ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa


Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2018, Vol. 15, No. 2, pp. 251-259

Weather defined optical properties of atmosphere in the nighttime visible and infrared remote sensing

А.А. Poyda 1 , M.N. Zhizhin 2, 3, 4 , A.V. Andreev 2 
1 National Research Center “Kurchatov Institute”, Moscow, Russia
2 Space Research Institute RAS, Moscow, Russia
3 University of Colorado, Broomfield, USA
4 NOAA National Centers for Environmental Information, Boulder, USA
Accepted: 20.12.2017
DOI: 10.21046/2070-7401-2018-15-2-251-259
Multispectral nighttime remote sensing of the Earth allows detecting and evaluating various parameters of visible and infrared sources, including radiance, temperature, area, etc. One of the key difficulties in this case is the local variation of the optical properties of the atmosphere due to the absorption and scattering of radiation from the ground sources in clouds, fog, aerosols and precipitation. The article presents a new method of local estimation and correction of atmospheric distortions on nighttime sate­llite images. The method is based on models of multiple scattering of light rays in the atmosphere, allowing to consider its optical density and the average size of aerosol particles (fog, rain). Unlike previous works, which were primarily aimed at computer synthesis and evaluation of the effect of weather conditions on night photographs and computer games, this work is aimed at analyzing satellite images of the Earth’s night surface and determining the true parameters of the light sources (electric lights, gas flares) and local atmospheric and meteorological conditions (clouds, smog, smoke, rain). The results of this work will make it possible to allocate small distortions on multispectral images, as well as to restore blurred and spectrally distorted remote sensing data for local meteorological conditions.
Keywords: nighttime remote sensing, optical properties of atmosphere, correction of atmospheric distortions
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  1. Zhizhin M. N., Poyda A. A., Tyutlyaeva E. O., Konoplev V. V., Elvidge C. D., Monitoring nochnykh sudovykh ognei po dannym VIIRS (Monitoring of night fishing boat lights with VIIRS), Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2018, Vol. 15, No. 1, pp. 101–119.
  2. Cao C., Bai Y., Quantitative Analysis of VIIRS DNB Nightlight Point Source for Light Power Estimation and Stability Monitoring, Remote Sens., 2014, Vol. 6, pp. 11915–11935.
  3. Elvidge C. D., Baugh K. E., Zhizhin M., Hsu F. C., Automatic Boat Identification System for VIIRS Low Light Imaging Data, Remote Sens., 2015, Vol. 7, No. 3, pp. 3020–3036, DOI: 10.3390/rs70303020.
  4. Lagarias J. C., Reeds J. A., Wright M. H., Wright P. E., Convergence Properties of the Nelder-Mead Simplex Method in Low Dimensions, SIAM J. Optimization, 1998, Vol. 9, No. 1, pp. 112–147.
  5. McHardy T. M., Zhang J., Reid J. S., Miller S. D., Hyer E. J., Kuehn R. E., An improved method for retrieving nighttime aerosol optical thickness from the VIIRS Day/Night Band, Atmos. Meas. Tech., 2015, Vol. 8, Issue 11, pp. 4773−4783.
  6. Metari S., Deschenes F., A new convolution kernel for atmospheric point spread function applied to computer vision, In: Proceedings of the IEEE 11th International Conference on Computer Vision (ICCV, 2007), Rio de Janeiro, Brazil, 2007, pp. 1−8.
  7. Narasimhan S. G., Nayar S. K. Shedding light on the weather, In: Proceedings of the 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’03), 2003, pp. 665–672.
  8. Narasimhan G., Nayar S. K. Interactive (De) weathering of an image using physical models, IEEE Workshop on Color and Photometric Methods in Computer Vision (In Conjunction with ICCV), Nice, France, 2003, pp. 528–535.