Automated spaceborne detection of degraded vegetation around Monchegorsk, Kola Peninsula, Russia
ABSTRACT This paper develops a simple method for the detection of ‘vegetation anomalies’, locations where the amount of vegetation, estimated through the use of the normalised difference vegetation index (NDVI), is significantly lower than expected on the basis of topographic factors alone. The meth...
| Published in: | Polar Record |
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| Main Author: | |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
Cambridge University Press (CUP)
2011
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| Subjects: | |
| Online Access: | http://dx.doi.org/10.1017/s0032247411000337 https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0032247411000337 |
| Summary: | ABSTRACT This paper develops a simple method for the detection of ‘vegetation anomalies’, locations where the amount of vegetation, estimated through the use of the normalised difference vegetation index (NDVI), is significantly lower than expected on the basis of topographic factors alone. The method is developed and tested using satellite imagery from the area around the town of Monchegorsk on the Kola Peninsula, Russia. This area has been subject to heavy levels of airborne industrial pollution for many years and the intended purpose of the method is to allow the extent of pollution damaged vegetation to be estimated with as few operational decisions as possible by the data analyst, thus suiting it for automation and for the analysis of time-series of satellite images. While the work described in this paper is to some extent preliminary, it does establish that spatial variations in the NDVI of undisturbed vegetation can, at least in the study area, be modelled satisfactorily using topographic variables, and that negative departures from this modelled variation are very strongly associated with industrially mediated damage. |
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