Effect of sensor modelling methods on computation of 3-D coordinates from Cartosat-1 stereo data

Abstract

The orbital and the rational polynomial coefficients (RPC) models are the two most commonly used models to compute a three-dimensional coordinates from an image stereo-pair. But it is still confusing that with the identical user provided inputs, which one of these two models provides more accurate digital elevation model (DEM), especially for mountainous terrain. This study aimed to find out the answer by evaluating the impact of used models on the vertical accuracy of DEM extracted from Cartosat-1 stereo data. We used high-accuracy photogrammetric DEM as the reference DEM. Apart from general variations in statistics, surprisingly in a few instances, both the DEMs provided contrasting results, thus proving the significance of this study. The computed root mean square errors and linear error at 90% (LE90) were lower in case of RPC DEM for various classes of slope, aspect and land cover, thus suggesting its better relative accuracy.

Geometric accuracy improvement of WorldView‐2 imagery using freely available DEM data

“…For the rigorous geometric processing model, when linearised collinearity equations are used to fit the variations of the exterior orientation elements, there are a total of 12 unknown parameters. In theory, at least six GCPs are necessary to solve these 12 unknowns; otherwise, the normal equations will be rank‐deficient (singular), and the unknown parameters cannot be solved (Liang et al., ; Singh et al., ). Empirical geometric processing models avoid sensor geometric imaging processing and use general mathematical functions to represent the relationship between the 3D object‐space coordinates of the ground points and the 2D image‐space coordinates of the corresponding image points.…”

Rational Polynomial Coefficients Modeling and Bias Correction by Using Iterative Polynomial Augmentation

“…For this reason, various vendors in space imaging prefer to produce some nonparametric geometric correction parameters, for instance, RPCs. RPC model allows end user to correct the satellite imagery without the explicit knowledge of physical sensor parameters (Maras 2015;Singh et al 2016;Tao 2001).…”