Aerial images have to be captured by an airplane, which involves planning the flight and acquiring the permits for data acquisition. A DSM based on RC 30 frame camera images has already selleck kinase inhibitor been used for an assessment of the increase and decrease of forest area in a mire biotope [16]. Space-borne images provide a cost-efficient alternative to aerial images and can be obtained regardless of various national over-flight restrictions. The launch of IKONOS in 1999 as the world’s first commercial sub-meter satellite opened up new possibilities in 3D data capturing. IKONOS can acquire two images of the same region with a ground resolution of approximately 1 m, which allows for the precise extraction of 3D features. The performance of IKONOS for DSM generation was for example evaluated by Baltsavias et al.
[17] and Eisenbeiss et al. [18]. Accuracy studies for DSM generations based on other commercial stereo satellites such as QuickBird in 2001 with a ground resolution of 0.65 m (e.g., [19,20]), WorldView-1 in 2007 with a ground resolution of 0.5 m (e.g., [21,22]), GeoEye-1 in 2008 with a ground resolution of 0.5 m (e.g., [23,24]) and WorldView-2 in 2009 with a ground resolution of 0.5 m (e.g., [25]) followed these developments. So far most of these studies have been presented at conferences, thus accuracy evaluations of DSM derived from the stereo satellite images mentioned above are still ongoing.Because these very high resolution satellites (VHRS) have a submetric ground resolution, they potentially offer an efficient alternative to airborne surveys for DSM generation.
Thus, the question of the input data source to be used now depends on factors other than ground resolution alone. Therefore, the accuracy assessment of the DSM is crucial in the generation process of a DSM [26], as any elevation errors propagate to the final product and can lead to false conclusions, e.g., about forest canopy properties. The accuracy of a DSM depends on a number of variables such as the roughness of the terrain surface, the interpolation function, interpolation methods and three key attributes (accuracy, density, and distribution) of the source data [27,28]. Thus the target land cover type is expected to influence the error budget of the derived DSM [29]. In order to take into account the influence of topographic variations, land cover classes should be distinguished in the accuracy assessment [30,31].
Prior studies showed that the accuracy of a DSM over forested areas is lower than over bare land (e.g., [31]).For space-based DSM accuracy assessment to be reliable, it is important to know how accurately the satellite image material is georeferenced with the delivered rational Batimastat considering polynomial coefficients (RPCs). These coefficients describe the image position by means of two third-order polynomials as a function of the ground coordinates [32].