Журнал

About Editorial Board Information for authors and reviewers Publication ethics Contacts User Account: send / review a manuscript
Archive
Volume 22, 2025
Номер 1
Volume 21, 2024
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 20, 2023
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 19, 2022
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 18, 2021
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 17, 2020
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6 Number 7
Volume 16, 2019
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 15, 2018
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6 Number 7
Volume 14, 2017
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6 Number 7
Volume 13, 2016
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 12, 2015
Number 1 Number 2 Number 3 Number 4 Number 5 Number 6
Volume 11, 2014
Number 1 Number 2 Number 3 Number 4
Volume 10, 2013
Number 1 Number 2 Number 3 Number 4
Volume 9, 2012
Number 1 Number 2 Number 3 Number 4 Number 5
Volume 8, 2011
Number 1 Number 2 Number 3 Number 4
Volume 7, 2010
Number 1 Number 2 Number 3 Number 4
Issue 6, 2009
Volume 1 Volume 2
Issue 5, 2008
Volume 1 Volume 2
Issue 4, 2007
Volume 1 Volume 2
Issue 3, 2006
Volume 1 Volume 2
Issue 2, 2005
Volume 1 Volume 2
Issue 1, 2004
Volume 1
Search
Find:
русский
ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2024, Vol. 21, No. 6, pp. 48-63

Technology of Meteor-M satellite MSU-MR data automatic georeferencing correction

E.E. Volkova 1 , A.I. Andreev 2 , M.A. Burtsev 1 , A.A. Mazurov 1 , A.M. Matveev 1 , E.I. Kholodov 2 
1 Space Research Institute RAS, Moscow, Russia
2 Far Eastern Center of SRC "Planeta", Khabarovsk, Russia
Accepted: 28.11.2024
DOI: 10.21046/2070-7401-2024-21-6-48-63
The paper discusses the application of correlation methods to improve the accuracy of georeferencing of low-resolution multiband scanning device (MSU-MR) data installed on domestic Meteor-M series spacecraft. The analysis of key obstacles preventing the automatic construction of stable base products based on MSU-MR data with the help of “standard” streamline georeferencing procedures used in Russian reception centers is carried out. Possible methods and approaches to georeferencing correction are considered. The developed automatic two-stage georeferencing scheme, realized on the basis of automatic search for control points and calculation of their displacements by means of phase correlation calculation between the georeferenced and reference images, is described. The scheme includes identification of control points from reference data, subsequent restoration of spacecraft orientation parameters, data reprocessing with the found parameters and automatic quality assessment of the obtained georeferencing. The description of the developed software solution and features of its realization is also given. The results of estimation of accuracy of automatic georeferencing of the MSU-MR data of Meteor-M No. 2-2 and No. 2-3, obtained on the basis of the proposed solution, which for about 70 % of data does not exceed one pixel, are presented.
Keywords: georeferencing of satellite data, satellite data pipeline processing, MSU-MR instruments, Meteor-M satellites, AROSICS, phase correlation
Full text

References:

