Analysis of GCP Chip Resolution for Automatic Accurate Sensor Modeling of Very High-Resolution Satellite Images

초록

Establishing accurate sensor models is an essential process for ensuring positional accuracy in remote sensing applications. This process needs to be developed further, in particular, for Very HighResolution (VHR) satellite images due to their high level of accuracy requirements. This study analyzed the effects of the resolution of Ground Control Point (GCP) chips on automated, accurate sensor modeling for VHR satellite images. Using WorldView-3 images with a resolution of 31.6 cm, accurate sensor models were established by matching the images against GCP chips constructed from aerial images with a resolution of 25 cm and from Unmanned Aerial Vehicle (UAV) images with a resolution of 1.9-3 cm, respectively. The accuracy of sensor models from the two types of GCP chips was evaluated. Results showed that GCP chips from UAV images yielded comparable or better performance than those from aerial images. On average, accurate sensor models were automatically established with an accuracy of 1.08 pixels at the rural site and 1.57 pixels at the urban site using UAV-based GCP chips, with a statistically significant improvement over aerial chips at the rural site. Results also showed that upsampling of raw satellite images improved the accuracy of sensor models. Future research is required on the selection of an optimal upsampling scale, the use of orthorectified UAV images as GCP chips, and the feasibility of achieving subpixel-level accuracy. Nevertheless, this study provides an important basis for advancing automated geometric correction in VHR satellite images.

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