The Luojia 1-01 Satellite (LJ1-01) is the first professional night-light remote-sensing satellite in China, and thus, it is of pioneering significance for the development of night-light remote sensing satellites in China and the application of remote sensing in the social and economic fields. To ensure the application of night-light remote-sensing data, several studies concerning on-orbit geometric calibration and accuracy verification have been carried out for the complementary metal oxide semiconductor (CMOS) rolling shutter camera of LJ1-01 since the launch of the satellite. Owing to the lack of high-precision nightlight geometric reference at home and abroad, it is difficult to directly calibrate the nighttime light image of LJ1-01. Based on the principle of rolling shutter dynamic imaging, a rigorous geometric imaging model of the time-sharing exposure of the rolling shutter of LJ1-01 is established, and a geometric calibration method for daytime imaging calibration and compensated nighttime light data is proposed. The global public Landsat digital orthophoto image (DOM) with a 15-m resolution and 90-m Shuttle Radar Topography Mission digital elevation model (SRTM-DEM) are used as control data. The images obtained in England, Venezuela, Caracas, Damascus, and Torreon (Mexico) were selected as experimental data. The on-orbit calibration and accuracy verification of LJ1-01 were carried out. Experiments show that after on-orbit geometric calibration, the daytime calibration parameters can effectively compensate for the systematic errors of night-light images. After compensation, the positioning accuracy of night-light images without geometric control points (GCPs) is improved from nearly 20 km to less than 0.65 km. The internal accuracy of the calibrated night-light images is better than 0.3 pixels, which satisfies the requirement of subsequent applications.
CITATION STYLE
Zhang, G., Wang, J., Jiang, Y., Zhou, P., Zhao, Y., & Xu, Y. (2019). On-orbit geometric calibration and validation of luojia 1-01 night-light satellite. Remote Sensing, 11(3). https://doi.org/10.3390/rs11030264
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