  1. Akimov N. P., Badaev K. V., Gektin Yu. M., Ryzhakov A. V., Smelyansky M. B., Frolov A. G., Multispectral low-resolution MSU MR scanning device for the Meteor-M space information complex: Principle of operation, evolution, prospects, Raketno-kosmicheskoe priborostroenie i informatsionnye sistemy, 2015, Vol. 2, Iss. 4, pp. 30–39 (in Russian).
  2. Asmus V. V., Dyadyuchenko V. N., Zagrebaev V. A., Milekhin O. E., Soloviev V. I., Uspensky A. B., Development of the space complex for hydrometeorological support based on geostationary satellites of the “Electro-L” series, Vestnik FGUP NPO S. A. Lavochkina, 2012, No. 1, pp. 3–14 (in Russian).
  3. Asmus V. V., Zagrebaev V. A., Makridenko L. A., Milekhin O. E., Soloviev V. I., Uspensky A. B., Frolov A. V., Khailov M. N., System of polar-orbiting meteorological satellites of the Meteor-M series, Meteorologiya i gidrologiya, 2014, No. 12, pp. 5–16 (in Russian).
  4. Bartalev S. A., Egorov V. A., Zharko V. O., Loupian E. A., Plotnikov D. E., Khvostikov S. A., Shabanov N. V., Sputnikovoe kartografirovanie rastitel’nogo pokrova Rossii (Land cover mapping over Russia using Earth observation data), Moscow: IKI RAS, 2016, 208 p. (in Russian).
  5. Burtseva T. N., Abrosimov N. I., Scientific research center Planeta, Zemlya i Vselennaya, 2009, No. 1, pp. 46–50 (in Russian).
  6. Volkova E. V., Estimates of cloud cover and precipitation parameters based on data from the MSU-MR radiometer of the polar-orbiting meteorological satellite “Meteor-M” No. 2 for the European territory of Russia, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2017, Vol. 14, No. 5, pp. 300–320 (in Russian), DOI: 10.21046/2070-7401-2017-14-5-300-320.
  7. Zubkova K. I., Grishantseva L. A., Kurevlev T. G. et al., Algorithm for analyzing spectral characteristics of snow and cloud cover based on MSU-MR data from the “Meteor-M” No. 2 satellite, Raketno-kosmicheskoe priborostroenie i informatsionnye sistemy, 2019, Vol. 6, No. 2, pp. 68–79 (in Russian), DOI: 10.30894/issn2409-0239.2019.6.2.68.79.
  8. Katamanov S. N., Development of an automatic method for geographic referencing of images from the MSU-MR polar-orbiting satellite “Meteor-M” No. 1, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2014, Vol. 11, No. 4, pp. 276–285 (in Russian).
  9. Katamanov S. N., Kachur V. A., Results of geographic referencing of images from the MSU-MR polar-orbiting satellite “Meteor-M” No. 2, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2018, Vol. 15, No. 2, pp. 9–18 (in Russian), DOI: 10.21046/2070-7401-2018-15-2-9-18.
  10. Kashnitsky A. V., Burtsev M. A., Proshin A. A., Technology for creating cloud-free composite images based on data from Sentinel-2 satellites, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2022, Vol. 19, No. 5, pp. 76–85 (in Russian), DOI: 10.21046/2070-7401-2022-19-5-76-85.
  11. Kovalev N. A., Loupian E. A., Balashov I. V. et al., ISDM-Rosleskhoz: 15 years of operation and development, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2020, Vol. 17, No. 7, pp. 283–291 (in Russian), DOI: 10.21046/2070-7401-2020-17-7-283–291.
  12. Kuznetsov A. E., Solovyov V. I., Software for thematic processing of target information from the “Meteor-M” spacecraft, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2014, Vol. 11, No. 2, pp. 68–77 (in Russian).
  13. Lozin D. V., Loupian E. A., Balashov I. V. et al., Adaptation of the MOD14 fire detection algorithm for use with MSU-MR data, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2024, Vol. 21, No. 1, pp. 231–245 (in Russian), DOI: 10.21046/2070-7401-2024-21-1-231-245.
  14. Loupian E. A., Proshin A. A., Burtsev M. A. et al., Experience in the operation and development of the collective use center for archiving, processing, and analyzing satellite data (CKP “IKI-Monitoring”), Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2019, Vol. 16, No. 3, pp. 151–170 (in Russian), DOI: 10.21046/2070-7401-2019-16-3-151-170.
  15. Plotnikov D. E., Kolbudaev P. A., Matveev A. M. et al., Automatic technology for building daily cloud-free composite images from KMSS for quantitative assessment of the state of the Earth’s surface, Materialy 19-i Mezhdunarodnoi konferentsii “Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa” (Proc. 19th Intern. Conf. “Current Problems in Remote Sensing of the Earth from Space”), 15–19 Nov. 2021, Moscow: IKI RAS, 2021, p. 451 (in Russian), DOI: 10.21046/19DZZconf-2021a.
  16. Plotnikov D. E., Kolbudaev P. A., Loupian E. A., An automatic method for subpixel registration of KMSS-M imagery based on coarse-resolution actualized reference, Computer Optics, 2022, Vol. 46, No. 5, pp. 818–827 (in Russian), DOI: 10.18287/2412-6179-CO-1098.
  17. Filei A. A., Retrieval of the cloud top height from Meteor-M No. 2-2 MSU-MR measurements, Optika atmosfery i okeana, 2020, Vol. 33, No. 12, pp. 918–925 (in Russian), DOI: 10.15372/AOO20201203.
  18. Baldwin D., Emery W. J., Spacecraft attitude variations of NOAA-11 inferred from AVHRR imagery, Remote Sensing, 1995, Vol. 16, No. 3, pp. 531–548, DOI: 10.1080/01431169508954417.
  19. Bessho K., Date K., Hayashi M. et al., An introduction to Himawari-8/9 — Japan’s new-generation geostationary meteorological satellites, J. Meteorological Soc. of Japan, Ser. II, 2016, Vol. 94, No. 2, pp. 151–183, DOI: 10.2151/jmsj.2016-009.
  20. Brown L. G., A survey of image registration techniques, ACM Computing Surveys, 1992, Vol. 24, No. 4, pp. 325–376, DOI: 10.1145/146370.146374.
  21. Iwasaki A., Detection and estimation of satellite attitude jitter using remote sensing imagery, Advances in Spacecraft Technologies, 2011, Vol. 13, pp. 257–272, DOI: 10.5772/14402.
  22. Lim Y.-J., Kim M.-G., Kim T. et al., Automatic precision correction of satellite images using the GCP chips of lower resolution, IEEE Intern. Geoscience and Remote Sensing Symp. (IGARSS 2004), 2004, pp. 1394–1397, DOI: 10.1109/IGARSS.2004.1368679.
  23. Lowe D. G., Distinctive image features from scale-invariant keypoints, Intern. J. Computer Vision, 2004, Vol. 60, pp. 91–110, https://doi.org/10.1023/B%3AVISI.0000029664.99615.94.
  24. Scheffler D., Hollstein A., Diedrich H. et al., AROSICS: An automated and robust open-source image co-registration software for multi-sensor satellite data, Remote Sensing, 2017, Vol. 9, Article 676, DOI: 10.3390/rs9070676.
  25. Schott J., Image processing of thermal infrared images, Photogrammetric Engineering and Remote Sensing, 1989, Vol. 55, No. 9, pp. 1311–1321.
  26. Schumann W., Stark H., McMullan K., Aminou D., Luhmann H. J., The MSG system, ESA Bull., 2002, pp. 11–14.
  27. Vallado D. A., Cefola P., Two-line element sets — practice and use, Proc. 63 rd Intern. Astronautical Congress, Naples, Italy, 2012, 14 p.
  28. Van Wie P., Stein M., A Landsat digital image rectification system, IEEE Trans. Geoscience Electronics, 1977, Vol. 15, No. 3, pp. 130–137, DOI: 10.1109/TGE.1977.6498970.
  29. Zitova B., Flusser J., Image registration methods: a survey, Image and Vision Computing, 2003, Vol. 21, pp. 977–1000, DOI: 10.1016/S0262-8856(03)00137-9.