered robustification of the methodology so that it can be applied to different data (e.g. Sentinel-2 and Planet satellite data) and different regions (e.g. Europe, Africa, Oceania) and for integration into Geographic Information Systems (GIS) cloud-based development of image annotation, training and validation methods and metrics fundraising, research on scientific funding institutions and their programs and preparation and drafting of applications guidance for students, interns and bachelor students documentation and scientific publication of the results as well as presentations at conferences