## 2 Study Area and Data Analysis  
The study area is located in Lower Austria, the north-eastern state of the country (48 deg30'30'' N; 15 deg08'34'' E; WGS84). With elevations ranging from 537 to 846 m above sea level, the region contains different land cover types such as: urban, suburban, rural, arable, grassland, and forested areas. Analysis was conducted based on tri-stereo satellite images acquired with both Pleiades-1B and WorldView-3 optical satellite sensors. Each triplet consists of images that were collected during the same pass from different sensor-viewing angles (along-track stereo): forward, close to nadir, and backward. The location of the study area acquired with the two sensors, with an overlapping surface of 44.5 km\({}^{2}\), is shown in Figure 1.  
For the current analyses, the reference data contains 43 GCPs measured by means of real time kinematic (RTK) GPS with an accuracy of approximately 1 cm. A DTM generated from a LiDAR flight campaign conducted in December 2015 is available, too. The raster DTM is in UTM 33 North map projection, datum WGS 84 with a grid spacing of 1 m. Its height accuracy was checked against the RTK GCPs yielding a \(\sigma_{Z}\) of 0.12 m. We used a digital orthophoto from 2017 at 0.20 m resolution for defining the positions of check points (CP). The planimetric accuracy of the digital orthophoto was verified by computing the differences between the RTK point coordinates and their corresponding position on the orthophoto. The result showed that no shifts larger than one pixel were observed. Each satellite image was delivered with RPCs that allow the transformation between object and image space [22]. Table 1 summarizes the main acquisition parameters like along, across and overall incidence angles, together with corresponding times and covered areas. Additionally, using the equations found in [23] we computed the stereo intersection angles (also called convergence angles in [24]) between each scene and their base-to-height (B/H) ratios. For WorldView-3 satellite imagery the resulting values for the B/H ratios were twice as large as those of the Pleiades imagery. The tri-stereo Pleiades images were provided at sensor processing level, corrected only from on-board distortions such as viewing directions and high frequency attitude variations [25]. For all three images, we performed an optical radiometric calibration using the open source software Orfeo Tool Box [26]. The pixel values were calibrated by the influence of the following parameters: sensor gain, spectral response, solar illumination, optical thickness of the atmosphere, atmospheric pressure, water vapor, and ozone amount, as well as the composition and amount of aerosol gasses. In contrast, the WorldView-3 images were delivered as tri-stereo with relative radiometrically-corrected image pixels. The relative radiometric calibration included a dark offset subtraction and a non-uniformity correction (e.g., detector-to-detector relative gain), which is performed on the raw data during the early stages of product generation. We computed the absolute radiometric calibration for each WorldView-3 image. This was done in two steps: the conversion from image pixels to top-of-atmosphere spectral radiance; and the conversion from top-of-atmosphere spectral radiance to top-of-atmosphere reflectance. The calculations were performed independently for each band, using the equations found in the technical sensor description [27]. Usually, the optical radiometric calibration step is necessary before making any physical interpretation of the pixel values. In particular, this processing is mandatory before performing any comparison of pixel spectrum between several images from the same sensor. In our case, this pre-processing step could be omitted, since it did not change the geometric quality of the images. An important characteristic of both satellites--Pleiades-1B and WorldView-3--is the fast rotation to enable recording three images within the same orbit in less than 1 min.