Affiliation:
1. Department of Geoinformatic Engineering, Inha University, 100 Inharo, Michuhol-gu, Incheon 22212, Republic of Korea
Abstract
Recent advancements in satellite technology have significantly increased the availability of high-resolution imagery for Earth observation, enabling nearly all regions to be captured frequently throughout the year. These images have become a vast source of big data and hold immense potential for various applications, including environmental monitoring, urban planning, and disaster management. However, obtaining ground control points (GCPs) and performing geometric correction is a time-consuming and costly process, often limiting the efficient use of these images. To address this challenge, this study introduces a Rational Function Model (RFM)-based rigorous bundle adjustment method to enhance the relative geometric positioning accuracy of multiple KOMPSAT-3A images without the need for GCPs. The proposed method was tested using KOMPSAT-3A images. The results showed a significant improvement in geometric accuracy, with mean positional errors reduced from 30.02 pixels to 2.21 pixels. This enhancement ensured that the corrected images derived from the proposed method were reliable and accurate, making it highly valuable for various geospatial applications.
Funder
Ministry of Land, Infrastructure and Transport
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