TECHNICAL MECHANICS
ISSN (Print): 1561-9184, ISSN (Online): 2616-6380

HOME    ABOUT THIS JOURNAL    EDITORIAL BOARD    GUIDE FOR AUTHORS    CURRENT    JOURNAL ISSUES    CONTACTS

UDC 629.78

Technical mechanics, 2024, 4, 17 - 30

OPTICAL METHODS OF EARTH REMOTE SENSING AND PROSPECTS FOR THEIR USE IN COMMERCIAL SPACECRAFT

Khramov D. O., Pyrozhenko O. O.

Khramov D. O.
Institute of Technical Mechanics of the National Academy of Sciences of Ukraine and the State Space Agency of Ukraine

Pyrozhenko O. O.
Institute of Technical Mechanics of the National Academy of Sciences of Ukraine and the State Space Agency of Ukraine

      Commercial remote sensing spacecraft currently use optical multispectral and hyperspectral, thermal infrared and radar imaging methods. At the same time, the capabilities of existing and promising remote sensing methods are not fully utilized in commercial satellites. Trends in the development of optical remote sensing methods are analyzed with the aim to determine prospects for the application of these methods in commercial remote sensing satellites. Optical multispectral, hyperspectral, and lidar imaging and methods based on chlorophyll fluorescence measurement are considered. It is shown that multispectral optical imaging is developing by way of increasing the number of spectral channels, using narrower channels, and increasing the spatial resolution in tasks of detailed and survey imaging and by way of increasing the repeatability of imaging without reducing the spatial resolution due to the use of constellations of inexpensive small satellites. Hyperspectral and lidar imaging face the problems of processing and transmission of a large amount of data. A promising way to solve these problems is to process data immediately onboard the spacecraft. In lidar imaging, there are prerequisites for the formation of a constellation of satellites to provide a regular annual global coverage of the Earth's dry land. Remote sensing methods based on chlorophyll fluorescence are at the stage of accumulation and generalization of experimental data. At the same time, these methods open new opportunities in solving many ecological and agricultural problems. The integration of spectral and structural information provided by optical imaging methods and lidars may be used in the future to solve a wide range of problems. It is possible to form orbital constellations in which individual satellites will use different remote sensing methods and constellations of universal satellites equipped with several types of imaging devices.
     

remote sensing, multispectral imaging, hyperspectral imaging, lidar, solar-induced chlorophyll fluorescence

1. Kramer H. J. Observation of the Earth and Its Environment. Berlin: Springer, 2002. https://doi.org/10.1007/978-3-642-56294-5

2. Fowler M. J. F. Declassified Intelligence Satellite Photographs. Archaeology from Historical Aerial and Satellite Archives. W. Hanson, I. Oltean (Eds.). New York, Springer, 2012. Pp. 47-66. https://doi.org/10.1007/978-1-4614-4505-0_4

3. Kondrat'ev K. Ya., Buznikov A. A., Vinogradov B. V., Volkov V. N., Gorbatko V. V., Smoktii O. I., Orlov V. M. Some results of Earth spectrophotometry from the Soyuz-T. Doklady AN SSSR. 1970. V. 195. No. 5. Pp. 1084-1087.

4. Qian S.-E. Hyperspectral satellites, evolution, and development history. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2021. No. 14. Pp. 7032-7056. https://doi.org/10.1109/JSTARS.2021.3090256

5. Bedini E. The use of hyperspectral remote sensing for mineral exploration: a review. Journal of Hyperspectral Remote Sensing. 2017. V. 7. No. 4. Pp. 189-211. https://doi.org/10.29150/jhrs.v7.4.p189-211

6. Lelong C. C. D., Pinet P. C., Poilve H. Hyperspectral imaging and stress mapping in agriculture. Remote Sensing of Environment. 1998. V. 66. No. 2. Pp. 179-191. https://doi.org/10.1016/S0034-4257(98)00049-2

7. Terentev A., Dolzhenko V., Fedotov A., Eremenko D. Current state of hyperspectral remote sensing for early plant disease detection: a review. Sensors. 2022. V. 22. No. 3. 757. https://doi.org/10.3390/s22030757

8. Khramov D. O., Volosheniuk O. L. Analysis of the state of the art and the trends in the development of orbital constellations of small agriculture-oriented Earth remote sensing spacecraft. Teh. Meh. 2023. No. 4. Pp. 31-39. https://doi.org/10.15407/itm2023.04.031

9. Diaz J. C. F., Carter W. E., Shrestha R. L., Glennie C. L. LiDAR Remote Sensing. Handbook of Satellite Applications. J. Pelton, S. Madry, S. Camacho-Lara (Eds.). Springer, 2017. https://doi.org/10.1007/978-3-319-23386-4_44

10. Borsah A. A., Nazeer M., Wong M. S. LIDAR-based forest biomass remote sensing: a review of metrics, methods, and assessment criteria for the selection of allometric equations. Forests. 2023. V. 14. 2095. https://doi.org/10.3390/f14102095

11. Lowe C. J., McGrath C. N., Hancock S., Davenport I., Todd S., Hansen J., Woodhouse I., Norrie C., Macdonald M. Spacecraft and optics design considerations for a spaceborne lidar mission with spatially continuous global coverage. Acta Astronautica. 2024. V. 214. Pp. 809-816. https://doi.org/10.1016/j.actaastro.2023.10.042

12. McGrath C., Lowe C. J., Macdonald M., Hancock S. Investigation of very low Earth orbits (VLEOs) for global spaceborne lidar. CEAS Space Journal. 2022. V. 14. No. 4. Pp. 625-636. https://doi.org/10.1007/s12567-022-00427-2

13. Lagutin A. Mordvin E. Y., Volkov N. Estimates of the terrestrial gross primary production for the south of Western Siberia in 2014-2021 according to OCO-2 and OCO-3 data. 28th International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics. 2022. V. 12341. https://doi.org/10.1117/12.2645053

14. Chen R. Liu L., Liu X., Liu Z., Gu L., Rascher U. Improving estimates of sub-daily gross primary production from solar-induced chlorophyll fluorescence by accounting for light distribution within canopy. Remote Sensing of Environment. 2024. V. 300. 113919. https://doi.org/10.1016/j.rse.2023.113919

15. Kritten L. Preusker R., Fischer J. A new retrieval of sun-induced chlorophyll fluorescence in water from ocean colour measurements applied on OLCI L-1b and L-2. Remote Sensing. 2020. V. 12. No. 23. 3949. https://doi.org/10.3390/rs12233949

16. Meroni M., Rossini M., Guanter M., Alonso L., Rascher U., Colombo R., Moreno J. Remote sensing of solar-induced chlorophyll fluorescence: Review of methods and applications. Remote Sensing of Environment. 2009. V. 113. No. 10. P.2037-2051. https://doi.org/10.1016/j.rse.2009.05.003

17. Gopal R., Mishra K. B., Zeeshan M., Prasad S. M., Joshi M. M. Laser-induced chlorophyll ?uorescence spectra of mung plants growing under nickel stress. Current Science. 2002. V. 83. No. 7. Pp. 880-884.

Copyright (©) 2024 Khramov D. O., Pyrozhenko O. O.

Copyright © 2014-2024 Technical mechanics