Recent studies intensely discuss the apparent green-up behaviour of Amazon rain forests during dry seasons. One explanation was that the forests were adapted to droughts through deep roots and profit from increased irradiance during the dry season. Another stream of studies found high impact of solar geometry on the often used MODIS Enhanced Vegetation Index (EVI) and calls for paying attention to this effect. One study completely challenges the green-up hypothesis and attributes all seasonal variation to effects of solar geometry. So far no final answer for this debate has been found.
One part in the puzzle is to assess the sensitivity of EVI and other vegetation indices to solar geometry. This has been done with observational data in different studies. In this context, the Unmanned Aerial Vehicle (UAV) of the GRS group offers great flexibility, which has already proven useful in an earlier study. The first part of this study will make use of the UAV in a similar way as in this earlier study. The second part of this study will employ vegetation radiative transfer models (VRTM) to assess the sensitivity of vegetation indices to solar geometry. VRTMs allow to study the solar and viewing geometry effect in a universal way while excluding atmospheric noise like clouds and aerosols. Additionally, they can be expanded to other vegetation indices apart from EVI and sensor band definitions. In this study the Automated Radiative Transfer Models Operator (ARTMO) software package will be exploited. ARTMO offers a single interface to several VRTMs with a MATLAB graphical user interface (GUI).
- Define a set of relevant VIs
- Study sensitivity of VIs to solar geometry with the dataset UAV acquired data set and the ARTMO toolbox
- Investigate mixed effects between changing geometry and other VRTM parameters
- GRS-32306 – Advanced Earth Observation
- Affinity with scripting (e.g. R, Pyhton, MatLab)