Abstract

As the core and foundational technology, on-orbit radiometric calibration of a space-borne sensor is of great importance for quantitative remote sensing applications. As for the space-borne multi-camera mosaic imaging sensor, however, the currently available on-orbit radiometric calibration method cannot carry out the integrated processing of on-orbit absolute radiometric calibration and relative radiometric correction simultaneously between cameras, influencing the accuracy of quantitative applications. Therefore, taking the GaoFen-1 (GF-1) wide-field-of-view (WFV) sensor as an example in this research, an innovative on-orbit radiometric calibration method is proposed to overcome this bottleneck. Firstly, according to the principle of the cross-calibration approach, we retrieve valid MODIS and GF-1 WFV image pairs over the Dunhuang radiometric calibration sites (DRCS) in China by using a set of criteria and extract the radiometric control points (RCPs) connecting in both images. Secondly, the DEM-aided block adjustment of the rational function model is applied to eliminate the geometrical misalignment of GF-1 WFV images at the same orbit. Then, the average digital numbers of spectral and spatial homogeneous surfaces are calculated and chosen as the radiometric tie points (RTPs) extracted from the overlapping region of the adjacent WFV cameras. Thirdly, the radiometric block adjustment (RBA) algorithm is introduced into on-orbit radiometric calibration of the space-borne multi-camera mosaic imaging sensor. Finally, the radiometric calibration coefficients are solved by the least square method. The validation results indicate that our proposed method can acquire high absolute radiometric calibration accuracy and achieve relative radiometric correction between cameras. Compared with the results using the cross-calibration method to calibrate each WFV camera independently, the advantages of RBA are presented. In addition, the uncertainties caused by RCPs’ distribution are discussed, which is beneficial to further optimize the calibration program.

Highlights

  • Radiometric calibration is an important process that converts the digital number (DN) of the Earth observation sensor to the at-sensor spectral radiance or the top-of-atmosphere (TOA) reflectance, which is one of the research hotspots in quantitative remote sensing

  • Taking the GF-1 WFV sensor as an object of investigation, an innovative on-orbit radiometric calibration method is proposed for the space-borne multi-camera mosaic imaging sensor to realize the integrated processing of on-orbit absolute radiometric calibration and relative radiometric correction between cameras

  • After eliminating the geometrical misalignment with the DEM-aided block adjustment of the Rational Function Model (RFM) method, the radiometric tie points (RTPs) are automatically extracted from overlaps of WFV images at the same orbit

Read more

Summary

Introduction

Radiometric calibration is an important process that converts the digital number (DN) of the Earth observation sensor to the at-sensor spectral radiance or the top-of-atmosphere (TOA) reflectance, which is one of the research hotspots in quantitative remote sensing. It is difficult to obtain an image with a large swath and high spatial resolution satellite simultaneously for a single camera. An image from a single camera with high spatial resolution but narrow swath might be wide enough to be acceptable for a small application region, but not for a large application area. When applying images of multi-camera mosaic imaging sensor to a quantitative remote sensing application for a large region, images of adjacent cameras on the same track will be spliced to get a large-swath satellite image with high resolution, which is a major development aim of this type of sensor. If the research region is located at the overlapping area of adjacent camera, in order to increase the access efficiency, the adjacent camera images must be spliced to get the mosaicking image of the whole region of interest

Methods
Results
Conclusion

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.