PRACTISE – Photo Rectification And ClassificaTIon SoftwarE (V.1.0)

Terrestrial photography is a cost-effective and easy-to-use method to derive the status of spatially distributed land surface parameters. It can be used to continuously investigate remote and often inaccessible terrain. We focus on the observation of snow cover patterns in high mountainous areas. The high temporal and spatial resolution of the photographs have various applications, e.g. validating spatially distributed snow hydrological models. However, a one to one analysis of projected model results to photographs requires a preceding georectification of the digital camera images. To accelerate and simplify the analysis, we have developed the "Photo Rectification And ClassificaTIon SoftwarE" (PRACTISE) that is available as a Matlab code. The routine requires a digital camera image, the camera location and its orientation, as well as a digital elevation model (DEM) as input. In case of an unknown viewing orientation an optional optimisation routine using ground control points (GCPs) helps to identify the missing parameters. PRACTISE also calculates a viewshed using the DEM and the camera position and it projects the visible DEM pixels to the image plane where they are subsequently classified. The resulting projected and classified image can be directly compared to other projected data and can be used within any geoinformation system. The Matlab routine was tested using observations of the north western slope of the Schneefernerkopf, Zugspitze, Germany. The obtained results have shown that PRACTISE is a fast and user-friendly tool, able to derive the microscale variability of snow cover extent in high alpine terrain, but can also easily be adapted to other land surface applications.