Two datasets from real projects were used to validate the proposed method and the experimental results show the effectiveness of the method by being evaluated both quantitatively and visually. An iteration process is performed to minimize the distance with boresight corrections in each epoch, and it stops when the distance is smaller than a predefined threshold or the total number of epochs is reached. Because boresight misalignments exist, a distance between the tie point and the image point of VCP can be found by collinear equations in that image from which the tie point is selected. Space intersection is then performed to obtain the corresponding object coordinate values of the tie points, while the elevation calculated from the space intersection is replaced by the value from the LiDAR data, resulting in a new object point called Virtual Control Point (VCP). The method firstly uses an image matching to generate a tie point set. In this paper, we present a method for the direct georeferencing of images collected by a digital camera integrated in an airborne LiDAR system by automatic boresight misalignments calibration with the auxiliary of point cloud. However, the photogrammetric system calibration is often independent of the LiDAR system and performed by the aerial triangulation method, which needs a test field with ground control points. Experimental results indicate that our proposed model can achieve the best performance compared with other popular models, producing an accuracy of approximately 3 m in planimetry and 2 m in height, thereby providing a generic way to synergistically use multi-source remote sensing data.Īirborne Light Detection and Ranging (LiDAR) system and digital camera are usually integrated on a flight platform to obtain multi-source data. Based on our proposed heterogeneous weight strategy, multi-source optical and SAR images are integrated to improve the geopositioning accuracy. The geometric performance of multi-source optical imagery from the Jilin-1 (JL-1) small satellite constellation is evaluated and analysed first, and then Gaofen-3 (GF-3) SAR images are calibrated based on statistical analysis for the production of virtual control points (VCPs). Therefore, this paper presents a framework for improving the geopositioning accuracy of multi-source datasets obtained from optical and synthetic aperture radar (SAR) satellites, and a novel heterogeneous weight strategy is proposed based on an analysis of the geometric error sources of SAR and optical images. The collection of multi-view datasets is an alternative method for geometric processing without GCPs, but relies heavily on the stability and revisit period of satellite platforms. Traditional methods can improve the accuracy of optical images with the addition of well-distributed ground control points (GCPs), which require considerable financial and human resources. However, compared with that of standard satellite imagery, the geometric performance of imagery from small satellites is relatively poor, restricting their photogrammetric applications. The development of small satellites has provided a new way to obtain repeated observations in a short period. To date, numerous Earth observation datasets from different types of satellites have been widely used in photogrammetric fields, including urban 3D modelling and geographic information systems. This review improves our understanding of satellite stereo geometry and the handling of the dual-satellite stereo images, which are expected to become more common in real mapping applications. Optimal ray intersection can improve the positioning accuracy using dual-satellite stereo images. In particular, the geometric limitation of dual-satellite stereo images often leads to very weak geometry, which degrades the positioning accuracy according to theoretical and experimental studies. This study reviews the image geometry and positioning accuracy of dual-satellite stereo images based on several important studies, including comparisons with conventional single-satellite stereo images. Considering the emergence of various types of satellite data and the requirements to combine these data, it is important to investigate dual-satellite stereo images that integrate two images taken by different satellites. Many previous studies have demonstrated the potential applications of stereo pairs obtained from high-resolution satellites for accurate geo-positioning, but it should be noted that they are based on the conventional use of single-satellite stereo images produced by integrating two images taken by the same satellite.
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