The efficiency of interior orientation parameters (IOPs) and exterior orientation parameters (EOPs) of the Satellite Pour l'Observation de la Terre 5 (SPOT-5) has been investigated with respect to georeferencing accuracy. A couple of SPOT-5 high-resolution geometric panchromatic level-1A stereoimages with 5-m ground sampling distance covering Zonguldak (Turkey) test field were used for this purpose using orientation parameters provided by metadata files. Ground control points are obtained by Global Positioning System observations. For the purpose of establishing geometric relationship between image and ground coordinate systems, an orbit-attitude parametric model has been used considering imaging geometry of sensor and ephemeris data of satellite. Adjustment consisting of the Gauss-Helmert model was performed in pre- and bundle-adjustment steps. Analyses show that the most efficient parameters are IOPs defined by look angles while EOPs are not significant on the accuracy. The validation of the EOPs and the correlation among IOPs and EOPs are also statistically analyzed. Different variations of point distribution and EOP configurations were preferred, achieving the georeferencing accuracies as ~ ±1 m and ~ ± 5 m at control and check points, respectively. All computations are performed via the developed program package called GeoSpot in Matlab platform.

Geometric high‐resolution satellite imagery (HRSI) is being used increasingly for generating large‐scale topographic maps. The detection of object shapes has become easier and more accurate with improved geometric resolution. The grey value range and spectral resolution are also important for the identification and classification of objects. The nominal ground sampling distance (GSD) must not be the same as the effective GSD corresponding to the information content. In addition, the topographic conditions, object contrast, sun elevation and azimuth and atmospheric conditions influence the object identification. The information content of panchromatic and multispectral satellite images (Landsat 7 ETM+, ASTER, TK‐350, KVR‐1000, SPOT‐5, IRS‐1C, IKONOS, QuickBird and OrbView‐3) available for the Zonguldak test field were investigated with respect to the generation of large‐scale topographic maps. The rule of thumb for topographic mapping of at least 0.1 mm GSD in the map scale with the limit of a maximum of 5 m GSD also for smaller map scales has been confirmed.

Many modelling applications require 3D meshes that should be generated from filtered/cleaned point clouds. This paper proposes a methodology for filtering of terrestrial laser scanner (TLS)‐derived point clouds, consisting of two main parts: an anisotropic point error model and the subsequent decimation steps for elimination of low‐quality points. The point error model can compute the positional quality of any point in the form of error ellipsoids. It is formulated as a function of the angular/mechanical stability, sensor‐to‐object distance, laser beam's incidence angle and surface reflectivity, which are the most dominant error sources. In a block of several co‐registered point clouds, some parts of the target object are sampled by multiple scans with different positional quality patterns. This situation results in redundant data. The proposed decimation steps removes this redundancy by selecting only the points with the highest positional quality. Finally, the Good, Bad, and the Better algorithm, based on the ray‐tracing concept, was developed to remove the remaining redundancy due to the Moiré effects. The resulting point cloud consists of only the points with the highest positional quality while reducing the number of points by factor 10. This novel approach resulted in final surface meshes that are accurate, contain predefined level of random errors and require almost no manual intervention.

An image triplet of Pleiades images covering the area of Zonguldak, Turkey has been investigated. The height to base relation of the first to the last image is just 1:4.5 and for the first and the second image 1:9. This is quite below the usual height to base relation of 1:1.6 for a typical stereo pair of space images. The corresponding small angle of convergence influences the possible vertical accuracy, but images with such a small angle of convergence are more similar to each other as images with larger convergence angles. This enables a better image matching, improving the vertical accuracy and compensating partially the influence of poor intersection geometry. Even over forest areas no matching gaps occurred. Height models are generated with different base configurations and compared with a reference height model. Pleiades images are distributed with 50cm ground sampling distance instead of the physical size of 70cm, the image quality justifies this zooming and also the geometric results are in the range of other space images with originally 50cm GSD. The image orientation by bias corrected Rational Polynomial Coefficients (RPC) is leading with more as 160 ground control points (GCP) to root mean square (RMS) differences slightly below 1.0 GSD of the distributed images (0.5m GSD). Only negligible systematic errors have been identified. With the combination of the first and last image a standard deviation of the generated height model of 1.6m, respectively for flat terrain close to 1.0m has been reached in relation to a reference height model. The small angle of convergence is not as much influencing the height accuracy as according to simple geometric relation.