Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2018, Vol. 15, No. 2, pp. 84-99
Experience of long-term monitoring of phytocenosis condition using temporary irregular remote sensing data in zones of increased radiation hazard
K. Yu. Silkin
1 , A.N. Kizeyev
2 1 Voronezh State University, Voronezh , Russia
2 N. A. Avrorin Polar-Alpine Botanical Garden-Institute of Kola Science Centre RAS, Apatity, Russia
Accepted: 19.02.2018
DOI: 10.21046/2070-7401-2018-15-2-84-99
The technique of condition assessment of phytocenosis on the basis of irregular long-term data of remote sensing of Earth is developed and approved. Remote studying of boreal landscapes faces a persistent problem of exclusive rarity of absolutely cloudless days. During continuous annual study of medium-sized, but numerous objects located in a certain area, it often occurs that not all the objects are visible at the same time among clouds during the next overflight of the satellite. Although such satellite as Landsat overfly every location on the globe approximately twice a month, the observations of each object are rather irregular. That is why very scarce data obtained at different times of the vegetation period are available for a long-term monitoring. Such observations are very difficult for direct comparison. The proposed technique was developed for the solution of this problem. Its essence is assessing the key parameters at the peak of a vegetative season use the scarce and irregular values obtained. In this work, the NDVI index was chosen key parameter, however, the offered technique can be applied also to other similar indexes. The test of this technique was for the first time performed by an example of the stationary monitoring sites system represented by bilberry pine forests. This system was developed within a 30-km zone around the Kola nuclear power plant which is a potentially dangerous object of nuclear power on the territory of the European Arctic. The received results allowed to draw conclusions on spatial and temporary influence of the nuclear power station on the condition of the environment.
Keywords: Kola nuclear power plant, phytocenosis, remote sensing, NDVI index, monitoring, algorithm
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