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, 2022, Vol. 19, No. 1, pp. 170-178

Assessment of changes in vegetation of the Norilsk industrial region with remote sensing data, based on the trend analysis of spectral indices

O.M. Zheleznyi 1 , O.V. Tutubalina 1 , V.I. Kravtsova 1 
1 Lomonosov Moscow State University, Moscow, Russia
Accepted: 20.01.2022
DOI: 10.21046/2070-7401-2022-19-1-170-178
The vegetation of the Norilsk industrial region, degraded over large areas under the influence of airborne industrial pollution, which varied at different stages of the metallurgical plant’s activity, is influenced by climate warming. To assess changes in vegetation, imagery from Landsat-5, -7, -8 satellites is used for the entire period of their operation since 1984, their analysis carried out by means of the cloud platform Google Earth Engine. The imagery was masked from clouds and snow, and cross-calibration of the imaging systems of different satellites was performed. The assessment of the state of vegetation was based on the maximum values of NDVI in each pixel for the summer season. Statistical tests were carried out on this series of data, including simple linear regression and analysis of Mann-Kendall trends; so, the analysis of changes is based on NDVI trends. To better account for the changes in tree and shrub cover, a similar analysis of NDMI was carried out. Analysis of the spatial structure of the trend showed that the maximum stable growth of both indices is observed southeast of Norilsk, in the Rybnaya River valley, the area most affected by pollution in the past. Validation via modern very high-resolution images confirms the appearance of grass and shrubs in the areas of the strong positive trend. A similar study based on MODIS/Terra-Aqua data for 2000–2020 confirmed the existence of significant NDVI trend in the Rybnaya valley. Analysis of changes in vegetation based on very high resolution images showed that the greatest increase in NDVI is observed for vegetation in ravines and gullies.
Keywords: satellite images, vegetation index, NDVI, vegetation recovery, Norilsk, Arctic
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