SenFor - Assessment of potentials of the Sentinel-2 mission for the detection of biophysical forest parameters by means of radiation transfer modelling
- Assessment of potentials of the Sentinel-2 mission
for the detection of biophysical forest parameters by means of
radiation transfer modelling
Aerospace Center DLR on behalf of the German Federal
Ministry of Economy and Technology based on the Bundestagresolution
Sentinel Utilization Preparation
Potsdam - Deutsches GeoForschungsZentrum GFZ|
Sektion 1.4 Fernerkundung
Umweltfernerkundung und Geoinformatik
Associate:||Dipl.-Ing. Anne Clasen
Lead:||Prof. Dr. Birgit Kleinschmit |
Dr. Michael Förster 
The detection of biophysical forest parameters as well as detailed tree-species information is of great importance for monitoring ecosystem processes in woodlands. Due to the size of forests and the complex structure, measurment of angular above crown signals and crown components is highly complicated. Thus results from only a few studies are currently available.
The aim of the project SenFor is to evaluate the potential of the Sentinel-2-Mission for assessment of bio-physical forest parameters. Therefore in-situ measurement data of bio-physical parameters and radiative transfer modelling data are analysed. The main task is to assess which Sentinel-2 data specifications are best for forest-parameter modelling and data-retrieval.
A focus is on the high temporal resolution and the strong angular effects (caused by the wide swath of the sensor) of Sentinel-2 data.
The research is performed with the help of the crane-based platform CLAUS (Crane for Leaf and Understorey Spectroscopy), which is part of the TERENO (Terrestrial Environmental Observatories) initiative of the Helmholtz-Association under the direction of the German Research Centre for Geosciences (GFZ). Within several years, there are repeated (phenological) spectral measurements of off-Nadir angles up to 14°. Hence, the effects of the wide swath width of the Sentinel-2 data can be estimated for forests. These values can be used to optimize the radiative transfer model INFORM for the inverse modelling of Sentinel-2 Data. Moreover, the data will be used for data-retrieval algorithms (especially Support Vector Regression and Gaussian Process Regression) to derive bio-physical parameters covering larger areas than just the observation radius of the crane.