How to decide which oblique image has the highest mapping potential for monoplotting method: a case studies on river erosion and floods
When studying the development of different geomorphic processes, floods, glaciers or even cultural heritage through time, one cannot rely only on regular photogrammetrical procedures and metrical images. In a majority of cases the only available images are the archive images with unknown parameters of interior orientation showing the object of interest in oblique view. With the help of modern high resolution digital elevation models derived from aerial or terrestrial laser scanning (lidar) or from photogrammetric stereo-images by automatic image-matching techniques even single nonmetric high or low oblique image from the past can be applied in the monoplotting procedure to enable 3D-data extraction of changes through time. The first step of the monoplotting procedure is the orientation of an image in the space by the help of digital elevation model (DEM). When using oblique images tie points between an image and DEM are usually too sparse to enable automatic exterior orientation, still the manual interactive orientation using common features can resolve such shortages. The manual interactive orientation can be very time consuming. Therefore, before the start of the manual interactive orientation one should be certain if one can expect useful results from the chosen image. But how to decide which image has the highest mapping potential before we introduce a certain oblique image in orientation procedure? The test examples presented in this paper enable guidance for the use of monoplotting method for different geoscience applications. The most important factors are the resolution of digital elevation model (the best are the lidar derived ones), the presence of appropriate common features and the incidence angle of the oblique images (low oblique images or almost vertical aerial images are better). First the very oblique example of riverbank erosion on Dragonja river, Slovenija, is presented. Than the test example of September 2010 floods on Ljubljana moor is discussed. Finally, case study from November 2012 floods is presented. During November 2012 floods an initiative was launched to gather as much non-metrical images of floods as possible from casual observers (volunteered image gathering). From all gathered images the guidelines presented before helped to pick out 21% images which were used for monoplotting.