Abstract
The Pleiades satellite constellation provides very high resolution multi-spectral optical data at a ground sampling distance of about 0.7 m at nadir direction. Due to the highly agile pointing angle capacity in the range of ±47 degrees the sensors are optimal for detailed earth observation. They are able to collect stereo and tri-stereo datasets in one overflight with a swath width of 20 km. Such images allow 3D mapping of any region on the Earth’s surface at very high resolution with high accuracy, where the reconstruction of the heights is based on along-track stereo. This work presents methodologies and workflows within the fields of remote sensing and computer vision that are used (1) to densely reconstruct digital surface models (DSM), (2) to derive digital terrain models (DTM), and (3) to generate multi-spectral ortho-rectified products. Within this process, the accuracy of the geometric sensor models, given as rational polynomial coefficient (RPC) models, plays a crucial role. Therefore, an assessment is performed on two distinct test sites discussing the initial 2D geo-location accuracy of the given sensor models. An optimization scheme is presented to adjust the given RPC models yielding 3D geo-location accuracies of 0.5 m in planimetry and 1 m in height. In the frame of surface model generation important issues like epipolar rectification, hierarchical stereo matching, and fusion of heights are reported. The main outcomes are that the sensor accuracy is within the range as defined by Astrium, but that a sensor model optimization is obligatory when it comes to highly accurate 3D mapping. The presented workflow generates mapping products with a GSD of 0.5m. The derived DSMs and DTMs show a high level of detail, thus enabling varying applications on a large scale, like land cover and land use classification, change detection, city modelling, or forest assessment.
Highlights
The Pléiades satellite constellation is a dual system comprising the two identical satellites Pléiades-1A and Pléiades-1B
Another focus of this paper is the extraction of dense digital surface models (DSM) and digital terrain models (DTM) from Pléiades image data, covering both theory and practical applications
Starting from a pair of images to be used for the generation of a digital surface model (DSM), the following procedures are applied: (a) Epipolar rectification of both stereo images based on the optimized sensor models such that a pre-defined point in the reference image can be found along a horizontal line in the search image, i.e., a line parallel to the image column direction: While the concept of epipolar geometry was first realized for perspective images, appropriate implementations were further made for Pléiades-like pushbroom geometries [18] and for SAR geometries [15]
Summary
The Pléiades satellite constellation is a dual system comprising the two identical satellites Pléiades-1A and Pléiades-1B. A significant innovation and advantage of Pléiades, is the capability to acquire even three images for an area, taken from the same orbit at along track forward-, nadir-, and backward-view of the Roland Perko et al.: Very High Resolution Mapping with the Pléiades Satellite Constellation sensor and through the possibility of an across-track swipe Such image triplets are denoted as tri-stereo datasets. The study contains an assessment of the 2D geo-location accuracy, employing the initial sensor models as well as optimized sensor models, and an assessment of the 3D mapping accuracy involving both stereo as well as tri-stereo datasets Another focus of this paper is the extraction of dense digital surface models (DSM) and digital terrain models (DTM) from Pléiades image data, covering both theory and practical applications. It should be noted that the presented workflow was already successfully applied by other research groups (e.g., in [5] or in [6])
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