Analysis of Vegetation Health in Noril’sk (1990s to present)
Background:
Russian environmental policy has gone through a recent period of privatization. Mining
companies across Russia – specifically Noril’sk Nikel – have sought to improve environmental
conditions to gain legitimacy from financial and environmental institutions1. Vegetation loss in
the vicinity of Noril’sk is a well-documented phenomenon that has been associated with the
city’s long history of mining and smelting nickel, copper, and palladium2. In a more recent,
comprehensive, study supported with fieldwork, various analysis techniques were used to
determine the extent of the vegetation loss up until 19993. Using a variety of techniques –
principal component analysis, post-classification comparison, and vegetation index differencing,
among others4 – a high correlation was found between vegetation loss and pollutant source
locations. However, no significant follow up investigations have been performed since then to
assess whether any changes in environmental policies are improving vegetation health in the
region.
Proposed Technical Approach:
This proposed project seeks to: 1) assess the current state of vegetation loss in the vicinity of
Noril’sk relative to loss in the 1990s as reported by Tutubalina and Rees3, and 2) compare the
change in accuracy of the vegetation loss detection methods relative to the study by Tutubalina
and Rees. These results will both provide insight into the effectiveness of Noril’sk Nikel’s
policies as well as further the understanding of the optimal methodology to use in the region to
identify vegetation loss.
Local considerations:
Noril’sk is located at 69°20'N, 88°06'E in Northern Siberia, and is not open to outside tourism.
Vegetation is most affected by air pollutants – including SO2 and heavy metals – and is only
visible in the summer between late June and early September (see attached photos). Dwarf birch
and lichens, which are more prevalent in the southern portion of the region, have been identified
as most affected by the pollution.
1
Salmi, Olli (2008) Drivers for adopting environmental management systems in the post-Soviet mining industry. Int
Environ Agreements, 8:51–77.
2
Zubareva, O.N., L.N. Zubareva, N. V. Greshilova, and V. I. Kharuk (2002) Zoning of Landscapes Exposed to
Technogenic Emissions from the Norilsk Mining and Smelting Works. Russian Journal of Ecology,
34(6):375-380.
3
Tutubalina, O.V. and W. G. Rees (2001) Vegetation degradation in permafrost region as seen from space: Noril’sk
(1961-1999). Cold Regions Science and Technology, 32(2001):191–203.
4
A summary of possible change-detection methods can be found at:
Lu, D. P. Mausel, E. Brondizios, and E. Moran (2003) Change detection techniques. Int. J. Remote Sensing,
25(12):2365-2407.
The lack of access to Noril’sk by outside visitors reinforces the need for remote sensing in this
project. To lower the cost of the proposed research, sampling and ground truthing by a local
organization will be contacted to conduct the field work. Ground radiometry will be conducted
to analyze vegetation type; requiring at least 100 samples to be taken at 25 locations in the
vicinity of the city.
Atmospheric Conditions:
This project would use the normalized difference vegetation index (NDVI) as a measure of
vegetated area; however, NDVI measurements are extremely sensitive to frequent cloud cover,
which is a problem in high altitude studies such as this one. Because the rapid phenology of the
region also contributes to this distortion, a prior study has developed a phenological correction
technique that removes some of this distortion. However, as this does not entirely correct for
atmospheric conditions, multiple image samples will be necessary. The use of SPOT satellite
imagery, which also does not correct for atmospheric correction, will make multiple samples all
the more necessary since the region cannot be imaged in a single swath. This will need to be
handled by a consultant when performing the vegetation index methods
Analysis of Vegetation Indexing Methods:
The Normalized Difference Vegetation Index (NDVI) uses chlorophyll-producing plants’
relative reflectnace of visible and near infrared (NIR) radiation. By analyzing the difference in
the spectral reflectance of NIR and visible light it is possible to estimate the extent of vegetation
represented by each pixel. A prior study has established 100 classes to identify different types of
local vegetation cover using NDVI; this project will employ that system as well. The principal
component analysis and post-classification comparison methods will then be performed by a
consultant due to the complexity of the methods and the increased difficulty in accounting.
A panchromatic image of Noril’sk from Landsat 7 in the summer – taken on 08/09/2010.
A panchromatic image of Noril’sk from Landsat 7 in the winter – taken on 05/14/2010.