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

机译:传感器建模方法对从Cartosat-1立体数据计算3-D坐标的影响

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摘要

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.
机译:轨道和有理多项式系数(RPC)模型是从图像立体对计算三维坐标的两个最常用的模型。但是仍然令人困惑的是,使用相同的用户提供的输入,这两个模型中的哪一个提供了更准确的数字高程模型(DEM),尤其是对于山区地形。这项研究旨在通过评估二手模型对从Cartosat-1立体声数据中提取的DEM的垂直精度的影响来找到答案。我们使用高精度摄影测量DEM作为参考DEM。除了统计学上的一般差异外,在某些情况下,令人惊讶的是,两个DEM均提供了相反的结果,从而证明了这项研究的重要性。对于各种坡度,坡度和土地覆盖率,在RPC DEM情况下,计算出的均方根误差和90%的线性误差(LE90)较低,因此表明其相对精度更高。

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