MONITORING THE EFFECTS OF AIR-POLLUTION ON TERRESTRIAL ECOSYSTEMS IN VARANGER (NORWAY) AND NIKEL-PECHENGA (RUSSIA) USING REMOTE-SENSING

Citation
H. Tommervik et al., MONITORING THE EFFECTS OF AIR-POLLUTION ON TERRESTRIAL ECOSYSTEMS IN VARANGER (NORWAY) AND NIKEL-PECHENGA (RUSSIA) USING REMOTE-SENSING, Science of the total environment, 161, 1995, pp. 753-767
Citations number
35
Categorie Soggetti
Environmental Sciences
ISSN journal
00489697
Volume
161
Year of publication
1995
Pages
753 - 767
Database
ISI
SICI code
0048-9697(1995)161:<753:MTEOAO>2.0.ZU;2-9
Abstract
During the period 1988-1993, NORUT Information Technology carried out a research project on the effects of air pollution on terrestrial ecos ystems in the areas of Varanger (Norway) and Nikel-Pechenga (Russia). To maintain environmental surveillance over the extensive border area, NORUT used satellite remote sensing data in combination with ground t ruth measurements. During the project, we produced vegetation cover ma ps for four different years (1973, 1979, 1985, and 1988), a change det ection image, and a vegetation change map. One of the major changes th at can be observed on the vegetation cover maps is that the area with lichen-dominated vegetation decreased from 2783 km(2) in 1973 to 538 k m(2) in 1988. Comparison of the vegetation cover maps and the change d etection map with the total number of emissions of SO2 from industry s hows a strong correlation between the decrease in lichen-dominated veg etation and the dramatic increase in emissions in the period 1973-1988 . A correlation between the degradation of the vegetation and the SO2 concentration in the air has also been documented. The area of severe air pollution impacts increased from approximately 400 km(2) in 1973 t o more than 5000 km(2) in 1988. This study shows that the critical loa ds/levels of air pollution have been exceeded for lichen-dominated veg etation cover types in the eastern parts of the study area. Finally, t his Study concludes that the use of optical remote sensing (Landsat MS S data) to map vegetation cover changes related to the impacts of air pollution was successful, with an overall classification accuracy of a bout 80%.