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Amendments to Articles 3.3 and 3.4 of the Kyoto Protocol have meant that detection of vegetation change may now form an interracial part of national soil carbon stocks. In this study multispectral multi-platform satellite data was processed to detect change to the surface vegetation of four peatland sites and one heath in Ireland. Spectral and spatial thresholds were used on difference images between master and slave data in the extraction of temporally invariant targets for multi-platform cross calibration. The Kolmogorov–Smirnov test was used to evaluate any difference in the cumulative probability distributions of the master, slave and calibrated slave data as expressed by the D statistic, with values reduced by an average of 89.7% due to the cross calibration procedure. A change detection model was created which incorporated a spatial threshold of 9 pixels and a standard deviation (SD) spectral threshold. Kappa accuracy values for the five sites ranged from 80 to 97%, showing that 1.5 SD was the optimum spectral threshold for detecting vegetation change. Change detection results showed mean percentage change ranging from 2.11 to 3.28% of total area and cumulative change over the observed time period of between 15.24 and 49.27% of total area.  相似文献   
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