high-resolution satellite imagery, orthorectification, PCI-RPC, ArcGIS-Spline
Digital Object Identifier (DOI)
Given the low accuracy of the traditional remote sensing image processing software when orthorectifying satellite images that cover mountainous areas, and in order to make a full use of mutually compatible and complementary characteristics of the remote sensing image processing software PCI-RPC (Rational Polynomial Coefficients) and ArcGIS-Spline, this study puts forward a new operational and effective image processing procedure to improve the accuracy of image orthorectification. The new procedure first processes raw image data into an orthorectified image using PCI with RPC model (PCI-RPC), and then the orthorectified image is further processed using ArcGIS with the Spline tool (ArcGIS-Spline). We used the high-resolution CBERS-02C satellite images (HR1 and HR2 scenes with a pixel size of 2 m) acquired from Yangyuan County in Hebei Province of China to test the procedure. In this study, when separately using PCI-RPC and ArcGIS-Spline tools directly to process the HR1/HR2 raw images, the orthorectification accuracies (root mean square errors, RMSEs) for HR1/HR2 images were 2.94 m/2.81 m and 4.65 m/4.41 m, respectively. However, when using our newly proposed procedure, the corresponding RMSEs could be reduced to 1.10 m/1.07 m. The experimental results demonstrated that the new image processing procedure which integrates PCI-RPC and ArcGIS-Spline tools could significantly improve image orthorectification accuracy. Therefore, in terms of practice, the new procedure has the potential to use existing software products to easily improve image orthorectification accuracy.
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Citation / Publisher Attribution
Remote Sensing, v. 8, issue 10, art. 827
Scholar Commons Citation
Zhang, Hongying; Pu, Ruiliang; and Liu, Xiuguo, "RPC and ArcGIS-Spline Tools to Improve the Orthorectification Accuracy of High-Resolution Satellite Imagery" (2016). School of Geosciences Faculty and Staff Publications. 1085.