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


Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2022, Vol. 19, No. 2, pp. 57-69

Creation and radiometric normalisation of cloud-free composite satellite images of snow-covered terrestrial surface for forest monitoring

S.А. Bartalev 1, 2 , I.I. Vorushilov 1, 2 , V.A. Egorov 1, 2 
1 Space Research Institute RAS, Moscow, Russia
2 Center for Forest Ecology and Productivity RAS, Moscow, Russia
Accepted: 22.04.2022
DOI: 10.21046/2070-7401-2022-19-2-57-69
The visible and near infrared remote sensing data collected over snow-covered terrestrial surface are highly informative for forest monitoring purposes. The use of such data leads to an increase in the brightness contrast between forested and forest-free terrestrial surface, as well as to a decrease of the background spectral-reflectance variability. The proposed method for constructing cloud-free composite images is based on time series of remote sensing data and includes at the first stage delineation of snow-free lands, as well as forest-free and forested areas with snow covered terrestrial surface. The subsequent remote sensing data time series statistical analysis is aimed at classification errors filtering, reconstructing data time series to fill in gaps and constructing composite images in a given time interval of satellite observations. The proposed method has demonstrated its applicability to the construction of composite images of snow covered terrestrial surface for the entire territory of Russia using the data collected by MODIS, Proba V and Sentinel 2 remote sensing systems. To increase the analysis efficiency of the multi-annual time series of composite satellite images, a method for their mutual radiometric normalisation has been developed. The method suppresses interannual variations of the spectral reflectance values over the terrestrial surface that are not related to the forest dynamics. The method of radiometric normalisation of composite satellite images of the snow-covered terrestrial surface is based on the use of localised normalising ratios coefficients estimated from the surface reflectance values for forest free reference areas. The application of the radiometric normalisation method for the time series of composite images developed with MODIS data for the period 2001–2021 for the Russian territory indicates a decrease in interannual variations of spectral reflectance values for 93 % pixels corresponding to snow covered terrestrial surface.
Keywords: remote sensing, composite images, snow cover, forest monitoring
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