Detection of boreal forest decline with high-resolution panchromatic satellite imagery

Abstract

Long-term operation of the powerful copper-nickel smelter Severonikel in central Kola Peninsula, Arctic Russia has caused decline of boreal forest. Using historical photographs from the American spy satellite CORONA from the 1960s and latest images from civil high-resolution satellites, it is possible to study changes in forest over a long perspective. The study aims were: (1) to detect expansion of the forest decline around the Severonikel smelter for the period 1964-1996 with panchromatic high-resolution image pair; (2) to test the applicability of CORONA and Landsat TM together with a high resolution panchromatic image in automatic change detection studies. High-resolution panchromatic summer images, registered by the CORONA in 1964 and by IRS 1C in 1996, as well as multi-spectral Landsat TM from 1996 were used in the analysis. The simple-difference and PCA methods were applied separately to the datasets CORONA/IRS and CORONA/Landsat TM for change-detection between 1964 and 1996. Both methods showed similar results for the same dataset and close results for the two datasets. Analysis showed several patches of change in forests due to the smelter emissions, fires and logging. Close to the smelter, a further transition from the forest decline to the industrial desert took place at the expanse of the low emission sources, whereas beyond 10 km from the smelter, expansion of the forest damage progressed due to the emissions from the high sources. Landsat TM, despite its coarser spatial resolution, can be a good alternative in change detection studies, if other high-resolution panchromatic satellite data are not available. Historical CORONA can be successfully used in automatic change detection, although, for mosaicking and co-registration, DEM is badly needed.