Together with the German Remote Sensing Data Center, the Remote Sensing Technology Institute forms DLR's Earth Observation Center - the competence center for Earth observation in Germany.

Since the penetration depth of light into water is wavelength-dependent, the water depth in shal-low water can be determined from calibrated multispectral data (bathymetry). Satellite data with high spatial resolution are particularly interesting for large-scale mapping. However, the operators of such satellites do not offer bathymetry as a product, and any available analysis software may provide unreliable results. In addition to the often inaccurate calibration of the sensor, the main challenges are the atmosphere, whose radiation usually accounts for more than 90% of the meas-urement signal, and the usually unknown benthic reflectance.

In order to be able to better estimate the availability of water in Peru in the future, the Peruvian water authority ANA wants to create more accurate bathymetry maps in cooperation with DLR with the help of satellite data. The master thesis shall contribute to ensure a high quality of these maps. Together with our project team and Peruvian colleagues, you will collect data on water depth and atmospheric parameters during a campaign lasting several weeks on lakes in Peru. Using these data you will then determine the accuracy of bathymetry maps, which you will derive from data of the commercial sensor PlanetScope under different atmospheric conditions using the freely available software Acolite and WASI. By varying the software parameters, you investigate the im-pact of calibration and atmospheric correction errors, as well as uncertainties in the benthic reflec-tance, on the calculated water depth. Finally, you will discuss ways to reduce the main error sources and quantify their impact, e.g., adding local information on benthic reflectance or water depth or current atmospheric conditions.