Geometric Accuracy Assessment of QuickBird Basic Imagery Using Different Operational Approaches

Abstract

The new very high-resolution space satellite images, such as QuickBird and Ikonos, open new possibilities in cartographic applications. This work has as its main aim the assessment of a methodology to achieve the best possible geometric accuracy in orthorectified imagery products obtained from QuickBird basic imagery which will include an assessment of the methodology's reliability. Root Mean Square Error (RMSE), mean error or bias, and maximum error in 79 independent check points are computed and utilized as accuracy indicators. The ancillary data were generated by high accuracy methods: (a) check and control points were measured with a differential global positioning system, and (b) a dense digital elevation model (DEM) with grid spacing of 2 m and RMSE z of about 0.31 m generated from a photogrammetric aerial flight at an approximate scale of 1:5000 that was used for image orthorectification. Two other DEMs with a grid spacing of 5 m (RMSE z = 1.75 m) and 20 m (RMSE z = 5.82 m) were also used. Four 3D geometric correction models were used to correct the satellite data: two terrain-independent rational function models refined by the user, a terrain-dependent model, and a rigorous physical model. The number and distribution of the ground control points (GCPs) used for the sensor orientation were studied as well, testing from 9 to 45 GCPs. The best results obtained about the geometric accuracy of the orthorectified images (two dimensional RMSE of about 0.74 m) were computed when the dense DEM was used with the 3D physical and terrain-dependent models. The use of more than 18 GCPs does not improve the results when those GCPs are extracted by stratified random sampling.

Bias Compensation for Rational Function Model Based on Total Least Squares

“…() assessed the accuracy of QuickBird stereo‐images, and a similar evaluation was conducted by Aguilar et al. (). Though the accuracy of geopositioning with vendor‐provided RPCs is sufficient for many applications, there exist significant systematic biases in them as reported in the aforementioned literature.…”

“…Grodecki and Dial (2003) proposed a model for the block adjustment of HRSI described by the RFM and achieved the same accuracy as the ground station block adjustment with a full physical camera model. Noguchi et al (2004) assessed the accuracy of QuickBird stereo-images, and a similar evaluation was conducted by Aguilar et al (2007). Though the accuracy of geopositioning with vendor-provided RPCs is sufficient for many applications, there exist significant systematic biases in them as reported in the aforementioned literature.…”

Real-time velocity measurement to linear motion of a rigid object with monocular image sequence analyses

“…One possible way to perform this reconstruction is through the computing of stereo pairs images and reconstruct the space object by the application of photogrammetric methods [1,17].…”

“…To proceed this reconstruction, it is necessary, at first, to carry out internal and external orientation of the camera and after performing the rectification and registration of such images acquired in stereo vision, then you should search for homologous pixels between images of the stereo pair for reconstructing these points in the space object [1,6,24].…”

Rational function modeling for spaceborne SAR datasets

“…Different methods are proposed to solve the key problem of optimum determination of RF model parameters (Samadzadegan et al, 2005;Puatanachokchai and Mikhail, 2008). Considering the limited accuracy of vendorprovided RFM parameters, a few methods were developed to refine these existing RF models through the usage of ground control points (GCP) Di et al, 2003;Fraser and Hanley, 2003;Aguila et al, 2007;Xiong and Zhang, 2009;Tong et al, 2010). A variety of practical applications of RFM in geometric processing of high-resolution optical imagery were explored in depth, including sensor orientation (Fraser and Hanley, 2005;Fraser et al, 2006), block adjustment (Grodecki and Dial, 2003), geopositioning (Li et al, 2007), image rectification (Tao and Hu, 2001b), and 3D reconstruction Tao et al, 2004;Toutin, 2006).…”