Remote sensing of industrial impact on Arctic vegetation around Noril'sk, northern Siberia: preliminary results

This study applies remote sensing techniques for monitoring nonferrous meta l smelting impacts in the extreme environment of northern Siberia. Ground a nd at-satellite reflectance and normalized difference vegetation index (NDV I) values for different vegetation types have been compared and a hybrid su pervised-unsupervised classification of Landsat TM data performed, based on field and ancillary data. This has allowed us to distinguish several degre es of vegetation damage in tundra and forests. However, it was difficult to differentiate between some significant classes, such as damaged grass tund ra and sparse dead larch forests with a grass understorey. We suggest possi ble refinement of our results, including the combination of images taken at different phenological stages and from different sensors. However, it shou ld be noted that the north-Siberian environment presents unusually severe l imitations of optical-infrared satellite observation possibilities and prob lems in imagery interpretation. Standard indicators of vegetation vigour, s uch as NDVI, widely applied at lower latitudes, become less informative in highly variable tundra and pre-tundra ecosystems.